Q2 2026 Appen Ltd Earnings Call

August 27, 2026

Speaker #2: Hey everyone, and welcome to Appen's first half FY26 results webinar. I'm Sam Wells from NWR, and joining me from the company today is CEO and Managing Director, Ryan Cole.

Sam Wells: Everyone, and welcome to Appen's first half FY2026 results webinar. I am Sam Wells from NWR, and joining me from the company today is CEO and Managing Director, Ryan Kolln, and Chief Financial Officer, Justin Miles. Following a brief summary of the results released to the ASX this morning, we will have some time for Q&A with the management team. There will be a choice of two options. First, research analysts are able to raise their hand should you wish to ask a verbal question of the management team, or we will also take written questions via the Q&A function at the bottom of your screen throughout today's presentation. We will endeavor to get to the majority of questions asked, in some cases, combining questions on the same or similar topic. With that, I will pass it over to you, Ryan.

Sam Wells: Everyone, and welcome to Appen's H1 FY 2026 results webinar. I am Sam Wells from NWR, and joining me from the company today is CEO and Managing Director, Ryan Kolln, and Chief Financial Officer, Justin Miles. Following a brief summary of the results released to the ASX this morning, we will have some time for Q&A with the management team. There will be a choice of two options. First, research analysts are able to raise their hand should you wish to ask a verbal question of the management team, or we will also take written questions via the Q&A function at the bottom of your screen throughout today's presentation. We will endeavor to get to the majority of questions asked, in some cases, combining questions on the same or similar topic. With that, I will pass it over to you, Ryan.

Speaker #2: And Chief Financial Officer, Justin Miles. Following a brief summary of the results released to the ASX this morning, we will have some time for Q&A with the management team.

Speaker #2: There will be a choice of two options. First, research analysts are able to raise their hand should you wish to ask a verbal question of the management team, or we'll also take written questions via the Q&A function at the bottom of your screen throughout today's presentation.

Speaker #2: We'll endeavor to get to the majority of questions asked, in some cases combining questions on the same or similar topic. With that, I'll pass it over to you, Ryan.

Speaker #3: Thanks, Sam, and good morning everyone. Thanks for joining us today for our H1 FY26 results presentation. My name is Ryan Cole, and I'm the CEO and Managing Director at Appen.

Ryan Kolln: Thanks, Sam, and good morning, everyone. Thanks for joining us today for our H1 FY2026 results presentation. My name is Ryan Kolln. I am the CEO and Managing Director at Appen, and with me is Justin Miles, our CFO. Today's presentation covers four sections. I will start with the results overview. Justin will then walk through the detailed H1 FY2026 financial performance. Then I will return to cover our strategy and operational update, and we will close with an FY2026 outlook and guidance before opening up to questions. Let me start now with an overview of our H1 results on Page 5 of the presentation. The first half delivered on the themes that we have been building towards. At the group level, we delivered USD 119.9 million in revenue. This is 17% growth on the prior corresponding period. Appen China was a standout for the half.

Ryan Kolln: Thanks, Sam, and good morning, everyone. Thanks for joining us today for our H1 FY 2026 results presentation. My name is Ryan Kolln. I am the CEO and Managing Director at Appen, and with me is Justin Miles, our CFO. Today's presentation covers four sections. I will start with the results overview. Justin will then walk through the detailed H1 FY 2026 financial performance. Then I will return to cover our strategy and operational update, and we will close with an FY 2026 outlook and guidance before opening up to questions. Let me start now with an overview of our H1 results on Page 5 of the presentation. The H1 delivered on the themes that we have been building towards. At the group level, we delivered USD 119.9 million in revenue. This is 17% growth on the prior corresponding period. Appen China was a standout for the half.

Speaker #3: And with me is Justin Miles, our CFO. Today's presentation covers four sections. I'll start with the results overview. Justin will then walk through the detailed H1 FY26 financial performance.

Speaker #3: Then I'll return to cover our strategy and operational update, and we will close with an FY26 outlook and guidance before opening up to questions.

Speaker #3: Let me start now with an overview of our H1 results on page 5 of the presentation. The first half delivered on the themes that we've been building towards.

Speaker #3: At the group level, we delivered $119.9 million in revenue. This is 17% growth on the prior corresponding period. Appen China was a standout for the half.

Speaker #3: Revenue grew 80% to $76.2 million and achieved an annualized revenue run rate exceeding $175 million in June. That is up from $135 million at the end of 2025.

Ryan Kolln: Revenue grew 80% to USD 76.2 million and achieved an annualized revenue run rate exceeding USD 175 million in June. That is up from USD 135 million at the end of 2025. The sustained growth reflects the strength of our relationships with the Chinese model builders and the ongoing demand for our data services in the region. Appen Global continues to make progress. Outside of our largest client, Q2 revenue grew 65% on Q1. We are progressing well in our ambition to expand across frontier AI labs in the USA. Capturing cost efficiencies via AI-enabled operations remains a focus for Appen Global. We have identified an incremental USD 12 million in operational efficiencies. 70% of the USD 12 million will be executed before the end of the year and the remainder in Q1 FY2027.

