Q2 2025 DigitalOcean Holdings Inc Earnings Call

Krista: Ladies and gentlemen, thank you for standing by. My name is Krista, and I will be your conference operator today. At this time, I would like to welcome everyone to DigitalOcean's second quarter 2025 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press star one again. Thank you. I would now like to turn the conference over to Melanie Strate, Head of Investor Relations. Melanie, you may begin.

Ladies and gentlemen, thank you for standing by. My name is Krista, and I will be your conference operator. Today, at this time, I would like to welcome everyone to DigitalOcean's second quarter 2025 earnings conference call. All lines have been...

Been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number 1 on your telephone keypad. And if you would like to withdraw your question, press star 1 again, thank you. And I would now like to turn the conference over to Melanie Strait head of investor relations Melanie you may begin.

Melanie Strate: Thank you, and good morning. Thank you all for joining us today to review DigitalOcean's second quarter 2025 financial results. Joining me on the call today are Padmanabhan Srinivasan, our Chief Executive Officer, and Matt Steinfort, our Chief Financial Officer. Before we begin, let me remind you that certain statements made on the call today may be considered forward-looking statements, which reflect management's best judgment based on currently available information. Our actual results may differ materially from those projected in these forward-looking statements, including our financial outlook. I direct your attention to the risk factors contained in our filings with the SEC, as well as those referenced in today's press release that is posted on our website. DigitalOcean expressly disclaims any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements made today.

Melanie Strate: Additionally, non-GAAP financial measures will be discussed on this conference call, and reconciliation to the most directly comparable GAAP financial measures can be found in today's earnings press release, as well as in our investor presentation that outlines the financial discussion on today's call. A webcast of today's call is also available in the IR section of our website. With that, I will turn the call over to Paddy.

Thank you and good morning. Thank you all for joining us today to review. Digital oceans. Second quarter 2025 Financial results joining me on the call today are Patty shuni Vasan, our chief executive officer and Matt Stein for our Chief Financial Officer. Before we begin, let me remind you that certain statements. May on the call today may be considered forward-looking statements which reflect Management's. Best judgment, based on currently available information. Our actual results May differ materially from those projected in these forward-looking statements including our financial Outlook. I direct your attention to the risk factors contained in our filings with the SEC as well as those referenced. In today's press release that is posted on our website, digital ocean expressly, disclaims any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements made today. Additionally, non-gaap Financial measures will be discussed on this conference call and Reconciliation to the most directly comparable gaap Financial measures can

Sound in today's earnings press release, as well as in our investor presentation that outlines the financial discussion on today's call, a webcast of today's call is also available in the IR section of our website. And with that, I will turn the call over to Patty.

Padmanabhan Srinivasan: Thank you, Melanie. Good morning, everyone, and thank you for joining us today as we review our second quarter 2025 results. We continue to make meaningful progress on the strategy we laid out at our investor day back in April. This is evidenced by our strong second quarter results and supported by the fact that we are raising our full-year guidance on both revenue and profitability metrics. My comments today will include a recap of our Q2 financial results and an update on both our progress in product innovation and our enhanced go-to-market strategy across both core cloud and AI, which are enabling over 174,000 digital native enterprise customers to scale on our platform. Let me start with the second quarter financial results highlighted on slide 10 of our earnings deck.

Thank you, Melanie. Good morning, everyone, and thank you for joining us today as we review our second quarter 2025 results.

We continue to make meaningful progress on the strategy. We laid out at our investor day back in April.

This is evidence by our strong second, quarter results, and supported by the fact that we are raising our full year guidance, on both revenue and profitability metrics.

My comments today will include a recap of our Q2 Financial results and an update on both our progress and products Innovation. And our enhanced go to market strategy, across both core cloud and AI which are enabling over 174,000, digital, native Enterprise customers to scale on our platform.

Padmanabhan Srinivasan: The growth momentum from Q1 continued into the second quarter, with revenue of $219 million growing 14% year over year. We saw excellent strength in our AI/ML business, with revenue growing north of 100% year over year. Revenue from our Scalar Plus customers, our customers who were at a $100,000 plus annual run rate during the quarter, continued to see strong growth during the quarter at 35% year over year and increased to 24% of total revenue. Finally, we achieved incremental ARR in the second quarter of $32 million, our highest incremental ARR since Q4 of 2022, and the highest organic incremental ARR in over three years. Given our strong top-line performance in the first half of the year and our confidence in the second half outlook, we are raising our full-year revenue guidance range to $888 million to $892 million.

Let me start with the second quarter of financial results. Highlighted on slide, 10 of our earnings deck.

The growth momentum from q1 continued into the second quarter with revenue of 290 million growing 14% year-over-year.

We saw excellent strength in our AIML business with Revenue growing north of 100% year-over-year.

Revenue from our scalar. Plus customers, or customers who were at $100,000 plus annual run rate during the quarter continued to see strong growth during the quarter at 35% year-over-year and increased to 24% of total revenues.

Finally, we achieved incremental ARR in the second quarter of $32 million, which is the highest incremental ARR since Q4 of 2022, and the highest organic incremental ARR.

in over 3 years.

Padmanabhan Srinivasan: We are also excited about the traction we are getting with larger customers and increase in committed contracts. I spoke last quarter about a multi-year $20 million plus committed deal, and this was a contributor to the material growth in our remaining performance obligation balance as we continue to seek and secure large multi-year deals with our higher spend customers and key strategic partners. Not only did our momentum carry over to the second quarter, but also the growth continues to come with healthy profitability, including adjusted free cash flow of $57 million, which is 26% of revenue. As a result of this performance, we are raising our full-year free cash flow guide to 17% to 19% of revenue, demonstrating our ability to accelerate revenue while maintaining attractive free cash flow margins.

Topline performance in the first half of the year and our confidence in the second half outlook; we're raising our full year revenue guidance range to $888 million to $892 million.

We are also excited about the traction we are getting with larger customers and the increase in committed contracts.

I spoke last quarter about a monthly year, 20 million plus committed deal. And this was a contributor to the material growth in our remaining performance obligation balance as we continue to see. And secure large multi-year deals with our higher, spend customers and key strategic partners.

Not only did our momentum carry over to the second quarter, but also the growth to come with the growth continued to come with healthy profitability, including adjusted free cash flow of 57 million, which is 26% of Revenue.

Padmanabhan Srinivasan: Turning to the balance sheet, we continue to make progress on our capital allocation priority and remain on track to address the outstanding 2026 convertible debt prior to the end of this calendar year. Matt Steinfort will go into further details on this front in his prepared remarks. Now, let me give you some updates on the product innovation that we continue to deliver for our digital native enterprise customers, which you can see highlighted on slides 11 and 12 in the earnings presentation. During the quarter, we released more than 60 new products and features addressing the needs of our higher spend customers, which includes builders, scalers, and Scalar Plus customers, who now drive 89% of our revenue.

As a result of this performance, we're raising our full year. Free cash flow guide to 17 to 19% of Revenue. Demonstrating, our ability to accelerate Revenue while maintaining attractive free cash flow margins.

turning to the balance sheet, we continue to make progress on our Capital, allocation priorities, and remain on track to address the outstanding 2026 convertible debt, prior to the end of this calendar year,

Maps will go into further details on this front in his prepared remarks.

Now, let me give you some updates on the product Innovation that we continue to deliver for our digital native Enterprise customers, which you can see, highlighted on slides, 11, and 12 in the earnings presentation.

Padmanabhan Srinivasan: Notably, 64 of our top 100 customers have adopted a product or a feature released within the last year, and 26 of the top 100 customers have adopted a new capability released within the last quarter. Both clear proof points of the impact product innovation is having on our digital native enterprise customers. Let me now provide a few product highlights from the quarter, starting with core cloud. This past quarter, we officially announced our Atlanta data center, and its resources are now available to all customers. As a reminder, this is our newest and largest data center, and it is purpose-built to deliver high-density GPU infrastructure optimized for AI inferencing, which requires a lot more than just GPUs.

During the quarter, we released more than 60 new products and features addressing the needs of our higher-spend customers, which include Builders, Scalars, and Scalar Plus customers, who now drive 89% of our revenue.

Notably 64 of our top. 100 customers have adopted a product or a feature released within the last year.

And 26 of the top. 100 customers have adopted a new capability released within the last quarter.

Both Clear Proof points of the impact products innovation is having on our digital native enterprise customers.

Let me now provide a few product highlights from the quarter starting with core cloud.

This past quarter, we officially announced our Atlanta Data Center, and its resources are now available to all customers.

Padmanabhan Srinivasan: This data center has our core cloud stack, including compute, storage, and other cloud features that are critical to enabling AI-native customers to run full-stack applications powered by AI and not just the training or inference part of their software. This agentic cloud data center infrastructure is a key differentiating factor for us over other neoclouds, as it provides a complete stack for running sophisticated AI applications that have comprehensive needs beyond GPUs. More on that a little later. During the quarter, we continue to build capabilities for larger digital native enterprises. These customers typically require high-quality storage, especially for AI workloads. To support that requirement, we enabled NFS, or Network File Systems, for GPUs so that customers can run the most demanding GPU applications with access to higher performance object storage to meet the demands of enterprise workloads such as video streaming and data lakes.

As a reminder, this is our newest and largest data center when it is purpose-built to deliver high density. GPU infrastructure optimized for AI inferencing which requires a lot more than just gpus.

This data center has our core Cloud stack, including compute storage and other Cloud features that are critical to enabling AI, native customers to run full stack applications, powered by Ai and not just the training or inference part of their software.

This agentic cloud data center infrastructure is a key differentiating factor for us over other Neo clouds, as it provides a complete stack for running sophisticated AI applications that have comprehensive needs beyond GPUs.

More on that, a little later.

during the quarter, we continue to build capabilities for larger digital native Enterprises

These customers typically require high-quality storage, especially for AI workloads.

To support that requirement. We enabled NFS or network file systems for gpus. So that customers can run the most demanding GPU applications with access to higher performance object storage to meet the demands of Enterprise workloads such as video streaming and data links.

Padmanabhan Srinivasan: We also introduced two advanced networking features in public preview: Bring Your Own IP Address, or BYOIP, and Network Address Translation Gateways, or NAT gateways. These are critical capabilities that will enable more and larger digital native enterprise workloads to migrate to DigitalOcean. BYOIP allows customers to use their existing publicly routable IP addresses on DigitalOcean rather than having to acquire new DigitalOcean-specific IP addresses. This makes it easy for customers to lift and shift their workloads to our platform without requiring extensive changes to their applications, while NAT gateway allows a customer's resources to securely access the internet from within their virtual private cloud on the DigitalOcean platform. These innovations on the core cloud platform are enabling us to scale and win more workloads from our digital native enterprise customer base.

We also introduced two advanced networking features in public preview.

Bring your own IP address or BYO IP and network address translation, gateways or Nat gateways.

These are critical capabilities that will enable more and larger digital native enterprise workloads to migrate to this solution.

By OIP allows customers to use their existing publicly routable IP addresses on do, rather than having to acquire new. Digital solution, specific IP addresses

This makes it easy for customers to shift their workloads to our platform without requiring extensive changes to their applications. While that Gateway allows the customer's resources to securely access the internet from within their Virtual Private Cloud on the DigitalOcean platform.

Padmanabhan Srinivasan: To leverage that traction, we are complementing our industry-leading product-led growth motion with a small dedicated migrations team to support customers moving existing workloads from hyperscalers and other clouds to DigitalOcean's platform, and we facilitated 76 of these migrations during the quarter. One example of this is a company called Exitium, a next-generation cybersecurity provider delivering innovative, no-cost incident response as part of its fully managed security operations center, or SOC, offering. Designed for businesses and managed service providers, or MSPs, Exitium's managed SOC provides real-time threat detection, threat hunting, and incident response, all without the high costs typically associated with legacy solutions. Exitium signed an 18-month contract with DigitalOcean, selecting the platform to migrate from other cloud providers due to our compelling total cost of ownership, performance, and ease of use, enabling Exitium to deliver its cutting-edge cybersecurity solutions more efficiently and at scale.

To leverage attraction, your complimenting, our industry-leading product like growth motion, with a small dedicated migrations team to support customers. Moving existing, workloads from hyperscalers, and other clouds to digital Ocean's platform. And we facilitated 76 of these migrations. During the quarter,

1 example of this is a company called xcm

And Next Generation, a cybersecurity provider, is delivering innovative, no-cost incident response as part of its fully managed Security Operation Center or SOC offering.

Designed for businesses and managed service providers (MSPs), Excites Manage. SOCKS provides real-time threat detection, threat hunting, and incident response—all without the high cost typically associated with legacy solutions.

Exciting and 18-month contracts. With digital ocean, selecting the platform to migrate from other Cloud providers, due to our compelling total cost of ownership performance and ease of use enabling exciting to deliver. Its Cutting Edge, cyber Security Solutions, more efficiently and at scale,

Padmanabhan Srinivasan: ServeDe.host, a Scalar Plus customer that offers managed hosting specifically tailored for the craft content management system, has already adopted our newly released Network Address Translation Gateway, enabling their customers to securely access the internet within their DigitalOcean virtual private cloud. We are also very excited about the progress we are making on our AI/ML platform, which we now call the DigitalOcean Gradient AI Agentic Cloud, which complements our full-stack general-purpose cloud. Slide eight in the earnings presentation shows the power of having these two platforms side by side, enabling our customers to take full advantage of the integrated stack that is required to build and run AI-powered applications in the future. The Gradient AI Agentic Cloud has three components: Gradient AI Infrastructure, Gradient AI Platform, and Gradient AI Agents.

Served the host, a Scalar Plus customer that offers managed hosting specifically tailored for the Craft Content Management System, has already adopted our newly released Network Address Translation Gateway, enabling their customers to securely access the internet within their DigitalOcean Virtual Private Cloud.

We're also very excited about the progress we're making on our AIML platform.

Which we now call the Digital Ocean Gradient: AI, agentic cloud.

Which complements our full stack general purpose, cloud.

Flight 8 in the earnings presentation shows, the power of having these 2 platforms side by side, enabling our customers to take full advantage of the integrated stack that is required to build and run AI, powered applications in the future.

The gradient AI agentic cloud has 3 components.

Gradient, AI infrastructure.

Padmanabhan Srinivasan: Let me start with the Gradient AI Infrastructure, where we expanded our GPU Droplets lineup significantly to now include eight major types, including the H, L, and RTX series GPUs from NVIDIA, and the latest Instinct series GPUs from AMD. Another major update that makes Gradient AI Infrastructure great for inferencing is a new inference-optimized GPU Droplet, which simplifies the setup and deployment of LLMs by leveraging Docker. This new GPU Droplet comes pre-configured with VLLM and includes built-in optimizations like multi-GPU parallelism, smart batching, faster and higher token generation, built-in support for Hugging Face model downloads, speculative decoding, prompt caching, and multi-model concurrency so that customers can go from deployment to serving tokens in minutes on any GPU Droplet without having to do all these steps manually.

Gradient AI platform and Gradient AI agents.

Let me start with the Gradient AI infrastructure, where we expanded our GPU Droplets lineup significantly to now include eight major types, including the H, L, and RTX series GPUs from Nvidia, and the latest Instinct series GPUs from AMD.

Another major update that makes gradient. AI infrastructure. Great for inferencing is a new inference, optimized GPU droplet, which simplifies the setup and deployment of llms by leveraging Docker, and this new GPU droplet. Comes pre-configured with v lln, and includes built-in optimizations like multi-gpu parallelism.

Smart batching faster and higher token. Generation built-in support for hugging face model downloads.

Padmanabhan Srinivasan: We recently announced a collaboration with AMD that provides DO customers with access to AMD Instinct MI325X GPU Droplets in addition to MI300X Droplets. These GPUs deliver high-level performance at lower TCO and are ideal for large-scale AI inferencing workloads. Another example of this growing collaboration between the two companies is the Gradient AI Infrastructure powering the recently announced AMD Developer Cloud, which enables developers and open-source contributors to test drive AMD Instinct GPUs instantly in a fully managed environment managed by our Gradient AI Infrastructure. This enables developers to start AI development with zero hardware investment and accelerate the time to value in tasks like benchmarking and inference scaling. This further advances our mission of democratizing access to AI while maintaining the quality, performance, and flexibility our customers have come to expect from DO. Let's look at how customers are taking advantage of our Gradient AI Infrastructure.

Speculative decoding prompt caching and multi-model concurrency. So that customers can go from deployment to serving tokens in minutes on any GPU droplet without having to do all these steps manually.

We recently announced a collaboration with AMD that provides do customers with access to AMD. Instinct me 325x GPU droplets. In addition to me, 300X droplets.

These gpus deliver high-level performance at lower TCO and are ideal for large scale, AI inferencing workloads.

Another example of this growing collaboration between the 2 companies is the gradient. AI infrastructure. Powering the recently announced AMD developer Cloud which enables developers and open source contributors to test drive. AMD Instinct gpus instantly in a fully managed environment, managed by our gradient, AI infrastructure.

This enables developers to start AI development with zero, Hardware investment and accelerate, the time to value in tasks. Like benchmarking and inference scaling,

This further advances our mission of democratizing access to AI while maintaining the quality performance and flexibility. Our customers have come to expect from do

Let's look at how customers are taking advantage of our gradient. AI infrastructure.

Padmanabhan Srinivasan: Featherless.ai is a serverless AI inference platform offering API access to an expansive and growing catalog of open weight models, primarily Hugging Face models like Llama, Mistral, Quen, DeepSeek, RWKV, and more. Featherless.ai leverages DigitalOcean for its simplicity and price performance, and they were an early adopter of our AMD MI300X GPU Droplets, which offer industry-leading price performance and ease of use for inference workloads. Another GPU Droplet customer is ScribeAI, a digital native enterprise specializing in AI-generated documentation, which is used by 94% of the Fortune 500 companies. ScribeAI migrated their AI/ML training workloads to DigitalOcean from competitive cloud providers, and it is now leveraging DO's GPU Droplets to build and train their process documentation and knowledge sharing platform.

Like llama Mistral quen deep sea or wkv and more.

Featherless AI leverages DigitalOcean for its simplicity and price performance. They were an early adopter of our AMD MI300 X GPU droplets, which offer industry-leading price performance and ease of use for inference workloads.

Another GPU droplet. Customer describe AI.

And Native a digital. Native Enterprise specialized in AI generated documentation, which is used by 94% of the Fortune 500 companies.

AI migrated their AIML training workloads to DigitalOcean from competitive cloud providers. It's now leveraging DIYOS GPU droplets to build and train their process documentation and knowledge-sharing platforms.

Padmanabhan Srinivasan: Moving on to the next layer of our Gradient AI Agentic Cloud, we recently announced the general availability of DigitalOcean Gradient AI Platform, which provides the industry's easiest and most cost-effective platform for developing production-grade AI agents with automated safety and security guardrails. The Gradient AI Platform, as shown on the right side of slide eight of the earnings deck, is a one-of-a-kind platform that caters to the end-to-end agent development lifecycle, or ADLC for short, enabling AI-native SaaS and any software application customer to build, test, deploy, monitor, and operate agentic AI software. Customers can use a rich set of proprietary and open-source foundation models, including OpenAI, Anthropic, Mistral, DeepSeek, and Llama, as high-performance serverless endpoints. These serverless endpoints automatically scale to meet real-time application demands, thus freeing customers from having to manage compute resources on their own.

Moving on to the next layer of our gradient. AI agentic cloud.

We recently announced the general availability of DigitalOcean Gradient, an AI platform that provides the industry's easiest and most cost-effective solution for developing production-grade AI agents with automated safety and security guardrails.

the gradient AI platform as shown on the right side of slide, 8 of the earnings deck is a 1-off, kind platform that caters to the end-to-end agent, development, life, cycle, or adlc, for short, enabling AI native

SAS and any software application. Customer to build test deploy Monitor and operate agentic, AI software.

Customers can use a rich set of proprietary and open-source Foundation models, including openai and topics Mistral deep, sea and llama.

As high performance serverless endpoints.

These serverless endpoints automatically scale to meet real-time application demands.

Thus.

Padmanabhan Srinivasan: The Gradient AI Platform provides built-in guardrails that verify AI behavior and new best-in-class agent evaluation frameworks to drive high accuracy and relevance of AI results and a robust experimentation capability to deliver optimal AI performance. Over 14,000 agents have been created since announcing this platform, which is almost double the number of agents last quarter. More than 6,000 customers have leveraged this platform since January, with 30% of these customers being new to DigitalOcean. One of the customers leveraging our new Gradient AI Platform is Quickest, with a Q, a leading AI-powered collaborative workspace product that helps product marketing and sales teams generate strategy documents, campaigns, and playbooks using shared AI personas. Quickest leverages the Gradient AI Platform to create persona-generating agents, enabling model comparisons and orchestrating tasks on the Gradient AI Platform to fetch and summarize the marked-down content.

Freeing customers from having to manage compute resources on their own.

The gradient AI platform.

Provides built-in guard rails. That verify, AI behavior and new best-in-class agent, evaluation Frameworks to drive high, accuracy and relevance of AI results and a robust experimentation capability to deliver optimal AI performance.

Well, we're 14,000 agents have been created since announcing this platform which is almost double the number of Agents last quarter.

more than 6,000, customers have leveraged this platform since January, with 30% of these customers being new to digital ocean,

1 of the customers leveraging. Our new gradient AI platform is

Quickest with a Q.

A leading.

AI powered, collaborative, workspace product, that helps product marketing, and sales teams generate strategy documents campaigns and playbooks using shared AI personas

Padmanabhan Srinivasan: Quickest chose DigitalOcean because they needed a flexible and scalable infrastructure to support complex AI workflows, and they valued the simplicity of deploying agents and integrating them to the Quickest product line with very little coding involved. Moving on to the Gradient AI Agents layer, our first commercial AI agent is the Cloudways Copilot, which continuously monitors critical server components like the web stack, disk space, iNodes, and host health to detect issues in real time, diagnose root causes, and deliver actionable recommendations faster than traditional alerting systems. An example of a customer leveraging this product is Mint Media, a full-service media and marketing company specializing in video production and digital marketing. Mint Media uses our Cloudways Copilot GenAI agents to automatically detect and remediate web hosting issues.

Quickest. Leverages the gradient AI platform to create Persona generating agents enabling model comparisons and orchestrating tasks on the gradient. AI platform to fetch and summarize, the markdown content.

Quickest chose digital ocean because they needed a flexible and scalable infrastructure to support complex, Ai workflows and they valued the Simplicity of deploying agents and integrating them to the quickest product line. With very low little coding involved.

Moving on to the gradient, AI agents layer. Our first commercial, AI agent is the Cloud waste co-pilot which continuously monitors critical server components.

Like the web stack disk space, I notes and post help to detect issues in real time. Diagnose root causes and deliver actionable recommendations faster than traditional alerting systems.

An example of a customer leveraging. This product is mint media, a full service media and marketing company, specializing in video production and digital marketing.

Padmanabhan Srinivasan: Mint Media manages over 180 websites and saw significant time savings by leveraging Cloudways Copilot and the associated AI-powered insights and automated issue resolution. What previously required hours of manual debugging is now handled in minutes through the agent's detailed actionable recommendations. In addition to the product innovations we delivered, we also made material progress on the go-to-market front during this quarter. From a new customer acquisition perspective, we saw meaningful progress in the top of the funnel from our product-led growth enhancements, with revenue from core cloud customers in their first 12 months significantly outpacing growth of prior years, which is a great leading indicator of future growth potential. Our direct sales motion and the strong ecosystem partnerships are driving more AI-native customers with large-scale inferencing requirements than we have ever seen in the past.

Mint media uses our cloud-based co-pilot Genai agents to automatically detect and remediate web posting issues.

Mint media, manages over 180 websites and saw significant Time Savings by leveraging cloud-based. Co-pilot and the associated AI power, insights and automated issue resolution.

What previously required hours of manual? Debugging is now handled in minutes.

Through the agents detailed actionable recommendations.

In addition to the product Innovations, we delivered. You also made material progress on the go to market front during this quarter.

You from core Cloud customers and their first 12 months.

Significantly outpacing growth of Prior years which is a great leading indicator of future growth potential.

Padmanabhan Srinivasan: Our growing success with these marquee customers is evident in the increased RPO that I mentioned earlier in my comments, and we anticipate this trend to continue as we scale out our AI capabilities. In closing, I am pleased both by the results of the second quarter and by the progress we are making on the strategy that we articulated at our investor day back in April. We maintained our top-line growth momentum from Q1 to Q2 while maintaining healthy profitability metrics, enabling us to raise our guidance across both revenue and profitability metrics for the fiscal year 2025. We delivered continued product innovation and both drove improved performance in our industry-leading product-led growth engine and continue to get traction with our direct sales go-to-market motion, especially for AI.