Speaker #3: The sustained growth reflects the strength of our relationships with the Chinese model builders and the ongoing demand for our data services in the region.

Speaker #3: Appen Global continues to make progress outside of our largest client. Q2 revenue grew 65% on Q1. We're progressing well in our ambition to expand across frontier AI labs in the USA.

Speaker #3: Capturing cost efficiencies via AI-enabled operations remains a focus for Appen Global. We have identified an incremental $12 million in operational efficiencies. Seventy percent of the $12 million will be executed before the end of the year, and the remainder in Q1, FY27.

Speaker #3: It's important to note that the cost outflow impacts the ability to grow within Appen Global. On profitability, we delivered an underlying EBITDA before effects of $5.3 million for the half, a $7.5 million improvement on the first half of last year.

Ryan Kolln: It is important to note that the cost outs do not impact the ability to grow within Appen Global. On profitability, we delivered an underlying EBITDA before FX of $5.3 million for the half, a $7.5 million improvement on the H1 of last year. EBITDA margins for the half were 4.5%. Our cash balance at 30 June was $44.7 million, equivalent to AUD 64.8 million. I will now hand over to Justin, who will take us through the financials.

Speaker #3: EBITDA margins for the half were 4.5%. Our cash balance at 30 June was $44.7 million, equivalent to $64.8 million Australian dollars. I'll now hand over to Justin, who will take us through the financials.

Speaker #2: Thank you, Ryan, and good morning, everybody. A reminder that we report in US dollars, and that all comparisons are to the half-year ended 30 June 2025, unless stated otherwise.

Justin Miles: Thank you, Ryan, and good morning, everybody. A reminder that we report in USD and that all comparisons are to the half year ended 30 June 2025, unless stated otherwise. Starting with the H1 FY26 profit and loss on page seven. As Ryan already mentioned, revenue increased 17.5% to $119.9 million. Within our operating segments, Appen China revenue grew by 80.4% to $76.2 million, with Appen Global down 26.9% to $43.7 million. Appen Global made solid progress during the half. However, growth in new areas has not yet offset a reduction in traditional work. Gross margin reduced slightly, down 30 basis points to 36.7%. The decrease reflects a change in customer and project mix. Noting China margins are traditionally lower compared to Appen Global. Underlying EBITDA before FX improved $7.5 million to $5.3 million.

Speaker #2: Starting with the H1 FY26 profit and loss on page 7. As Ryan already mentioned, revenue increased 17.5% to $119.9 million. Within our operating segments, Appen China revenue grew by 80.4% to $76.2 million, with Appen Global down 26.9% to $43.7 million.

Speaker #2: Appen Global made solid progress during the half. However, growth in new areas has not yet offset a reduction in traditional work. Gross margin reduced slightly, down 30 basis points to 36.7%.

Speaker #2: The decrease reflects a change in customer and project mix, noting China margins are traditionally lower compared to Appen Global. Underlying EBITDA before FX improved by $7.5 million to $5.3 million.

Speaker #2: The increase reflects revenue and gross margin growth, prudent cost management, and operational leverage within Appen China. I won't talk to slide 8, as we have just covered this data.

Justin Miles: The increase reflects revenue and gross margin growth, prudent cost management, and operational leverage within Appen China. I will not talk to slide eight as we have just covered this data. So over to Appen Global revenue and to EBITDA on slide nine. The chart on the left shows quarterly revenue, and on the right-hand side, it is underlying EBITDA. The charts demonstrate the progress made during the half. Q2 FY26 revenue reflects growth from expanding projects with leading AI labs. Pleasingly, outside the largest customer, Q2 FY26 revenue grew 65% compared to Q1 FY26. However, as just mentioned, growth in new areas has not yet offset a reduction in traditional work, resulting in revenue of $43.7 million for the half, which is down compared to H1 FY25. An important point to note is that traditional work has currently stabilized.

Speaker #2: So, over to Appen Global revenue and EBITDA on slide 9. The chart on the left shows quarterly revenue, and on the right-hand side is underlying EBITDA.

Speaker #2: The charts demonstrate the progress made during the half. Q2 FY26 revenue reflects growth from expanding projects with leading AI labs. Pleasingly, outside the largest customer, Q2 FY26 revenue grew 65% compared to Q1 FY26.

Speaker #2: However, as just mentioned, growth in new areas has not yet offset a reduction in traditional work, resulting in revenue of $43.7 million for the half, which is down compared to H1 FY25.