Our direct sales motion and the strong ecosystem partnerships are driving more AI-native customers with large-scale inferencing requirements than we have ever seen in the past.

Our growing success with these marquee customers is evident in the increased RPO that I mentioned earlier in my comments, and we anticipate this trend to continue as we scale out our AI capabilities.

In closing I am pleased both by the results of the second quarter. And by the progress, we're making on the strategy that we articulated at our investor day back in April.

We maintained our Topline growth momentum from q1 to Q2 while maintaining healthy profitability metrics, enabling us to raise our guidance across both revenue and profitability metrics for the fiscal year 2025.

Padmanabhan Srinivasan: We recently launched the Gradient AI Platform into full general availability, a significant step in our offering to our customers a twin stack of cloud capabilities as outlined in slide eight of the earnings slide deck. In a single unified stack, we provide a mature, complete general-purpose cloud, and on the other stack, a modern agentic AI cloud. These integrated stacks enable AI-native customers to run inferencing at scale while taking advantage of the core cloud modules and digital native customers to build AI directly into their software applications without having to do the heavy lifting of dealing with AI infrastructure. With this unique twin cloud and AI stack, we are getting increasing momentum with AI-native companies with larger scale inferencing workflows, and we are expanding our partnerships with key ecosystem players in the AI domain.

We delivered continued product innovation and both drove improved performance in our industry-leading product, like Growth Engine, and continue to get traction with our direct sales go-to-market motion, especially for AI.

We recently launched the gradient AI platform into full General. Availability. A significant step in our offering.

Um, to our customers at Twin stack of cloud capabilities, as outlined in slide. 8 of the earnings slide deck.

in a single unified stack, we provide a mature, complete general purpose, cloud,

And on the other stack, a modern agentic, AI cloud.

These integrated Stacks enable AI, native customers to run inferencing at scale while taking advantage of the core.

Core Cloud modules and digital native customers to build AI directly into their software applications without having to do the heavy lifting of dealing with AI infrastructure.

With this unique twin.

Padmanabhan Srinivasan: We are also making good progress on our balance sheet and refinancing priorities, positioning us for a strong 2026. Thank you, and I'll now turn it over to Matt.

Cloud and AI Stacks. We are getting increasing momentum. With AI, native companies with larger scale, inferencing, workloads. And our, we are expanding our Partnerships with key ecosystem players in the AI domain.

We're also making good progress on our balance sheet and refinancing priorities positioning us for a strong 2026.

Thank you, and I'll now turn it over to Matt.

Matt Steinfort: Thanks, Paddy. Good morning, everyone, and thanks for joining us today. As Paddy discussed, we are very pleased with our Q2 2025 performance, and we are confident in our ability to sustain and build on this momentum in the latter half of the year. In my comments, I will walk through our Q2 results in detail, provide an update on our balance sheet and capital allocation strategy, and share our third quarter and full-year 2025 financial outlook. Starting with the top line, revenue in the first quarter was $219 million, up 14% year over year. Our annual run rate revenue, or ARR, was $875 million, which was $32 million above Q1. This incremental ARR of $32 million was the highest incremental ARR since Q4 of 2022 and the highest organic incremental ARR achieved in over three years.

Thanks Patty. Good morning everyone and thanks for joining us today.

As Patty discussed. We are very pleased with our Q2 2025 performance and we are confident in our ability to sustain and build on this momentum in the latter half of the year.

in my comments, I'll walk through our Q2 results in detail, provide an update on our balance sheet and capital allocation strategy and share our third quarter and full year 2025 Financial Outlook,

Starting with the top line revenue in the first quarter was 219 million of 14% year-over-year.

Annual run rate revenue or ARR was 875 million.

Which was 32 million above q1.

Matt Steinfort: We continue to build and strengthen our relationships with our higher spend customers and key strategic partners. This is evidenced by the material increase in our remaining performance obligation balance as we continue to secure large multi-year deals with our digital native enterprise customers, which is an early but promising new go-to-market motion for the company. Our product innovation and go-to-market enhancements are resonating with this target customer base. In Q2, revenue from our Scalars Plus customers, or customers whose annualized run rate revenue in the quarter was greater than $100,000 and who represent 24% of overall revenue, grew 35% year over year with a 23% increase in customer count. This is clear evidence of the increasing traction that we are getting with our largest customers as they expand their use of our core cloud products and adopt our new AI offering.

This incremental ARR of 32 million was the highest incremental ARR, since Q4 of 2022 and the highest organic incremental ARR achieved in over 3 years.

We continue to build and strengthen our relationships with our higher, spend customers and key strategic partners.

This is evidenced by the material increased in our remaining performance obligation balance. As we continue to secure, large, multi-year deals with our digital native Enterprise customers, which is an early. But promising, new, go to market motion for the company.

Our product Innovation and go to market. Enhancements are resonating with this Target. Customer base.

In Q2 revenue from our scalars plus customers, or customers whose annualized run rate Revenue in the quarter, was greater than 100,000 and who represent 24% of overall Revenue. Grew 35% year-over-year with a 23% increase in customer count.

this is clear evidence of the increasing traction that we are getting with our largest customers as they expand their use of our core Cloud products and adopt new AI offering

Matt Steinfort: Q2 revenue growth was primarily driven by improvements in customer acquisition across both core cloud and AI, as well as strong customer adoption of our AI/ML products. As Paddy mentioned, revenue from core cloud customers in their first 12 months significantly outpaced growth of prior years, which is a great leading indicator of future growth as these stronger recent cohorts not only drive up revenue from customer acquisition, but also they should positively contribute to net dollar retention when they reach their 13th month and become part of our NDR cohort. Our Q2 net dollar retention was 99%, up from 97% in the same quarter last year and within the expected range that we communicated on the prior quarter's call.

YouTube Revenue growth is primarily driven by improvements in customer acquisition across both core, cloud and AI as well as strong customer adoption of our AIML products.

As Patty mentioned revenue from core Cloud customers in their first 12 months significantly outpaced growth with prior years which is a great leading indicator of future growth as these stronger recent cohorts. Not only drive up revenue from customer acquisition, but also they should positively contribute to net dollar retention when they reach their 13th month and become part of our ndr cohort.

Matt Steinfort: We also delivered strong AI/ML revenue growth in Q2 as we continue to see a robust demand environment, particularly for inference workloads, with AI revenue growing north of 100% year over year. Turning to the P&L, we delivered strong performance on all of our key profitability metrics. Gross margin for the second quarter was 60%, which was 100 basis points higher than the prior year. Adjusted EBITDA was $89 million, an increase of 10% year over year. Adjusted EBITDA margin was 41% in the second quarter, approximately 100 basis points lower than the prior year. Non-GAAP diluted net income per share was $0.59, a 23% increase year over year. This increase is a direct result of expanding per share profitability by driving durable revenue growth while exercising ongoing cost efficiency.

We also delivered strong AIML Revenue growth in Q2 as we continue to see a robust demand environment, particularly for inference workloads with AI Revenue growing north of 100% year-over-year.

To the p&l, we delivered strong performance on all of our key profitability metrics.

Gross margins for the second quarter were 60%, which is 100 basis points higher than the prior year.

Adjusted ibitta was 89 million and increase at 10% year-over-year. Adjusted ebit margin was 41% in the second quarter. Approximately 100 basis points, lower than the prior year.

Non-gaap diluted. Net income per share was 59. Cents a 23% increase year-over-year.

Matt Steinfort: GAAP diluted net income per share was $0.39, a 95% increase year over year as we continue to grow revenue, drive operating leverage, and prudently manage stock-based compensation. Q2 adjusted free cash flow was $57 million, or 26% of revenue, up significantly from our front-loaded Q1, which included a large portion of the upfront investment required to bring the Atlanta data center online. As I'll detail later in my comments, we remain confident in our ability to deliver attractive adjusted free cash flow margins for the full year, although the timing of capital investment payments will continue to create quarter-to-quarter variations in adjusted free cash flow margins, hence our highlighting of the trailing 12-month adjusted free cash flow margins on slide 15. Our balance sheet continues to be strong as we continue to maintain material cash and cash equivalents and ended the quarter with $388 million in cash.

Is a direct result of expanding per share, profitability by driving durable Revenue growth while exercising ongoing cost decisions.

Diluted net income per share was 39, cents a 95% increase year-over-year as we continue to grow Revenue, Drive operating leverage, and prudently, manage stock-based compensation.

Due to adjusted free. Cash flow was 57 million or 26% of Revenue of significantly from our front-loaded q1. Which included a large portion of The Upfront investment required to bring the Atlanta Data Center Online.

As I'll detail later in my comments, we remain confident in our ability to deliver attractive adjusted free cash flow margins for the full year.

Although the timing of capital investment payments will continue to create order to quarter variations in adjusted free cash flow. Margins. Hence our highlighting of the trailing 12 month. Adjusted free cash. Flow margin on slide 15.

Matt Steinfort: We also continue to execute our share repurchase program in the quarter, with $20 million of repurchases in Q2, buying back approximately 691,000 shares. This brings our cumulative share repurchases since IPO to $1.6 billion and 34.8 million shares through June 30, 2025. At the end of Q2, we had $3.4 million remaining on our current share repurchase authorization. On the debt front, we continue to actively evaluate the market and our financing alternatives and remain committed to fully addressing the 2026 convert over the balance of this calendar year. We have multiple attractive financing options available to us, including convertible debt, bank debt, and bonds, and we plan to tap into these markets as needed to optimize our long-term cost of capital. Before we move on to guidance, I will highlight one non-cash item related to both the balance sheet and the P&L.

Our balance sheet continues to be strong. As we continue to maintain material cash and cash equivalents and ended the quarter with 388 million in cash.

We also continue to execute our share repurchase program in the quarter, with $20 million of repurchases in Q2, buying back approximately 691,000 shares.

This brings our cumulative share repurchases since IPO to $1.6 billion and 34.8 million shares through June 30, 2025.

At the end of Q2, we had $3.4 million remaining on our current share repurchase authorization.

On the debt front, we continue to actively evaluate the market and our financing Alternatives and remains committed to fully addressing the 2026 convert over the balance of this calendar year.

We have multiple attractive financing options available to us, including convertible debt Bank, debt, and bonds, and we plan to tap into these markets as needed to optimize our long-term cost of capital.

Matt Steinfort: We continue to evaluate the necessity of our valuation allowance on certain existing tax deferred tax assets each quarter in accordance with U.S. GAAP. While the valuation allowance is still necessary for Q2, in the latter half of fiscal 2025, we may release all or a portion of our valuation allowance of $109 million, which was discussed in our most recent 10K as well as in our most recent 10Q. When released, we estimate this would have the financial impact of decreasing our non-cash tax expense by the amount of the release, resulting in a corresponding increase in net income. When this occurs, it will be a positive non-cash event and will have no impact on non-GAAP financial metrics.

Before we move on to guidance, I'll highlight one non-cash item related to both the balance sheet and the P&L.

We continue to evaluate the necessity of our valuation allowance on certain existing tax. Deferred tax assets, each quarter in accordance with us, gaap,

while the valuation allowance is still necessary for Q2 in the latter, half of fiscal 2025, we may release all or a portion of our valuation allowance of 109 million which was discussed in our most recent 10K, as well as in our most recent 10 Q

When released, we estimate this would have the financial impact of decreasing our non-cash tax expense by the amount of the release, resulting in a corresponding increase in net income.

When this occurs, it will be a positive non-cash event, that will have no impact on non-gaap financial metrics.

Matt Steinfort: Moving on to guidance, for the third quarter of 2025, we expect revenue to be in the range of $226 million to $227 million, representing approximately 14.1% year-over-year growth at the midpoint. For the full year 2025, we are raising our annual revenue guidance to the range of $888 million to $892 million, representing approximately 14% year-over-year growth at the midpoint. Given our strong Q2 performance, visibility into our customers' usage trends, and the strength of the AI/ML demand environment, we are able to raise our full-year guide with confidence. For the third quarter of 2025, we expect our adjusted EBITDA margins to be in the range of 39% to 40%. For the full year, we raise our adjusted EBITDA margin guide to the range of 39% to 40%.

Moving on to guidance for the third quarter of 2025, we expect revenue to be in the range of $226 million to $227 million, representing approximately 14.1% year-over-year growth at the midpoint.

For the full year 2025, we are raising our annual revenue guidance to the range of $888 million to $892 million, representing approximately 14% year-over-year growth at the midpoint.

Given our strong Q2 performance visibility into our customers usage strength, and the strength of the AI ml demand environment, we are able to raise their full year guide with Compton.

for the third quarter of 2025, we expect our adjusted Eva margins to be in the range of 39 to 40%

Matt Steinfort: For the third quarter of 2025, we expect non-GAAP diluted earnings per share to be $0.45 to $0.50, based on approximately 102 million to 103 million in weighted average fully diluted shares outstanding. For the full year 2025, we expect non-GAAP diluted earnings per share to be $2.05 to $2.10, based on approximately 103 million to 104 million in weighted average fully diluted shares outstanding. Turning to adjusted free cash flow, we raise our guided adjusted free cash flow margins for the full year to 17% to 19%, increasing our projected cash flow margins. At the same time, we are accelerating our revenue growth outlook, which speaks to the confidence we have in our ability to maintain attractive free cash flow margins while we accelerate our top-line growth.

For the full year, we raise our adjusted, Eva margin Guide to the range of 39 to 40%.

For the third quarter of 2025, we expect non-gaap diluted earnings per share to be 45 to 50 cents based on approximately 102 to 103 million in weighted average fully diluted shares outstanding.

For the full year 2025.

We expect non-gaap diluted earnings per share to be $25 to do a 2.10 cents based on approximately 103 to 104 million in weighted average fully diluted shares outstanding.

To 17 to 19%.

Matt Steinfort: Consistent with our historical guidance practice, we are not providing adjusted free cash flow guidance on a quarter-by-quarter basis, given it is heavily influenced by working capital timing, as you saw in our year-to-date results. That concludes our prepared remarks, and we will now open the call to Q&A.

Increasing our projected cash flow margins. At the same time, we are accelerating our revenue growth outlook, which speaks to the confidence we have in our ability to maintain attractive free cash flow margins while we accelerate our topline growth.

Consistent with our historical guidance. Practice we are not providing adjusted free cash flow guidance on a quarter-by-quarter basis. Given it is heavily influenced by working capital timing as you saw in our year-to-date results.

Krista: Thank you. We will now begin the question and answer session. If you would like to ask a question, please press star one on your telephone keypad to raise your hand and join the queue. If you would like to withdraw your question, simply press star one again. We also ask that you limit yourself to one question in one follow-up. Your first question comes from Patrick Walraven with City Citizens. Please go ahead.

That concludes our prepared, remarks and will now open the call to Q&A.

Thank you. We will now begin the question and answer session. If you would like to ask a question, please press *1 on your telephone keypad to raise your hand and join the queue. If you would like to withdraw your question, simply press *1 again. We also ask that you limit yourself to one question and one follow-up. Your first question comes from Patrick Wall, Ravens with City Citizens. Please go ahead.

Speaker 5: Oh, great. Thank you very much, and congratulations. Paddy, could you talk a little bit more about the AI/ML revenue, the over 100% increase there, and maybe walk us through a little bit the history of this offering and why the current version is really starting to kick in?

Oh, great. Thank you very much, and congratulations. Um,

Patty, could you?

Um, talk a little bit more.

about, uh,

Padmanabhan Srinivasan: Thank you, Patrick. Good morning. Good way to get started. The AI/ML revenue, as I mentioned in the call, grew more than 100% year over year. If you remember, last Q2 was when we brought a lot of H100 NVIDIA gear online. More than doubling that this quarter was a significant step for us. What is different is, as I explained, we have a three-layer AI stack. On the foundational level is our Gradient AI Infrastructure stack, which is a network of GPUs, both from AMD as well as NVIDIA. In the middle layer is our Gradient AI Platform that we just took from private and public preview all the way to general availability. On the topmost layer is agents. The type of customers that use these three layers are slightly different at this point.

The AIML revenue and you know, the over 100% increase there and maybe walk us through a little bit, the um the history of this offering and and why the current version is um is really starting to kick in.

Yeah. Thank thank you. Patrick good morning.

Um, good way to get started. So the AIML, um, Revenue as I mentioned in the call, um, grew more than 100% year-over-year. So, uh, if you remember last Q2 is when we, um,

Padmanabhan Srinivasan: AI infrastructure is consumed typically by AI-native companies that have their own model or have taken an open-source model and are doing some tweaks to it and hosting those models and scaling them, especially in the inferencing mode, are typically consuming the AI infrastructure. A majority of our revenue comes from the Gradient AI Infrastructure stack. That's not very dissimilar from the rest of the industry. The Gradient AI Platform that we recently pushed out to GA is where any software application, like a SaaS provider, for example, can start consuming AI into their own applications without having to do the heavy lifting of building and managing their own GPU infrastructure. We have serverless endpoints for these LLMs, for example, and we have a bunch of other tools and modules that are critical building blocks for consuming AI into your own application.

We brought a lot of, um, h100 um, Nvidia gear online. So, uh, more than doubling that this quarter was uh, uh, significant step for us and what is, uh, different is, uh, as I explained, we have a 3 layer AI stack on the, um, foundational level is our gradient. AI infrastructure stack, which is, uh, a network of gpus, both from AMD, as well as Nvidia. And then uh, in the middle layer is our gradient AI platform that we just took from private uh, and public preview all the way to General availability. And then on the topmost layer is Agents. So, uh, the type of customers that use these 3 layers are slightly different at this point. So AI infrastructure is consumed typically by AI native companies that have their own model or have taken a open source model and and are doing

Some, um, um, tweaks to it and hosting those models, um, and scaling them, um, especially in the inferencing, uh, mode, uh, are typically consuming the AI infrastructure and a majority of our Revenue comes from the gradient. AI infrastructure stack. And uh, that's not

Padmanabhan Srinivasan: It becomes very, very easy to build AI into your existing application. That's what is powering the growth of our AI revenue is predominantly on the infrastructure side, but we are driving a lot of adoption and mindshare with developers with the AI platform. On the agentic layer, the first commercial application of that is the Cloudways Copilot that's typically adopted by end customers as a way to automate some of the manual tasks that they're seeing in managing and operating cloud-based applications.

Very, um, dissimilar from the the rest of the industry, the gradient AI platform that we recently pushed out to GA is where, um, any software application, like a SAS provider, for example, can start, uh, consuming AI into their own applications without having to do the heavy lifting of building and managing their own GPU infrastructure. So we have serverless endpoints for these llms, for example, and we have, uh, a bunch of other, um, tools and modules that are critical building blocks for consuming AI into your own application. So it becomes very, very easy to uh, to build AI into your uh, existing application and that's what is powering the growth. Uh, of our uh, AI revenue is predominantly on the infrastructure side, but we are driving a lot of adoption and mind share with developers with the AI platform. And on the agentic layer, the first commercial, uh, application of that is the cloudway scope.

Pilot that's typically uh adopted by end customers as a way to um automate some of the manual tasks that they're seeing in managing and operating Cloud cloud-based applications.

Speaker 5: That's very helpful. Thank you.

That's very helpful. Thank you.

Krista: Your next question comes from the line of Mike Sykos with Needham and Company. Please go ahead.

Your next question comes from the line of Mike secos with Neiman Company. Please go ahead.

Speaker 5: Hey, guys. Thanks for taking the questions here. Just to further the conversation on the AI/ML, good to see the north 100% revenue growth, but reflecting some of the more recent trends you guys have seen on the ARR front. We just wanted to see, I know historically you guys have given us more color on the underlying components for that net new ARR. I think the last quarter you guys had cited north of 160% year-on-year. Maybe I missed the data point, but just wanted to see how that net new is growing on the AI/ML front in the June quarter.

New is growing on the AIML front in the June quarter.

Matt Steinfort: Mike, I think what we said is that our ARR was growing. The AI ARR was growing north of 160% in prior quarters. That was not referring to the incremental ARR. It was the actual ARR. The north of 100 reflects still very strong growth. In fact, if you look at the incremental ARR for this quarter at 32, it was a good balance across both AI and core cloud. But it was our highest incremental ARR in the company's history. The reason that it dropped, if this is where you were going with the question around from 160 to north of 100, is just as Paddy Srinivasan had said, we lapped the Q2 when we launched all of our AI capabilities and we had a bunch of pent-up demand. So the Q2 growth in the AI business in particular from last year was high.

Matt Steinfort: So it was just a difficult time. But if you look at the incremental ARR that we are adding for the business on a go-forward basis, we are accelerating. It is an accelerating business.

Um, Mike Smith. Um, I think what we said is that our ARR was growing, they I ARR was growing, uh, north of 160% in Prior quarters that wasn't referring to. The incremental are at least the, the actual error. Um, and the, the north of a 100 reflect still, you know, very strong growth. In fact, if you look at the incremental ARR for this, um, this quarter at 32, you know, it was a good balance across both Ai and and um, and the core Cloud. Um, but it was our highest incremental are in the company's history and the reason that it dropped it, this is where you're you're going with the question around from 160 to North 100 is just as Patty. Had said we lapped the Q2 when we launched all of our, um, you know, our AI capabilities and we had a bunch of pent-up demands. So the Q2 growth, um, in the AI business in particular, uh, from last year was was high. So it was just a difficult time but if you look at the um, incremental are that, we're adding for the, you know, in that business on a go forward basis, we're accelerating its

it's an accelerating, because

Speaker 5: Got it. For the NDR, I know that the 99% here is in keeping with that commentary you guys have provided last quarter. Can you just explain what actually acted against that? Because I would have thought there would have been at least some benefit from you guys lapping that Cloudways price increase in April.

Got it and for the the ndr I know that the the 99% here is in keeping with that commentary. You guys have provided last quarter. Can you just explain uh what what actually acted against that because I would have thought there would have been at least some benefit from you guys laughing that cloudways price increase in April

Matt Steinfort: Yeah, I think that when we look at the NDR, and this is the reason that we signal that it will likely bounce around the kind of current range into this quarter and probably going for the next couple of quarters, is that in the market, we haven't seen a degradation in the market. We haven't really seen any change in the market since the April timeframe. But as we look at some of our larger customers in the long tail, I'd say there's a mixed impact on customers. It's very individual. So some customers we see that are maybe on edge and they're optimizing or they're a little bit hesitant to expand their business. But in the same industry or in the same size of customer, we also see a number of customers that are accelerating the business.

Matt Steinfort: They're doing really well and they're expanding their business with us and they're growing their workloads. And you see that in the growth of the customers, the Scalers Plus at 35%. But we're seeing really strong growth in parts of our customers, but we're also seeing others that are being cautious and aren't scaling as fast. So we think that we're likely to stay kind of in this level. I'd say what the good news is, despite the fact that the NDR was just a hair lower at 99%, we were able to raise our guidance. We're delivering the best incremental ARR that we've delivered in a very long time. So we're very encouraged by the trends. I think that NDR is still, it's such a laggy metric. It's going to be a little stubborn to improve, but that's not going to slow us down from a revenue growth standpoint.

Yeah, I think the, um, when we look at the um, at the ndr and and this is the reason that we we signal that a that'll likely Bounce Around the kind of current range, um, you know, into this quarter and probably going for the next couple quarters is, um, that, you know, with, with the, in the market. We haven't seen that degradation Market. We haven't really seen any change in the market since, um, you know, the April time frame. But as we, we look at our, some of our larger customers in the, in the long tail. Um, there's a I'd say, there's a mixed impact on customers. It's very individual. So, some customers we see that that are, um, uh, maybe on edge and they're, they're optimizing or they're a little bit hesitant to, um, to expand their business. But in the same industry, or in the same size of customer, we also see a number of customers that are accelerating the business. They're doing really well and they're expanding their business with us and they're growing their workloads. Um, and you see that in the growth of the, um, you know, the the, the customers, the scalars, Plus at 35%. So we're seeing really strong growth in, um, you know, in parts of our customers. But we're also seeing other

Is that that they're being cautious and and um and our uh, scaling is as um as fast. And so, you know, we we think that we're likely to to stay kind of in the level, I say what what the good news is, You know, despite the fact that the ndr um was just a hair lower at 99, we were able to raise our guidance. We're we're delivering the best incremental um ARR that we've delivered in in a very long time. And so we're very encouraged by the trends. I think that ndr is still

Matt Steinfort: We're doing enough with the new product acquisition on the core cloud, which is doing really, really well, getting really good cohorts and they're coming in. We've got the migration motion, which is a relatively new motion that doesn't always impact NDR. And then we've got the growth and acceleration in the AI business. So we're very bullish on the growth prospects, and that was what enabled us to raise the guidance for the year.

It's such a laggy metric. It's going to be a little stubborn to to improve but that's not going to slow us down from a a revenue growth standpoint. We're, we're doing enough with the new product acquisition and the core Cloud which is doing really, really well. Getting really good cohorts and they're coming in. We've got the migration motion, which is a relatively new motion. Um, that doesn't always impact, um, ndr and then we've got the, the growth and acceleration in the AI business. So we're we're very bullish on the, the growth prospects and and that was what enabled us to to raise the um the guidance for the year.