Speaker #2: An important point to note is that traditional work has currently stabilized. EBITDA reflects some investment in winning new customer projects and does show improvement during the period.

Justin Miles: EBITDA reflects some investment in winning new customer projects and does show improvement during the period. Ryan has already mentioned this, but again noting that approximately $12 million in operational efficiencies have been identified in the Appen Global segment, with 70% to be executed by the end of this year and the remainder in Q1 next year. Over to slide 10, which shows quarterly revenue and underlying EBITDA for Appen China and reflects the strong market position Appen China continues to hold. Revenue grew each quarter, with Appen China achieving $76.2 million revenue for H1 FY26, which was 80% growth on H1 FY25. Growth continues to be driven by new and expanding LLM-related projects. Appen China exited the half with annualized revenue exceeding $175 million.

Speaker #2: Ryan has already mentioned this, but I want to note again that approximately $12 million in operational efficiencies have been identified in the Appen Global segment, with 70% to be executed by the end of this year and the remainder in Q1 next year.

Speaker #2: Moving on to slide 10, which shows quarterly revenue and underlying EBITDA for Appen China, and reflects the strong market position Appen China continues to hold.

Speaker #2: Revenue grew each quarter, with Appen China achieving $76.2 million in revenue for H1 FY26, which was 80% growth over H1 FY25. Growth continues to be driven by new and expanding LLM-related projects.

Speaker #2: Appen China exited the half with annualized revenue exceeding $175 million. Pleasingly, in addition to revenue growth, profitability has improved, with increased gross margins due to a greater mix of Gen AI projects and increased revenue from high-margin pre-built data sets.

Justin Miles: Pleasingly, in addition to revenue growth, profitability has improved, with increased gross margins due to a greater mix of GenAI projects and increased revenue from high-margin pre-built datasets. Appen China is also capturing scaling efficiencies due to tight OpEx controls as revenue expands. Turning to slide 11 for the profit and loss summary. I will not talk to all line items. However, there are a few additional points to highlight. There was a decrease in employee and other expenses in Appen Global, and this is highlighted later in the presentation. Employee expenses for Appen Global were down 19% on PCP and other expenses down 29% on PCP. The decrease was achieved through technology innovation and automation. The decrease in Appen Global was offset by additional expense from the Appen China segment to enable the delivery of strong revenue growth.

Speaker #2: Appen China is also capturing scaling efficiencies due to tight OPEX controls as revenue expands. Turning to slide 11 for the profit and loss summary.

Speaker #2: I won't talk to all line items. However, there are a few additional points to highlight. There was a decrease in employee and other expenses in Appen Global.

Speaker #2: And this is highlighted later in the presentation. Employee expenses for Appen Global were down 19% on pcp, and other expenses were down 29% on pcp.

Speaker #2: The decrease was achieved through technology innovation and automation. The decrease in Appen Global was offset by additional expense from the Appen China segment to enable the delivery of strong revenue growth.

Speaker #2: The $14.9 million MPAT improvement and $8 million improvement to underlying NPAT reflect the improved performance for the half, as well as a decrease in amortization.

Justin Miles: The 14.9 million NPAT improvement and AUD 8 million improvement to underlying NPAT reflects the improved performance for the half, as well as a decrease in amortization. I will finish up with the cash flow summary on slide 12. The cash balance at the end of the period was USD 44.7 million. The Australian dollar equivalent cash balance is AUD 64.8 million. Despite the decrease in balance compared to the prior period, a strong balance remains. Cash flow used in operations was USD 2.7 million. In comparing to the prior period, it is important to note that H1 FY25 was positively impacted by the receipt of a payment from a major customer in the first week of January 2025 versus December 2024 as scheduled. Cash flow used in operations for the period was impacted by the timing of customer receipts, annual payments during the period, and working capital required to support strong Appen China growth.

Speaker #2: I'll finish up with the cash flow summary on slide 12. The cash balance at the end of the period was $44.7 million. The Australian dollar equivalent cash balance is $64.8 million.

Speaker #2: Despite the decrease in balance compared to the prior period, a strong balance remains. Cash flow used in operations was $2.7 million. In comparing to the prior period, it is important to note that H1 FY25 was positively impacted by the receipt of a payment from a major customer.

Speaker #2: In the first week of January '25 versus December '24 as scheduled. Cash flow used in operations for the period was impacted by the timing of customer receipts.

Justin Miles: Cash flow used in operations for the period was impacted by the timing of customer receipts, annual payments during the period, and working capital required to support strong Appen China growth. Cash used in investing activities was USD 1.9 million higher compared to H1 FY25 due to higher investment in product development and new facilities for the Appen China division. Cash used in finance activities of USD 2.7 million reflects lease payments. Cash was used to fund operations and CapEx. That concludes the financial performance slides. I will now hand back to Ryan.