Speaker 5: Great. Thank you, guys.

Great. Thank you guys.

Krista: Your next question comes from the line of Gabriela Borges with Goldman Sachs. Please go ahead.

Speaker 7: Hey, good morning. Thank you. I wanted to touch on the unit economics of the AI business. Matt Steinfort, I know in the past you've talked about the three-year payback period, but we've both been very consistent in saying as you move from bare metal GPUs to more differentiated services, exactly as you've illustrated in the graphic in the slides, you should be able to command more gross margin, essentially. So maybe give us an update on how those efforts are tracking. How do you feel about the gross margin and the LTV to CAC of the AI business relative to the core business?

Your next question comes from the line of Gabriella Borges with Goldman Sachs. Please go ahead.

Hey, good morning, thank thank you. I wanted to touch on the unity economics of the AI business. Now, I know in the past you've talked about the 3 of payback periods, but we'll have both been very consistent and saying, As you move from bare metal gpus to more differentiated Services. Exactly, as you've Illustrated in the the graphic in the slides, you should be able to command more gross margin essentially. So maybe give us an update on how those efforts are tracking. How do you feel about the growth margin and the LTV to attack of the AI business relative to the Core Business?

Matt Steinfort: We are very encouraged and comfortable with the margins that we are getting in the AI business. As you said, Gabriela Borges, the higher layers of the stack, the three-layer stack that Paddy Srinivasan describes, have better margins than pure infrastructure. But even at the pure infrastructure level, we are very comfortable with the returns, particularly given the long-term value that we believe. You talked about the LTV. The long-term value that we believe we will generate from those customers is, as Paddy Srinivasan has talked about multiple times, inferencing customers, which is what we are seeing more and more of, even at the infrastructure layer as we are kind of going through this, they will pull other cloud services through. They need databases, they need storage, they need bandwidth, they need standard compute CPU.

Matt Steinfort: This is a bit of, we are still investing ahead in terms of if there is a bunch of infrastructure, the margins on that are lower than the margins at the higher stacks. But you need that baseline infrastructure capability to get the higher layer services. We think it is a very good investment, very good use of our capital, and we are very encouraged by the returns that we are getting and the promise of higher returns as that business matures and we get more pull-through revenue and we get more of the revenue shifting to the higher layers of the AI stack.

Even at the infrastructure layer as we're kind of, um, going through this, um, they will pull other uh, cloud services through it. They need databases. They need storage, they need bandwidth. Um, they need standard, uh, compute CPU. And so, you know, this this is a bit of, um, you know, we're still investing ahead, in terms of, I think if there's a bunch of infrastructure, the margins on that or the our, our, um, you know, lower than the margins at the higher Stacks. But you need that Baseline, um, infrastructure capability to get the higher layer services. And so we, we think it's a a very good investment. It's a very good use of our Capital, um, and

Padmanabhan Srinivasan: To add to it, Gabriela, this is Paddy. To add to what Matt just said, that is why we are also forward investing in making our Gradient AI Agentic Cloud very, very optimized for inferencing. I talked about our inference-optimized droplet. If you look at that right side of the slide eight, you will also see that we are investing in model optimization. We are investing in infrastructure optimization at the infrastructure level. Everything is aimed to scale inferencing workloads on our platform, which tend to have very long tails. As Matt mentioned, they also drag through some of the other cloud primitives. They drag the left side along with them as the inferencing workloads scale globally. We feel very good about where we are and some of the early success we are seeing with very marquee customers that are starting to scale up their inferencing footprint on us.

very encouraged by the, um, the returns that we're getting and and the promise of of higher returns as that business matures. And and then we get more pull through revenue and, and we get more of the, the revenue shifting to the higher layers of of the AI stack.

And just to add to it. Uh uh Gabrielle this is just just to add to what Matt just said. That's why we're also uh, forward investing in making our um a a gradient AI agent, a cloud very, very uh, optimized for inferencing. So I talked about our inference optimized droplet. Um, if you look at that, uh, right side of the, uh, slide 8, you will also see that we are investing in model optimization. We are investing in infrastructure optimization at the infrastructure. Level, everything is aimed to um, scale inferencing, workloads, on our platform, which tend to be, um,

Speaker 7: Yeah, that makes sense. Thank you. Paddy and Matt, the follow-up I have here just on these comments on highest incremental ARR, highest organic ARR in over three years in terms of the net new that you are adding. Can we think of this as the new high watermark? I am looking at what is being implied in guidance. Talk to us about your ability to consistently deliver growth off that metric and whether there is any unevenness, whether because of seasonality or company-specific factors like the timing of new AI capacity coming online that we should be aware of as we think about the core model.

Which tend to have very long tails. And as Matt mentioned, they also, uh, dragged through some of the other uh, Cloud Primitives. So they dragged the left side along with them as the inferencing workload scale globally. So, uh, we feel very good about, um, where we are and some of the early success we are seeing with, uh, very Marquee customers, uh, that are, um, starting to scale up their inferencing, footprint on us.

Yeah, that that makes sense. Thank you, and Patty and Matt for followup I have here just some of these comments on highest incremental are our highest organic are and over 3 years in terms of the net new that you're adding.

Can we think of this as the new high water, mark, I'm looking at what's being implied in guidance. Talk to us about your ability to consistently deliver growth off that metric. And whether there's any unevenness, whether because it's a seasonality or a company specific factors like the timing of new AI capacity coming online that we should be aware of as we think about the forward model.

Padmanabhan Srinivasan: I can just talk, Matt, and you can fill in. So we did not have anything unnatural this last quarter. We didn't bring a bunch of capacity online or there was no seasonality associated with it. I think we are just, as we mentioned in our prepared remarks, we are honing our product-led growth motion for our core cloud customers, and that is starting to really produce results. On one hand, our migration motion is bringing in a new type of customers that are typically digital native enterprise customers, and we are starting to grow them. On the AI side, we're just starting to see some scaled-up inferencing customers. So it's a combination of all of those. It's just not one big contract or one spike in capacity of GPUs or anything like that.

Yeah, I can talk Matt and and you can go ahead, um, fill in. So we did not have anything on natural. This last quarter. Like we didn't bring a bunch of, uh, capacity online or there was no seasonality associated with it. I think we are just as, uh, we mentioned in our prepared remarks, we are, um, honing our product-led growth motion for our core Cloud customers. And that is starting to really, uh, produce results on 1 hand, uh, or migration motion is bringing in a new

Type of customers, uh, that are typically digital native Enterprise customers and we are starting to grow them.

Padmanabhan Srinivasan: It's a very secular and durable type of momentum that we are seeing on the new customer acquisition side. Matt?

And on the AI side, we're just starting, um, to see some scaled up, uh, inferencing customers. So it's a combination of all of those. It's just not 1, uh, big contract or 1 spike in capacity of gpus or anything like that. It's a very secular um and durable type of um um momentum that we are seeing on the new customer acquisition side, Matt,

Matt Steinfort: I agree with all that, Paddy. I think that, again, the reminder on ARR is it's not based on a booking. It's not based on a sale. It's based on actual customer revenue and customer utilization. So I think that we hope that that's a steady predictor in going forward of the exit trajectory that we're on and a good indicator. It's certainly a critical metric for us. As Paddy said, we're encouraged by our ability to increase that. Certainly, it'll, like any metric, will vary quarter to quarter. I hope that it'll always be up and to the right, but we have enough motions going that we're very confident in our ability to improve that metric.

Speaker 7: Really nice paragraph. Thank you for the detail.

I I agree with all that Patty. I think that um, again, the reminder um, ARR is it's not based on a booking. It's not based on a sale. It's based on actual customer revenue and customer utilization. And so, you know, it's it's, um, I think that the, you know, we hope that that's a, a steady predictor and going forward of the exit trajectory, you know, that we're on and and a good indicator. So it's certainly a critical metric for us. And as Patty said, we're, we're encouraged by our ability to to increase that. Um, certainly, you know, it'll like any metric will will vary quarter to quarter. I know that it'll always be um, up until the right. But um, we have enough motions going that uh, that we're very confident in our ability to improve that metric.

Really nice progress. Thank you for the detail.

Krista: Your next question comes from the line of Raimo Lenschow with Barclays. Please go ahead.

Padmanabhan Srinivasan: Perfect. Thank you. Staying on that AI notion and inferencing, what is, if you think about, Paddy Srinivasan, you talked about your, you know, how you try to differentiate there, et cetera. Where is the industry at the moment in terms of also capacity constraints? Is that still a factor for you that it is helping, or is it really now about all differentiation? Thank you. Then I have one follow-up from that. Thank you, Raymo. Capacity constraints are a way of life in AI as we are scaling like everyone else. We are trying to stay ahead of it a little bit, but there are just so many factors there in terms of the real estate footprint and the power and the cooling and the actual gear. There is just a lot of variable factors here.

Your next question comes from the line of Remo. Lenschow with Barkley's, please go ahead.

Perfect, thank you. Um,

Staying on that AI notion and and inferencing. Like, what is if you think about like the, how do you talk about like your, you know, how you try to different differentiate your Etc?

Where the industry at the moment in terms of also capacity constraints like is that still a factor for you that it's helping or is it really now about all differentiation? Thank you. And then I have 1 follow-up from that

Padmanabhan Srinivasan: I think for us, it all boils down to why some of these marquee AI-native customers are starting to choose us over the other alternatives that they have. It is really the twin stack cloud that we have laid out in slide eight. I do not think there are too many cloud providers that can claim to have both sides of that equation. We certainly feel like we are driving home that point in terms of not only offering a world-class AI infrastructure, but increasingly those same customers are also starting to leverage some of the guardrails and the agent evaluation framework and the agent observability and things like that, going up stack on the right side of the agentic cloud. As Matt Steinfort mentioned, they also have very sophisticated storage, data processing, and CPU compute requirements as well.

Like everyone else. Um, so we are, uh, trying to stay ahead of it a little bit, but it's uh, there's just so many, uh, factors there in terms of, um, the the real estate footprint and the power and the cooling and, uh, the actual gear. Um, so there's just a lot of, uh, variable factors here. Uh, but, but I think, uh, for us, it it all boils down to why. Um, some of these Marquee AI. Native customers are starting to choose us over, um, the other Alternatives that they have and it is really the, um, uh, the twin stack, um, Cloud that we have laid out in slide 8. So, um, I don't think there are too many Cloud providers, um, that can claim to have both sides of uh, of that equation and we certainly feel like we we are driving home that point. Um, in terms of not

Padmanabhan Srinivasan: At the end of the day, these are very sophisticated applications that require the might of a full-stack general-purpose cloud. I think that is the differentiator that we are leaning on. We feel really confident. I have been talking about this for about four quarters. Finally, we have the twin stacks that we have described on slide eight of the earnings deck. We feel really good. We are just getting started. Some of the RPO and the large contracts that we have been talking about, they have not even started hitting their full stride as we are scaling those customers. We feel really good about the forward momentum that we are building. That kind of leads into my next question for Matt Steinfort.

Not only offering uh a world class AI infrastructure, but increasingly those same customers are also starting to leverage some of the, the guard rails and the agent evaluation framework, and the agent observability and things like that. Going up, stack on the right side on of the agentic cloud. But also, as Matt mentioned, uh, they also have very sophisticated storage data processing, um, and uh CPU compute, uh requirements as well because

The end of the day. These are very sophisticated uh applications that require the the might of a full stack general purpose Cloud. So I think that is the differentiation differentiator that we are leaning on and we feel really confident. I've been talking about this for about 4 quarters and finally we have the the the twin Stacks that we have described on slide 8 of the earnings stack and we feel really good. We're just getting started. And some of the um, the RPO and the large contracts that we have been talking about. They have not even started hitting their full stride as we are scaling those customers. So uh, we feel really good about uh, the forward momentum that we are building.

Padmanabhan Srinivasan: If I think about the second half, I got a good few questions already of people saying, well, actually you are kind of raising probably raising a little in the full year by more than you are actually beating Q1, Q2. There is kind of obviously a lot of confidence in the second half. Should we think about like more RPO gives you more visibility, which kind of drives some of that guidance because we know you as a conservative person normally? Thank you.

and and that kind of leads into my next question or from Matt like if you if I think about

Second half. I

A few questions already. If people think, well, actually you kind of raising probably raising a little, the full you buy more than you actually beating q1 Q2. So that's kind of obviously, a lot of kind of confidence in the second half. Should we think about like more RPO gives you more visibility which kind of drives kind of some of that guidance. Um because we know you as a conservative person normally. Thank you.