Speaker #2: Annual payments during the period, and working capital required to support strong Appen China growth. Cash used in investing activities was $1.9 million higher compared to H1 FY25 due to higher investment in product development and new facilities for the Appen China division.

Justin Miles: Cash used in investing activities was USD 1.9 million higher compared to H1 FY25 due to higher investment in product development and new facilities for the Appen China division. Cash used in finance activities of USD 2.7 million reflects lease payments. Cash was used to fund operations and CapEx. That concludes the financial performance slides. I will now hand back to Ryan.

Speaker #2: Cash used in financing activities of $2.7 million reflects lease payments. Cash was used to fund operations and capex. That concludes the financial performance slides.

Speaker #2: I'll now hand back to Ryan.

Speaker #1: Thanks, Justin. I'll now cover the strategy and operational progress that we've made in the half. So, turning to page 14, to understand Appen's service that helps us start where the value sits in AI development.

Ryan Kolln: Thanks, Justin. I will now cover our strategy and operational progress that we have made in the half. Turning to page 14. To understand Appen's services, it helps to start where the value sits in AI development. There are three fundamental building blocks for AI development: compute, algorithms, and data. Compute is abundant and commoditizing. Algorithms are increasingly open and largely commoditized, while unique data is becoming scarce and is a major source of differentiation for AI model performance. Not all data is equal. There are many facets of data used to train models, all with different uses. Public data is largely exhausted, and it has already been captured in existing models and offers little ability to differentiate. Synthetic data is reliant on other models to produce, does not solve new or novel situations, and can result in model collapse if overused.

Speaker #1: There are three fundamental building blocks for AI development: compute, algorithms, and data. Compute is abundant and commoditizing. Algorithms are increasingly open and largely commoditized, while unique data is becoming scarce and is a major source of differentiation for AI model performance.

Speaker #1: But not all data is equal. There are many facets of data used to train models, all with different uses. Public data is largely exhausted, and it’s already been captured in existing models and offers little ability to differentiate.

Speaker #1: Synthetic data is reliant on other models to produce. It does not solve new or novel situations and can result in model collapse if overused. Real-world, bespoke data—the kind that Appen creates—enables new AI approaches.

Ryan Kolln: Real-world bespoke data, the kind that Appen creates, enables new AI approaches. It brings human expertise and interactions that improve and evaluate models in ways that alternatives cannot replicate. This is the market that Appen serves. The primary way that we serve our clients is through a managed services approach, where we build custom and high-value datasets that are specific to the AI model needs. The usual first step is that a researcher comes to us with their data needs. It could be a description of the task, expertise requirements, quality rubrics, data volumes, and timelines. Our delivery experts work very closely with clients to deeply understand their intentions and translate that into a data workflow that typically coordinates a set of complex and iterative handoffs between humans and AI models to generate the data.

Speaker #1: It brings human expertise and interactions that improve and evaluate models in ways that alternatives can't replicate. This is the market that Appen serves. The primary way that we serve our clients is through a managed services approach.

Speaker #1: We build custom and high-value datasets that are specific to the AI model needs. The usual first step is that a researcher comes to us with their data need. This could be a description of the task, expertise requirements, quality rubrics, data volumes, and timelines.

Speaker #1: Our delivery experts work very closely with clients to deeply understand their intentions and translate that into a data workflow that typically coordinates a set of complex and iterative handoffs between humans and AI models to generate the data.

Speaker #1: We deliver through a combination of our research and delivery experts, our proprietary software stack, and our expert workforce marketplace. The output we provide is high-quality data for leading AI organizations, including the global Q1 AI labs.

Ryan Kolln: We deliver through a combination of our research and delivery experts, our proprietary software stack, and our expert workforce marketplace. The output we provide is high-quality data for leading AI organizations, including the global tier 1 AI labs. What differentiates Appen is the combination of the platform, people, and our global reach. Our workforce is a core competitive asset. More than 1 million contributors across 200 plus countries and over 500 dialects and languages covered. We focus on building out our domain expertise in our workforce. We now have contributors covering more than 100 specialist fields, from computer science and mathematics to law, medicine, and the creative disciplines. Generative AI demands a different type of contributor. It requires people who can reason, evaluate, and provide expert-level feedback. Our workforce has rapidly evolved to support the new expert-level requirements of our customers.

Speaker #1: What differentiates Appen is the combination of our platform, our people, and our global reach. Our workforce is a core competitive asset, with more than 1 million contributors across 200-plus countries, and over 500 dialects and languages covered.

Speaker #1: We focus a lot on building out our domain expertise in our workforce. We now have contributors covering more than 100 specialist fields, from computer science and mathematics to law, medicine, and the creative disciplines.

Speaker #1: Generative AI demands a different type of contributor. It requires people who can reason, evaluate, and provide expert-level feedback. Our workforce has rapidly evolved to support the new, expert-level requirements of our customers.

Speaker #1: And our service offering continues to expand and now covers nine categories. It's evolving rapidly with the needs of our customers. Some of the areas we are working in include LLM training data, covering supervised fine-tuning, RLHF, and preference annotation.

Ryan Kolln: Our service offering continues to expand and covers 9 categories, and it is evolving rapidly with the needs of our customers. Some of the areas that we are working in include LLM training data, covering supervised fine-tuning, RLHF, and preference annotation. Multimodal data across text-to-image annotation, aesthetic scoring, video labeling, and embodied intelligence. Speech and audio across a broad set of languages. Domain expert annotation in medical, scientific, legal, and financial fields, amongst many others. Model evaluation, covering LLM and vision benchmarking and search quality performance. Computer vision and physical AI for autonomous driving, robotics, smart home, AR/VR, and embodied AI. We also offer reinforcement learning environments, off-the-shelf datasets, and platform and tooling solutions. The breadth of our offering allows us to evolve with the needs of the leading AI labs. We have recently expanded our dataset offering significantly.

Speaker #1: Multimodal data across text-to-image annotation, aesthetic scoring, video labeling, and body intelligence. Speech and audio, across a broad set of languages. Domain expert annotation in medical, scientific, legal, and financial fields, among many others.

Speaker #1: Model evaluation, covering LLM and vision benchmarking, and search quality performance. Computer vision and physical AI for autonomous driving, robotics, smart home, AR/VR, and embodied AI.

Speaker #1: We also offer reinforcement learning environments, off-the-shelf datasets, and platform and tooling solutions. The breadth of our offering allows us to evolve with the needs of the leading AI labs.

Speaker #1: We've recently expanded our data set offering significantly. These are the existing data sets that we either own or resell, with value-added services on top.

Ryan Kolln: These are the existing datasets that we either own or resell with value-added services on top. We are seeing an increase in the demand for these datasets, and we are building out a catalog to meet the specific needs of model builders. Some of the areas where we have recently added datasets include reinforcement learning tasks, code repositories, book corpuses, enterprise data for agentic AI, and many other standalone datasets covering unique areas like medical dictation, STEM Q&A, and infographics. These products accelerate time to value for our customers and often also come alongside managed service projects to add value to the datasets. We anticipate this to be a solid growth driver in the near future. A unique proposition of Appen is our coverage of the 2 AI epicenters, namely China and the US. We operate 2 dedicated businesses to cover these markets, each purpose-built for the specific customer requirements.

Speaker #1: We're seeing an increase in the demand for these datasets, and we're building out a catalog to meet the specific needs of model builders.

Speaker #1: Some of the areas where we have recently added data sets include reinforcement learning tasks, code repositories, book corpora, enterprise data for agentic AI, and many other standalone data sets covering unique areas like medical dictation, STEM Q&A, and infographics.

Speaker #1: These products accelerate time to value for our customers and often also come alongside managed service projects to add value to the data sets. We anticipate this to be a solid growth driver in the near future.

Speaker #1: A unique proposition of Appen is our coverage of the two AI epicenters, namely China and the USA. We operate two dedicated businesses to cover these markets, each purpose-built for the specific customer requirements.

Ryan Kolln: We operate 2 dedicated businesses to cover these markets, each purpose-built for the specific customer requirements.

Speaker #1: Appen Global serves the USA and Europe, targeting hyperscalers, foundational AI companies, and vertical AI builders. Demand drivers include AI capabilities, new customer expansions, and new data modalities.

Ryan Kolln: Appen Global serves the USA and Europe, targeting hyperscalers, foundational AI companies, and vertical AI builders. Demand drivers include AI capabilities, new customer expansions, and new data modalities. Appen China serves China, Japan, and Korea, targeting Chinese big tech, foundational AI, and vertical AI builders. In addition to the demand drivers, international expansion is an increasing driver of Chinese model builders looking to compete in the global markets. Each business has its own dedicated operations and technology stack. That separation allows us to optimize for the distinct requirements of each market without compromise. As Justin Miles mentioned earlier, Appen Global's technology roadmap has continued to deliver operational efficiencies. Employee expenses in H1 2026 came in at $14.4 million, down from $17.7 million in H1 2025. Other expenses were $8.1 million compared to $11.4 million in H1 2025.

Speaker #1: Appen China serves China, Japan, and Korea, targeting Chinese big tech foundational AI and vertical AI builders. In addition to the demand drivers, international expansion is an increasing driver as Chinese model builders look to compete in global markets.

Speaker #1: Each business has its own dedicated operations and technology stack. That separation allows us to optimize for the distinct requirements of each market, without compromise.