Matt Steinfort: Thanks, Raymo. I wish that it was all the RPO that was giving us full confidence. If you look at the RPO, we are really encouraged by the increase. It is still a very, very small portion of our business. That is certainly encouraging. I would say when we look at the performance that we had in the first half, we look at the visibility that we have into the customer usage patterns. We look at the migrations that we are seeing and that motion kind of coming. We look at the traction we are getting with AI and with some of the through some of the direct sales and partnerships and some of the conversations that Paddy Srinivasan articulated we are having with large AI-native companies. We just, we have enough irons in the fire that we are confident in increasing the revenue guide.

Matt Steinfort: What to me is most encouraging, because you do know I am a relatively conservative guy, is that we are able to increase our free cash flow margin at the same time. To me, that we can demonstrate that we can grow revenue, we can accelerate revenue while maintaining attractive free cash flow margins. To me, that is incredibly encouraging as we think about what is in front of us in the second half and how that sets us up for 2026.

Thanks very much. Um, but I, I wish that it was all the RPO that was giving us, uh, full confidence. If you look at the, the RPO, um, while we're really encouraged by the the increase. It's still a very, very small portion of our business. Um, so that, that, that certainly emerging, but I'd say, you know, when we look at the performance that we had in the first in the first half, we look at the um, visibility that we have into the customer usage. Patterns, we look at the migrations that um, that we're seeing in that motion kind of coming. We look at the faction we're getting with um with AI and with with some of the through some of the direct sales and Partnerships and and some of the conversations that P articulated we're having with with large AI native companies. We we just we we have enough irons in the fire um that we're confident and increasing uh the revenue guide and and what to me is is most encouraging I think as you do you know I am a relatively conservative guy is that we're able to increase our free cash flow margin at the same time. And so to me that that you know, we

Padmanabhan Srinivasan: Okay, perfect. Thank you. Congrats.

Can demonstrate that we can grow Revenue. We can accelerate Revenue while maintaining attractive free cash flow margins. And, and to me, that's incredibly, um, encouraging as we think about the, um, what's in front of us in the second half and how that sets us up for 2026,

Yeah. Okay, perfect. Thank you. Congrats

Krista: Your next question comes from the line of Jason Ader with William Blair. Please go ahead.

Matt Steinfort: Yeah. Thank you. Good morning, guys. I just wanted to see if you could give us a little bit of a breakdown of the business right now when we think about the kind of AI side versus the non-AI side. I know you've given the growth rates. Can you tell us, you know, just sort of ballpark, is this like, I do not know, I am kind of, I am in the neighborhood of like 5% to 10% of revenue now from AI. I do not know if there is any specificity you can give on that, but that would be really helpful. Yeah. Jason, we are not, you know, we do not break this out. Part of it is because of the, you know, we believe that a lot of the AI capabilities are going to be pulling through other other capabilities.

You are next question. Comes from the line of Jason adder with William Blair. Please go ahead.

Yeah, thank you. Good morning, guys. Um

I just wanted to see if you could give us a little bit of a breakdown of the business right now, when we think about the kind of AI side versus the non AI side, I know you've given the growth rates

um, can you tell us, you know, just sort of ballpark is this like

I don't know. I'm kind of I'm in the neighborhood of like 5 to 10% of Revenue. Now from from AI, I don't know if there's any specificity you can give on that, but that would be really helpful.

Matt Steinfort: The impact of the growth is beyond what is represented if you just kind of wrote down the SKUs that we consider AI. But you are in the ballpark. I would say it is increasingly becoming a material chunk of the business. It is still small because it is a business that we just launched a year ago, and we are accelerating. But that is a reasonable ballpark for a percentage of revenue. We expect that to increase. It will become an increasingly meaningful portion of our business in 2026, but it will still be a small portion. The core cloud is still a very healthy and growing portion of our business.

Matt Steinfort: The AI business is a great complement to that and is accelerating our growth and also opening up different kind of entire channels and new customers to bring in that will drive that core cloud growth up as well. Okay. Great. Just as a quick follow-up, is it fair to assume that the core cloud business grew at a similar rate in Q2 versus Q1? That kind of low double digits. Is that accurate? Yeah. We still see momentum in the core cloud business. While the NDR was a little bit lower in Q2 than it was in Q1, the revenue that we are getting from new customers is ahead of our plan and our expectations. We are doing a really good job there.

But you're in the ballpark, I'd say it's um, it's increasingly um uh becoming a material, you know, chunk of the business. It's still small because it's a, it's a um, it's a uh, um, a business that we just launched a year ago and and we're accelerating. But but that's a reasonable, uh, ballpark for percentage of Revenue. And we expect that to to increase. And and you know um you know, it it uh it will become an increasingly meaningful portion of our business in 2026, but it'll still be a small portion. Uh, the core cloud is still very healthy and growing portion of our business and, and the AI business is a great complement to that. And, and, um, is accelerating our growth and, and, um, also opening up different, uh, kind of entire channels and, and new customers to bring in. They kill will drive the core Cloud growth up as well.

Okay, great. And then just as a quick follow-up to, um, is it fair to assume that the core core Cloud business was, um, grew at a similar rate in Q2 versus q1, uh, and that kind of, you know, low double digits. Is that is that accurate?

Matt Steinfort: Again, you got to remember NDR is a little wonky, laggy metric because what happened, like the change in revenue from a year ago has as much impact as the change in revenue this year. So the core cloud business continues to accelerate. It is in that low double-digit growth rate and is improving. So most of the upside then was from new customers, it sounds like. Yeah, correct. Yeah, because I mean, with NDR coming down a little bit, the new customer acquisition plus the growth in AI offset the slight headwind from the NDR. Again, if you look at the incremental ARR, so if you look at it on an exit run rate standpoint, there was a very good balance between the core business and AI.

Yeah, we we still see momentum in the um, in the core Cloud business and the well, the ndr was a little bit lower, um, in Q2 than it was in q1. The revenue that we're getting from, um, from new customers is um, is is ahead of our plan and our expectations. We're we're doing a really good job there and again, you got to remember ndr is is a little wonky laggy metric because what happened like the change in in

Revenue from a year ago has as much impact as a change in Revenue this year. So the, the core Cloud business is it continues to to, um, to accelerate. It's it's in that low double digit growth rate and is improving.

so that most of the upside, then was from new customers, it sounds like

Matt Steinfort: You both saw AI at its highest point, but there was still very good core cloud growth on an incremental ARR as well.

Padmanabhan Srinivasan: Okay. Awesome. Thanks, guys.

Yeah, correct. Yeah, because I mean with with NBR coming down a little bit that, you know, the um, the new customer acquisition plus the, um, the growth in AI offset the slight, um, you know, uh, had 1 from the the ndr. But again, if you look at the incremental are, so if you look at it on an exit run rate standpoint, um, it was a very good balance between the core business and Ai. And so you both saw Ai and its highest point. Um, but there was still, you know, very very good and, um, core cloud, cloud cloud growth on an incremental error, as well.

Okay, awesome. Thanks guys.

Krista: Your next question comes from the line of Josh Baer with Morgan Stanley. Please go ahead.

Your next question comes from the line of Josh bear with Morgan Stanley. Please go ahead.

Matt Steinfort: Great. Thanks for the question. I just wanted to confirm that in the net dollar retention rate, AI and ML revenue is not in that metric. Is that right? That is right, Josh Baer. That is still the case and will likely be the case for a while. As we have talked about it internally and we have talked about investor data, we said it will eventually contribute to the NDR, and we still believe it will. It will likely be for more inferencing workloads where they are steady production workloads. They are not projects where someone comes in, tests something for a month, and then kind of scales it back. If you think about the time lag of someone being in NDR, the customer does not count even in our core cloud until their 13th month.

Great. Thanks for the question. Uh just wanted to confirm that in the net dollar retention rate Ai and and ml revenue is not in that metric. Is that right?

Matt Steinfort: If you are turning up inferencing workloads now with marquee customers, it will be a year before they have even hit NDR. It will be, we will incorporate at least the inferencing portion of AI at some point, but it is certainly not going to be in the next couple of quarters. It continues to not include, NDR continues to not include AI.

Speaker 5: Okay, got it. I would think, especially now as it is scaling, you have more than 12 months. You talked about 100% growth off of the Q2 last year where there was AI revenue, and it is all organic, kind of missing piece to that NDR percentage just around that expansion from existing customers. I did want to ask you about the large deals, how we should be expecting the potential for large deals in the future. Also for you, Matt Steinfort, how you are thinking about it from a guidance perspective, assuming that would be a little bit lumpier or have longer sales cycles or it is just a new motion for you guys. How do you incorporate the potential for large deals in guidance? Thank you.

Yes, right? Josh, that's still that. That is still the case and will likely be the case. Um, you know, for a while as we talked about it internally and we've talked about investor day we said it'll eventually uh you know contribute to the to the MDR and um and we still believe it will the the um it'll likely be for more inferencing workloads where they're, you know, steady production workloads. They're not projects where someone comes in tests, something for a month and then you kind of scales it back and so if you think about the time lag of someone being in ndr, they don't the customer doesn't count even, you know, in our core Cloud until they're 13th month. And so if you're turning up inferencing workloads, now with um, you know, with with Marquee customers, it'll be a year before they, you know, they would even hit ndr. So it'll be, you know, we we'll incorporate the, um, at least the, uh, the infringing portion of AI at some point. But it's it's certainly not going to be in the next couple quarters. So it continues to not include ndr continues to not include a

okay, got it. Yeah, I would I would think like especially now as it's it's scaling but also you have more than 12 months. You talked about 100% growth off of the Q2 last year where there was AI Revenue. Um, and it's all organic. Um,

You know, kind of missing piece to that ndr percentage just around uh that expansion from existing customers. Um, I did want to ask you about the large deals. Um like how we should be expecting the potential for large deals in the future and then also for you Matt um how you're thinking about it from a guidance perspective? Assuming that would be a little bit lumpier or have longer sales Cycles or it's just a new motion for you guys. You know how do you incorporate the potential for large deals and guidance? Thank you.

Matt Steinfort: Guys, do you want to start and talk about the nature of large deals, and I can talk, I can answer Josh's question about the guidance?

Padmanabhan Srinivasan: Yeah. The nature of large deals is a very new muscle for us, both from a sales, business development, forecasting, all of the above. I think what we are driven by is, can we make these customers successful, and do we have enough of a technology edge that can attract and retain and get these customers to scale? That is the number one thing that I am focused on, that Broughton and Larry are focused on, is making sure that we have the ability to articulate our technology differentiation in a durable fashion and have the right engineering expertise on the ground to make these customers successful. I feel fairly encouraged by the couple of early successes that we have had, and hopefully we can, and we see enough in the pipeline to be quite encouraged with these kinds of deals.

And do we have enough of a technology Edge that can attract and retain and and get these customers to scale. And that's the number 1 thing that I'm focused on that.

Padmanabhan Srinivasan: With inferencing, it just takes time to go from binning a customer deal to actually scaling that up with real-world traffic. We are in the process of doing that with some of our customers. Extrapolating that into the future, we will see how we can do a more predictable job in terms of forecasting how these things fall. I expect this to be lumpy and spiky in the beginning before it starts normalizing because our customers are also new to this, and they get sudden spikes based on some new updates to their models or new updates to their software. Some of them are in the consumer AI space. Some of them are in the B2B AI space. We are learning along with them, and they are learning with us in terms of their business model and how it is scaling out.

Brought in and Larry are focused on is making sure that we have, uh, the ability to articulate our technology differentiation in the durable fashion and have the, uh, the right, uh, engineering expertise on the ground to make these customers successful. So I feel, um, fairly encouraged by, uh, the couple of early successes that we have had and hopefully we can uh, and we see enough in the pipeline to be quite encouraged uh, with these kinds of, uh, deals now. Um, with with inferencing, it just takes time, um, to to go from. Um, winning a customer deal to actually uh, scaling that up with real world traffic. So we are in the process of doing that with um uh with some of our customers and um, extrapolating that into the future. Uh we'll um, we'll see how we can um do uh uh more uh predictable job in terms of forecasting, how these things fall?

Padmanabhan Srinivasan: I will let Matt answer how we will start reflecting these things in our financials.