Speaker #1: As Justin mentioned earlier, Appen Global's technology roadmap continues to deliver operational efficiencies. Employee expenses in H1 FY26 came in at $14.4 million, down from $17.7 million in H1 FY25.

Speaker #1: Other expenses were $8.1 million, compared to $11.4 million in H1 FY25. We continue to be highly focused on driving technology-led efficiencies across our operations, particularly through the use of AI.

Ryan Kolln: We continue to be highly focused on driving technology-led efficiencies across our operations, particularly through the use of AI. We have identified approximately $12 million in incremental annualized cost efficiencies. Around 70% will be executed over the remainder of 2026, with the balance by the end of Q1 2027. Importantly, there has been no operational impact from the cost outwork executed to date. We are capturing efficiencies through AI-enabled operations, not by reducing our abilities to deliver high-quality data at speed. Let me now turn to our outlook and guidance statement for the full year. We remain confident in the AI data market and Appen's ability to contribute meaningfully to the development of leading foundation models. We continue to see positive signals on LLM-related growth from both Appen Global and Appen China customers. We are winning new work with leading AI labs and expanding existing programs.

Speaker #1: We have identified approximately $12 million in incremental annualized cost efficiencies. Around 70% will be executed over the remainder of FY26, with the balance by the end of Q1 FY27.

Speaker #1: Importantly, there has been no operational impact from the cost-out work executed to date. We're capturing efficiencies through AI-enabled operations, not by reducing our ability to deliver high-quality data at speed.

Speaker #1: Let me now turn to our outlook and guidance statement for the full year. We remain confident in the AI data market and Appen's ability to contribute meaningfully to the development of leading foundation models.

Speaker #1: We continue to see positive signals on LLM-related growth from both Appen Global and Appen China customers. We are winning new work with leading AI labs and expanding existing programs.

Speaker #1: We remain focused on driving technology-led efficiencies across our operations. As in previous years, Appen Global revenue is predominantly project-based, and seasonality continues to skew revenue towards H2.

Ryan Kolln: We remain focused on driving technology-led efficiencies across our operations. As in previous years, Appen Global revenue is predominantly project-based and seasonality continues to skew revenue towards H2. Considering all of this, we reaffirm our 2026 guidance of group revenue of $270 to $300 million and underlying EBITDA before FX margin of 5% to 10%. That concludes our presentation for today. Thank you for your time and your continued interest in Appen. Justin Miles and I are now happy to take questions.

Speaker #1: Considering all of this, we reaffirm our FY26 guidance of group revenue of $270 to $300 million and underlying EBITDA before FX margin of 5% to 10%.

Speaker #1: That concludes our presentation for today. Thank you for your time and your continued interest in Appen. Justin and I are now happy to take questions.

Speaker #2: Great. Thank you very much, Ryan and Justin. As a reminder, research analysts can ask questions by raising your hand on Zoom, and I'll aim to get to you shortly.

Sam Wells: Great. Thank you very much, Ryan Kolln and Justin Miles. As a reminder, research analysts can ask questions via raising your hand on Zoom, and I will aim to get to you shortly, while the remainder of the audience can submit written questions via the Q&A function at the bottom of your screen. We will kick off with some pre-submitted questions before getting to any analyst questions today. First, on profit sustainability, can you clarify how much of the recent EBITDA improvement is driven by a permanent structural cost reduction versus temporary project-based revenues?

Speaker #2: While the remainder of the audience can submit written questions via the Q&A function at the bottom of your screen, we'll kick off with some pre-submitted questions before getting to any analysts' questions today.

Speaker #2: First, on profit sustainability, can you clarify how much of the recent EBITDA improvement is driven by a permanent structural cost reduction, versus temporary project-based revenues?

Speaker #1: Yeah, thanks, Sam. So we're definitely focused on a sustainable cost base and profitable growth across the business. The good thing is that, particularly for China, we're seeing improved margins.

Ryan Kolln: Yeah. Thanks, Sam. We are definitely focused on a sustainable cost base and profitable growth across the business. The good thing is that, particularly for China, we are seeing improved margins. That is coming through the gross margin of China improving. We are also getting the leverage of the scaling efficiencies in the China business. As we have called out, we have continued to drive OpEx improvement in Appen Global. So multitude of factors, but we see this as a sustainable and ongoing trend in the business.

Speaker #1: That's coming through the gross margin at China—improving—but also we're getting the leverage of scaling efficiencies in the China business. And, as we've called out, we've continued to drive OPEX improvement in Appen Global.

Speaker #1: So, a multitude of factors, but we see this as a sustainable and ongoing trend in the business.

Speaker #2: Okay, great. Thank you. And just to follow up there, what baseline quarterly revenue is currently required to maintain positive EBITDA through the second half of FY26?

Sam Wells: Okay, great. Thank you. Just to follow up there, what baseline quarterly revenue is currently required to maintain positive EBITDA through the H2 of FY26?

Speaker #1: Well, I think it's fairly similar to where we're at with that. In Q2, as we said, we've made some efficiencies across the business, so there's not a material uplift required to deliver profitability through the remainder on a quarterly basis.

Ryan Kolln: Well, I think it is fairly similar to where we are at with that. In Q2, as we said, we have made some efficiencies across the business. There is not a material uplift required to deliver profitability through the remainder at a quarterly basis.

Sam Wells: Great. Thank you. On cash runway and free cash flow, given the cash balance, what is the current projected timeline to achieve consistent positive free cash flow?

Speaker #2: Great, thank you. And on cash runway and free cash flow, given the cash balance, what's the current projected timeline to achieve consistent, positive free cash flow?

Ryan Kolln: I'll throw that one to Justin.

Speaker #1: Yeah, I'll throw that one to Justin.

Speaker #3: Thanks, Ryan. Thanks for the question, Sam. Obviously, part of the strategy—we're talking about the efficiencies and the performance of the business and the growth in Appen Global.

Justin Miles: Thanks, Ryan. Thanks for the question, Sam. Obviously, part of the strategy, we're talking about the efficiencies and the performance of the business and the growth in Appen Global. We're well towards heading in the right direction and well towards achieving that. That is the goal, sustained profitability and free cash flows. We've got enough cash. We've got a strong cash balance. There's enough working capital. We're confident that the runway's there. There's no additional funds required to manage the growth. We're definitely heading towards it. We're heading in the right direction, and we're not too far off.

Speaker #3: We are well on our way, heading in the right direction and progressing towards achieving that. That is the goal: sustained profitability and free cash flows. So, we've got enough cash.

Speaker #3: We've got a strong cash balance. There's enough working capital. We're confident that the runway's there. There's no additional funds required to manage the growth.

Speaker #3: So we're definitely heading towards it. We're heading in the right direction, and we're not too far off.

Speaker #2: Okay. And another follow-up there: should shareholders expect the current cash reserves to be sufficient to fund operations until self-sustainability is reached?

Sam Wells: Okay, and another follow-up there. Should shareholders expect the current cash reserves to be sufficient to fund operations until self-sustainability is reached?

Speaker #3: Based on everything we know today, yes.

Justin Miles: Based on everything we know to date, yes.

Speaker #2: Thank you. And just one more pre-submitted question before we get to the analysts. On revenue diversification, outside Appen's core hyperscaler clients, what specific momentum or contract wins are we seeing in the broader enterprise AI market?

Sam Wells: Thank you. Just one more pre-submitted question before we get to the analysts. On revenue diversification, outside Appen's core hyperscaler clients, what specific momentum or contract wins are we seeing in the broader enterprise AI market, and how long are the typical sales cycles for these newer revenue streams?

Speaker #2: And how long are these, sorry, are the typical sales cycles for these newer revenue streams?

Speaker #1: So, we're very focused on the large foundation model builders and the new labs that are popping up, typically spun out of the research divisions of these large AI labs.

Ryan Kolln: We are very focused on the large foundation model builders and the neo labs that are popping up, typically spun out of the research division of these large AI labs. That remains the focus of Appen at the moment. That is where the bulk of the spend is in the market, and it is highly aligned to the capabilities that we are building. In terms of the deal cycle time, it can vary quite extreme. Some of the deals are very short lead time. If researchers are contemplating specific areas they want to work through and there is a good amount of back and forth, that can introduce a longer sales cycle. It is certainly trending towards much shorter sales cycles.

Speaker #1: So that remains the focus of Appen at the moment. That's where the bulk of the spend is in the market, and it's highly aligned to the capabilities that we're building.

Speaker #1: In terms of the deal cycle time, it can vary quite a bit. Some of the deals have a very, very short lead time. In some cases, if researchers are contemplating specific areas they want to work through and there's a good amount of back and forth, that can introduce a longer sales cycle.

Speaker #1: But it’s certainly trending towards much, much shorter sales cycles.

Speaker #2: Okay, great. Thank you. Next question comes from Nicola Wilmette at Barren Joy. Nicola, please unmute your line and go ahead. Nicola at Barren Joy, would you like to ask a verbal question?

Sam Wells: Okay, great. Thank you. Next question comes from Nicola Wilmot at Barrenjoey. Nicola, please unmute your line and go ahead. Nicola at Barrenjoey, would you like to ask a verbal question? Please unmute your line.

Speaker #2: Please unmute your line.

Josh Kannourakis: Hi, guys. It is Josh Kannourakis here. Can you hear me?

Speaker #4: Hi, guys. It's Josh Kenaraka here. Can you hear me?

Speaker #2: Yeah. Hi, Josh.