All. But I expect this to be lumpy and spiky in the beginning before. It starts normalizing because, um, our customers are also new to this and they get sudden spikes based on some new updates to their models or new updates to their uh, software. Some of them are in the consumer AI space. Some of them are in the B2B AI space, so we're learning along with them and they're learning with us, in terms of, um, their uh, business, uh, model and how, uh, it is scaling out. So I let Matt answer, how we will start reflecting these things in our financials.

Matt Steinfort: With that context, Josh, as you would expect based on our track record and our history, we'll be conservative in forecasting those. The good news is, as Paddy said, we book revenue, and when we get that revenue, it's not like we're signing massive deals that just turn on right away. So we have visibility into the ramps and how those customers are going. But given it's such a new motion and given some of those kind of the newness of it for both us and the customers, Paddy described, we'll be conservative in terms of including any projected revenue from large deals until we're very comfortable that things are on the right track and we're growing and we have good visibility to that growth. I would expect that you would continue to see us be conservative as it relates to any large deals reflected in our forecast.

With with that context, Josh that you as you, you would expect based on our, our, our track record and our history, we'll be conservative in in forecasting. Those. I mean, the good news is, is Patty said, um, yeah. We we, uh, we booked Revenue when when we get that Revenue, it's not like we're signing, you know, a massive deals that that, um, that just turn on, um, right away. So we have visibility into the ramps and how those those customers are going. Um, but but given it's such a new motion and, and given some of those, um, kind of, uh, the newness of it for both us and the customers probably described. We'll be conservative in terms of, um, of including any, any projected revenue from from large deals until we're, we're very comfortable that, um, you know, the things are on the right track and, and we're growing and, and we have good visibility to that growth. So, I, I would expect that, um,

Padmanabhan Srinivasan: Great. Thank you.

Uh, that you would continue to see us be conservative as it. Reflects it relates to any large deals reflected in our forecast.

Great. Thank you.

Krista: Your next question comes from the line of James Fish with Piper Sandler. Please go ahead.

You are our next question.

Matt Steinfort: Hey, guys. You know, you keep using the word conservative here, but on the guide side, we haven't seen this level of second half step up in some time, really going back to the pandemic. You guys deserve credit here doing $32 million of net new ARR organic. Can you just walk us through the linearity you are seeing, what you're expecting from some of the newer solutions in the second half to raise guide by this much? And any of the other moving parts, it helps you bridge this kind of larger than normal step up here because if I look at this and say you book similar kind of to slightly better net new ARR in the sort of $30 million to $35 million range over the next two quarters, it really doesn't leave much wiggle room based on how you guys are defining ARR versus revenue now.

Comes from the line of James fish, with Piper Sandler. Please go ahead.

Hey guys, um, you know, you keep using the word conservative here. But on on the guide side, we haven't seen this level of second half Step Up in some time, really going back to the pandemic. And, and you guys deserve credit here doing 32 million of net new error, current organic, but can you just walk us through the linearity? You are seeing what you're expecting from some of the newer Solutions in the second half to to raise guide by this much and any of the other moving Parts it helps you bridge, the this kind of larger than normal step up here because if, if I look at this and and say, you booked similar, kind of just slightly better admit, new error in the sort of 30 35 million uh range over the next few quarters. It really doesn't leave much wiggle room based on on how you guys are are defining ARR versus Revenue now.

Matt Steinfort: I think, Jim, it's a good question. Recall in the last quarter, we didn't raise guidance. We beat Q1. We didn't raise guidance at Q2. We did that intentionally because the market had changed pretty dramatically, and we just didn't know what was going to happen from a macro standpoint. We've now got a full quarter under our belt on that front. We feel good about the visibility we have with the core customers. We've got a bit of the beat from the first quarter and the beat in the second quarter to pass through. As I said, we have enough levers at the moment that we're confident in. We've got the revenue from new customers, the month 1 to month 12 that's doing very well. That's a relatively stable and predictable. It's a, you know, we're seeing increased volume. We're seeing increased conversion.

I think um it's a good good question to um recall in the last uh quarter. We didn't raise guidance, but we we beat the q1. We didn't raise the guys to keep you do and we did that. Um

Intentionally because the market, you know, has had changed pretty pretty dramatically. Um and we just didn't didn't know what was going to happen from a macro standpoint. We've now got a, a full quarter under our belt on that front. We feel good about the visibility. We have with the the core customers. We've got a bit of the Beat from the first quarter and the beat and the second quarter.

Matt Steinfort: We're seeing better customers in that cohort. That's a fairly durable kind of improvements that we've made. So we're really confident in that. We've got the migration motion that we turned up that, as Paddy Srinivasan talked about, 70-something migrations during the quarter. That's a very new motion for us, but we've got clearly a pipeline of those because those aren't things that you just, like somebody comes in one day and you turn on a migration. You have to be talking to a customer for a period of time. So we're managing a pipeline. That.

Krista: We also have very good visibility into our AI pipeline and are getting increasing traction there. We have got enough things that are going that give us confidence to be able to deliver on that. As I said in the prior question or the answer, we haven't fully reflected the large deal potential in the guide that we have. That certainly gives us the upside potential beyond what we are even talking about. We feel good that we are confident in the base, confident enough to raise the guide and that there are still other things we can be doing and progress we could be making over the balance of this year to give us further room.

You're talking to the customer for a period of time. So we're managing a pipeline around that. Um, we also have very good visibility into our AI Pipeline and um, are getting increasing traction there. So we we've got enough things that are going that, um, that give us confidence to, um, to be able to deliver on that. And and as I said in, um, you know, in the prior uh, question or the answer, um we haven't fully reflected the large deal potential in the um in the guide that we have. And and that certainly gives us, you know, the upside potential um beyond what we've we've been uh you know we're talking about. So we feel good that we're confident in the base, confident enough to raise the the guide and that that there's still, you know, other things we can be doing and and and progress we could be making over the balance of this year. Um, to to give us further room.

Melanie Strate: Got it. Then, Paddy Srinivasan, maybe for you, can you talk about what you are seeing on sort of the GPU pricing dynamic? Is it seeming like across the space, pricing came down a little bit and how you are thinking about the ability to repurpose any GPU Droplets that kind of migrate from customer to customer or what you are seeing in terms of utilization at this point across the GPU side? Thanks, guys.

Padmanabhan Srinivasan: Okay. Thank you, Jim. The utilization is very robust. We are running very lean on our GPU fleets, regardless of the generation of GPUs we are talking about. As we become more and more heavy on the inferencing side, it gives us a lot of degrees of freedom in terms of how we allocate the machines. Typically, what we are seeing with our inferencing customers is, yes, they do care about the generation of GPUs, but they care more about the price performance rather than just the raw throughput of any given generation of technology. Let's say you have 100 units of GPU on the current generation. If we can deliver the same price performance with 90 units of GPU in the next generation, the customer really doesn't care as long as it's in the same family of GPUs and they don't have to re-engineer or do anything.

Then um, Addie maybe for you can you talk about what you're seeing on on sort of the GPU uh pricing dynamic as as it seemed like across the space pricing, came down a little bit and how you're thinking about um, you know, the ability to repurpose any gpus that kind of migrated from customer to customer or you know what you're seeing in terms of utilization at this point. The the GPU side. Thanks guys.

Okay, thank you. Jim U the uh the utilization is very robust. We are running uh very lean on uh on our GPU fleets uh regardless of the generation of uh gpus. We were talking about um as uh we become more and more heavy on the inferencing side it gives us a lot of degrees of freedom in terms of how we allocate the machines and typically what we're seeing with our inferencing customers is yes, they do care about the generation of gpus but they care more about the price performance rather than just the, the raw throughput, uh, of Any Given generation of technology. So, um, let's say you have a, um, uh, you have, uh, 100 units of GPU on, um, the current generation. And if we can deliver the same, uh, price performance with, uh, 90 units of GPU in the Next Generation, the customer.

Padmanabhan Srinivasan: We are getting to a point where it's more about the price performance rather than the price alone or the performance alone. That gives us a lot of degrees of freedom in terms of how we allocate which family of GPUs across our inference workload customers. I think this is going to get even more important as we start scaling up many of our customers across geographies and start doing this in multiple data centers. A lot of new things to be figured out there, but the pricing dynamics and training workloads are quite a bit different from the ones that we are experiencing in a stack that is predominantly driving inferencing.

Really doesn't care as long as it's in the same family of uh of gpus. And they don't have to re-engineer or do anything. Um so they so we are getting to a point where it's more about the price performance rather than the price alone or the performance alone. So that gives us a lot of degrees of freedom. In terms of how we allocate, uh, which family of gpus across our inference workload, customers. And I think this is going to get, um, even more important as we start scaling up,

Um, many of our customers across geographies and, uh, and start, uh, doing this, uh, in multiple data centers. So, um, a lot of, uh, a lot of new things to be figured out there, but, um, um, the, the pricing Dynamics and training workloads are quite a bit different from the ones that we are experiencing in a stack that is predominantly driving inferencing.

Matt Steinfort: We have time for one more question, and that question comes from the line of Brad Rybak with Stifel. Please go ahead.

Speaker 5: Great. Thanks very much. Matt, as we think about gross margin for the back half of the year as the revenue mix maybe shifts a little bit and you continue to invest in the CapEx, how should we think about the trajectory? Then heading into next year as you lap the change in useful life, what type of impact should we expect then? Thanks.

We have time for 1, more question and that question comes from the line of bread Reebok with stifel please. Go ahead.

Great. Thanks very much Matt as we think about gross margin for the back half of the year as the revenue mix, maybe shifts a little bit and you continue to invest in the capex. How should we think about the trajectory and then heading into next year's you lap the uh the change in useful life. What type of impact? Should we expect that? Thanks.

Krista: Thanks, Brad. The gross margins are, we expect to be relatively consistent, the current levels over the balance of this year. Again, as you said, the AI business is growing fast, but it is still a small part of the business. So it is not going to have a material impact on gross margins. If you roll that out to next year, clearly we are not at a point ready to give guidance, but we would expect it to have a modest headwind to gross margins, but it is still going to be in the vast majority of our business. It is going to be at the same high margins that we have. We continue to drive efficiencies in the core business, bandwidth optimization, the longer-term data center optimization strategy that we have.

Um, but the gross margins are uh, we expect to be relatively uh, consistent. The current levels over the balance of this year. With again, as you said this, the AI business is um, it's growing fast but it's still a small part of the business. So it's not it's not going to have a material impact on, on Gross margins. Um, if you, if you roll that out to next year, clearly we're not at a point ready to give guidance but we would expect it to have, um, you know, kind of a modest, uh, headwind to address margins. But it's, you know, it, it's still going to be in the

Krista: We are confident that we can maintain healthy gross margins in the realm that we have right now. If AI becomes a much, much bigger portion of our business, you will clearly have visibility into that as we do. At that point, you would see a little bit of margin pressure. At this point, the gross margin we expect to stay right around where it is through the balance of the year.

Speaker 5: That's great. Thanks very much.

Vast majority of our business is going to be at the the same high margins that we have. And we continue to drive efficiencies in, um, in the core business, um, bandwidth optimization. You know, the the um, the longer term data center optimization, uh, strategy that we have. And so we're we're confident that we can maintain kind of healthy gross margins in the um, in the in the realm that we have right now. And if if AI becomes a um, a much much bigger portion of our business you'll clearly have visibility into that at, you know, as we do and at that point you would um you would see a little bit of margin pressure. But at this point the um, the gross margin. We expect to stay right around where it is, 200 the year.

Matt Steinfort: Your next question comes from the line of Mark Zhang with Citi. Please go ahead.

your next question comes from the line is

From the line of Mark Zhang with City, please go ahead.

Matt Steinfort: Hey, great. Good morning, guys. It's great to be here. Maybe just want to dig a little bit more into the RPO performance. Very nice to see. Can you give a sense of your characteristics here? What are the average deal prices, contract durations? I just wanted to confirm that AI was the leading contributor here, or you saw good contributions from CoreCloud as well. Thanks.

Hey great. Um, good morning guys for squeezing the end, maybe just want to dig a little bit more into the brpo performance. Very nice to see on something. Maybe the deer characteristics here. Um, what are the average deal? Slices, contract durations, I just want to confirm that AI was the leading contributor here or you saw you know, good contribution from C Cloud as well. Thanks,

Speaker 5: It was shortly. Go ahead, Matt.

Krista: I was saying from the start in the reverse. So it was the increase in RPO was from both CoreCloud and AI. It wasn't just AI. Clearly, there are some AI deals that are in there. You can see that I think the average duration, and I might be quoting Q1, so I apologize if it's slightly off, but it's like 19 months. So you can get the average kind of length of the deal. The two, say, call it two years on the outside, and sometimes one year, somewhere between one and two years is the typical for us because this is a relatively new motion for us. It's great that we're getting customers that are used to and value the ability to just do straight consumption with us to make the commitments for a minimum level of revenue over some period of time.

But surely go. Go ahead, man.

Krista: That's something that's very encouraging and speaks to the product innovation and the improvements we've made in the CoreCloud and customers' confidence in our ability to continue to meet their needs. Paddy, if you wanted to add something to that.

Say, from the start of the reverse, so it was the increase in RPO was from both core cloud and AI. So, it wasn't wasn't just, um, uh wasn't just AI clearly there's some AI deals, um, that that are in there. Um, the, um, the and you can see that I think the, the average, um, duration, and I might be quoting q1, so I apologize if it's slightly off, but it's like 19 months. Um, so you can get the average, um, kind of length of the, the, the deal, you know, the 2 2. They call it 2 years on the outside and sometimes when you 1 year, somewhere between 1 and 2 years is, um, is the the typical for us because this is a relatively new motion, um uh for us and it's great that we're getting customers that are used to and value the, the ability to just do Straight consumption with us to make the commitments to um, you know, for a minimum level of, of Revenue, over some period of time. So that's that's something that's very encouraging.

Padmanabhan Srinivasan: You nailed it, Matt. It is definitely a combination of both our CoreCloud as well as AI. This is not just reflective of just one giant huge deal or anything like that.

Um, and then speaks to the product Innovation and the improvements we made in the core cloud, and, and customers confidence in our ability, to continue to, to meet their needs and our Patty, if you wanted to add something to that.

No I think uh you you nailed it Matt. Um yeah. It is definitely a combination of both both our core Cloud as well as AI. So there's not, this is not just reflective of just 1, giant huge deal or anything like that.

Matt Steinfort: Got it. Thank you. Just maybe a quick follow-up on capital allocation. It seems like you guys have been stepping up on share repurchases since, I guess, end of last year. Now the authorization is dwindling down to about 3 million. What is the thought process around capital allocation going forward? Thanks.

Krista: Yeah. Our capital allocation, so we actually reduced the amount of repurchases that we have been doing over the last two years. We did almost $500 million in 2023. Across 2024 and into 2025, it was only $140 million. Our primary objective at the moment, and we articulated this in Investor Day, is all about organic growth and investing to drive organic growth. Secondly, and as important, we are committed to making sure that we have taken care of the balance sheet and we have addressed the outstanding convert. We have said that we are going to do that by the end of this year. We started that process with our $800 million bank facility, $500 million of that as a term loan. We are dialing back the share repurchases just so that we can make sure that we take care of those first two objectives.

Got it. Thank you and then just maybe a quick follow up um just on Capital allocation um seems like you guys have been stepping up on share repurchases since uh I guess end of last year but now we're working. You know the authorization is going down to about 3 million what sort of the stock process around just you know Capital allocation go forward. Thanks.

Yeah. Our, um, our Capital allocation. So we actually reduced the amount of repurchases that we've been doing over the last 2 years. We, we did almost 500 million in in 2023. And then across 2024 and into 2025 it, it was only 140 million. Um, our primary objective at the moment and, and we articulated this in, in investor day is, um, it's all about, um, it's all about the organic growth and and investing to drive organic growth growth. But then, secondly and and, um, you know, as important is, we're committed to, um, to making sure that we've taken care of the balance sheet and we've addressed the outstanding uh convert and we we've said that we're going to do that by the end of this year. And we started that process with our um, 800 Million Dollar Bank facility.

Krista: As soon as we take care of those two objectives, the first one will be ongoing, but the second being taking care of the outstanding convert, then we will go back to, I would say, a reasonable level of share repurchases that are targeted at offsetting dilution. I think priority one is organic growth. Priority two is take care of the convert. Priority three is use the repurchases to offset dilution. Right now, priorities one and two are the bigger focus for the next quarter or so.

You know, 500 million of that. Is a Term Loan. Um, and so we're we're dialing back the, um, the share repurchases just so that we can make sure that we take care of those first 2, um, objectives. And as soon as we take care of those 2 objectives, the first 1 will be ongoing, but the, the second being taken care of the, um, of the outstanding convert. Then we'll, you know, we'll, we'll go back to a, let's say a reasonable level of share repurchases, um, that are targeted at offsetting solution, you know. So it's, I think, you know, I already wanted is organic growth priority, 2 is take care of the, the, the convert and Party 3 is, is use, um, the, um, the repurchases to offset dilution and right now, priorities 1 and 2, or or the bigger Focus for the, for the next quarter. So,

Matt Steinfort: Your next question comes from the line of Tom Blakey with Cantor. Please go ahead.

Your next question comes from the line of Thomas Blakey with caner. Please go ahead.

Speaker 7: Hey, guys. Congratulations on the results, and thanks for squeezing me in here. I had a point of clarification first. I think it was Jason Ader's question earlier. Did Matt, did you say that the CoreCloud accelerated in Q2? From a question perspective, I know the Core AI is organic now, growing over 100%. What kind of derivative impact did that have to NDR, if any, Paddy or Matt? You would think there would be some kind of flow-through of these customers buying more services on the platform. I would just be curious to see what kind of impact that had on that metric. Thank you.

Hey guys, uh

Congratulations on the results and thanks for squeezing. The, in here I I had a point of clarification first to I think it was Jason aer's question earlier did, Matt, did you say that the core Cloud accelerated in 2q. Um, and then, uh, from a, from a question perspective

You know, I know, um, the core, you know, uh, AIS organic. Now, um, grown over 100%. What kind of derivative impact did I have to ndr if any um you know Patty or or Matt just you would think there'd be some kind of like flow through of these customers buying more services on the platform. Um, and and I, you know, that that I would just be curious to see what kind of impact that had on that on that on that metric. Thank you.

Krista: On the second part of your question, a lot of the AI customers that are coming to us are new customers. So they're particularly in the infrastructure side of AI. They're not yet buying a tremendous amount of products on the CoreCloud side. Even if they did, they haven't been in the cohort long enough to count towards NDR. There's basically not much impact from that. That's the future benefit, which I think you're appropriately pointing out. I'm sorry, could you repeat the first part of your question?

Side of AI. So they're they're not yet buying, you know, a ton, a tremendous amount of um, of uh, of products on the core Cloud side and even if they did they haven't been in the cohort long enough to count towards ndr. So they're they're not they're not there's basically not much impact from that, that's the future benefit which I think you're

Speaker 7: Yeah. I was, I think you said earlier in the call to a question that CoreCloud, you know, kind of excluding AI/ML, accelerated. I just wanted to make sure I heard that correctly.

You're appropriately. Um, pointing out and I'm sorry. Can you repeat the first part of your question?

Krista: Yeah. Yeah. The year-over-year growth rates for the CoreCloud continue to improve. So again, when you look at a metric like NDR, it is again a function of what happened, a change in revenue last year compared to the change in revenue this year. So it has a lot of kind of laggy components to it. On the CoreCloud, in terms of the incremental ARR, the and the overall ARR growth of the core business, that continues to accelerate.

Yeah, I think you said earlier on the call to a question that uh, core class, you know, kind of excluding, AI ml, uh, accelerated. And I just wanted to make sure I heard that correctly.

Yeah, yeah. The the year-over-year growth rates for the in the core Cloud continue, uh, continue to improve. So, again, when you look at the metrics like ndr, it's again a function of what happened the change in, in, in Revenue, last year compared to the change in Revenue, this this year. So it's, it's got a lot of kind of laggy components to it, um, on the core cloud in terms of the, the incremental are the, um, the, the, um, uh, and the kind of the overall error growth of the core business, that that continues to accelerate.

Speaker 7: Thanks, God.

That's good.

Matt Steinfort: Your next question comes from the line of Wamsley Mohan with Bank of America. Please go ahead.

Your next question comes from the line of Walmsley moham with Bank of America. Please go ahead.

Speaker 8: Thanks for taking my question here. I guess firstly, on your AI customers, are you seeing higher volatility or churn in that customer base? Just to clarify, is the penetration of these customers, how would you categorize that between maybe learners, builders, scalers in your traditional way of thinking about the customers? Where are these in their journey? Any thoughts around graduation rates on these customers?

Padmanabhan Srinivasan: Yeah, great question, W. Steinfort. It's good to hear from you. It's a completely different customer acquisition motion. We do not think of them as testers, learners, builders, scalers because they typically do not go through that journey on our platform. A lot of these customers are in the initial stages, there were a lot of very early-stage startups. As we are seeing a lot of traction on the inferencing side, these customers, in their own evolution or in their own progression have crossed some of the chasms in terms of both funding as well as finding product-market fit and customer traction. They are coming to us with inferencing needs that are scaling, which by definition means that they have found product-market fit, and now they have a captive audience that is willing to pay for their inferencing need.

Uh, yes. Thanks for taking my question here. Um, I guess firstly on your, uh, AI customers. Are you seeing higher volatility or churn in that customer base and just to clarify, uh, is the penetration of these customers. How would you categorize that between maybe Learners builder, scalars, in your traditional way of of thinking about the customers where, where are these in their journey and any any thoughts around graduation rates on on these customers

Yeah, great question, 1. See, uh, it's good to hear from you. Um, the it's a completely different, customer acquisition motion. So we don't think of them as testers Learners Builder scalars because they typically don't go through that Journey on our platform. Um, a lot of these customers are, um, in in the initial stages, they were a lot of very early stage startups, uh, but as we are seeing a lot of traction, on the inferencing side, these customers

Padmanabhan Srinivasan: We are starting to see, there was a lot of the test and leave kind of phenomenon in the fine-tuning on the training side last year. Now, as we have started flipping more and more towards the inferencing side, these customers come, they stay, they expand, and they start leveraging different parts of our stack described in my diagram. It's a very different lifecycle that we are seeing on this side.

Um, in their own Evolution or in their own progression. Have crossed some of the chasms in terms of both funding as well as finding product Market fit, and customer traction. But they're coming to us with uh entrancing needs that are scaling, which by definition means that they have found product Market fit. And now they have a captive audience, that is willing to pay for their inferencing needs. So we are

Starting to see. Um, there was a lot of the, uh, um, the um, the test and and leave kind of phenomenon in the, uh, fine tuning on the training side last year. But now as we have started flipping more and more towards the inferencing side, these customers come, they stay, they expand, and they start leveraging, different parts of our stack described in, uh, in my diagram. So, um, it's a very different, uh, life cycle that we are seeing on this side.

Speaker 8: Okay. Great. Thanks, Paddy. If I could follow up quickly with Matt on the growth CapEx side, any incremental thoughts over here? I know you said organic investments and driving organic growth are sort of highest priorities. So, relative to your comments that you made last quarter, how should we be thinking about the growth CapEx profile over the next few quarters or into next year? Thank you so much.

Okay great, thanks Patty. And if I could follow up quickly with Matt on on the growth capex side, any incremental thoughts over here I know you said you know organic Investments and driving or organic growth just sort of highest priority. So um relative to your comments that you made last quarter, how should we be thinking about the uh, growth capex profile over the next few quarters or into next year? Thank you so much.

Krista: Yeah, thanks, W. Steinfort. Yeah, I think, a couple of things. One, I would point to, again, we've increased the pre-cash flow margin guidance, and we feel good about that relative to the growth rates that we're articulating. What we said in the last quarter and say again is if we see the opportunity to accelerate growth beyond what we communicated at the Investor Day of 18% to 20% by 2027, we certainly do that. We have a lot of tools in our toolkit to be able to do that in a capital-efficient and cash-flow-efficient way. So we remain very confident that we can grow revenue while maintaining attractive free cash flow margins.

Thanks. Yeah, I think, um, a couple things 1, I would I would point to you again. We've we've increased the free cash flow margin, uh, guidance and and um, feel good about that um uh relative to the uh to the growth rates that were articulating. And and what we said in the last quarter and you say again is if we see the opportunity to accelerate growth beyond what we communicated at the um at the uh investor day of 18 to 20% by by 2027. Um, we certainly do that and and we have a lot of tools in our tool kit.

To um, to be able to do that in a capital efficient and cash flow, efficient way. So we're we're very confident remain, very confident that we can grow Revenue, um, while maintaining attractive free cash flow margins.

Matt Steinfort: Ladies and gentlemen, that does conclude our question and answer session, and it does conclude today's conference call. Thank you for your participation. You may now disconnect.

Thank and ladies and gentlemen, that does conclude our question and answer session. And it does conclude today's conference call. Thank you for your participation and you may now disconnect