Sam Wells: Yeah. Hi, Josh.

Josh Kannourakis: Oh, cool. Sorry. Nicola's just looking at me a bit funny. All good. No worries. Just the first couple of questions to get kicked off. First one, just around in the global business. I know obviously there were some reasonably chunky customers in terms of that you had contracts for that you ended last year. Some of those contracts were potentially coming back. What have you seen in terms of the start? I know visibility's obviously not high, but what are some of the conversations and scope for work that you see from both some of the traditionally big customers that you have, but also, as we said, some of

Speaker #4: Oh, cool. Sorry. Nicola's just looking at me a bit funny here. All good, no worries. So just the first couple of questions to get kicked off.

Speaker #4: First one, just around in the global business. So I know, obviously, there were some reasonably chunky customers in terms of that you had contracts for, that you ended last year on.

Speaker #4: Some of those contracts were potentially coming back. What have you seen in terms of the start? And I know visibility is obviously not high, but what are some of the, I guess, the conversations and scope for work that you see from both some of the traditionally big customers that you have, but also, as we said, some of the foundational other customers into the second half? And just to talk a little bit about, yeah, what confidence you have in that deliverability to deliver into the second half there?

Josh Kannourakis: the foundational other customers into H2? Just to talk a little bit about what confidence you have in that ability to deliver into H2 there.

Speaker #1: Yeah, thanks, Josh. So there are a few things that are giving us some really good confidence at the moment. The first is we've been able to penetrate into some new areas within existing customers that are really focused on the foundation model build.

Ryan Kolln: Yeah. Thanks, Josh. There are a few things that are giving us some really good confidence at the moment. First is, we've been able to penetrate into some new areas within existing customers that are really focused on the foundation model build. We started in specific areas that, starting as a first project in a specific domain. Now what we're seeing is a much broader set of conversations around growth opportunities, not just within the projects that we're working on, but across a broader set of domains. A lot of these growth opportunities are in areas that we've been strategically investing our capabilities in. Some of the things that we've called out, like coding, finance, healthcare, really pushing into the more valuable part of the market at the moment to support AI development in specific data modalities.

Speaker #1: And we've started in specific areas, starting with the first project in a specific domain, and now what we're seeing is a much broader set of conversations around growth opportunities—not just within the projects that we're working on, but across a broader set of domains.

Speaker #1: And a lot of these growth opportunities are in areas that we've been strategically investing our capabilities in. So, some of the things that we've called out—like coding, finance, healthcare—are really pushing into the more valuable part of the market at the moment, to support AI development in specific data modalities.

Speaker #4: Got it, that's helpful. And traditionally, the margin on those sorts of projects as well, versus maybe where the historical gross margin is—can you give a bit of context on that?

Josh Kannourakis: Got it. That's helpful. Traditionally, the margin on those sorts of projects as well, versus maybe where the historical gross margin is. Can you give a bit of context on that?

Speaker #1: Yeah, it can vary, but you should think about them broadly as similar to the traditional margins that we've seen in the business.

Ryan Kolln: Yeah. It can vary, but you should think about them broadly similar to the traditional margins that we've seen in the business.

Josh Kannourakis: Got it. Just while we're on Global, just the competitive environment in terms of what you're seeing out there. Obviously, there's a number of players. What are you guys seeing in terms of when you are in those new markets? What the competition is? Is price coming into it? Is it more around the deliverability or the quality? Maybe just to talk through some of those frameworks that you think customers are using to choose the vendors

Speaker #4: Got it. And just while we're on global, just the competitive environment in terms of what you're seeing out there. Obviously, there are a number of players.

Speaker #4: What are you guys seeing in terms of, when you are in those new markets, what the competition is? Is price coming into it?

Speaker #4: Is it more around the deliverability or the quality? Maybe just talk through some of the frameworks that you think customers are using to choose vendors in that space?

Josh Kannourakis: in that space.

Speaker #1: So, the ability to deliver high-quality data is always number one. We don't see price as a major factor, particularly for the AI labs. We see quality and speed being the two primary considerations.

Ryan Kolln: The ability to deliver high-quality data is always number one. We don't see price as a major factor, particularly for the AI labs. We see quality and speed being the two primary considerations. We use a call-out. There are some competitors that are growing very rapidly, and that's built on a lot of, they're established within the companies. They've got the trust of the researchers, and the researchers go directly to them because they trust their ability to deliver quality and it speeds up the cycle rather than running an RFP process. That's what's giving me a lot of confidence in the Appen Global momentum that we're seeing is because of the conversations that we're having in specific labs, and it's across multiple labs. They're really satisfied with our work. The quality is really great. That's leading to bigger opportunities.

Speaker #1: And we used to call out that there are some competitors that are growing very rapidly. And that's built on a lot of—they're established within the companies.

Speaker #1: They've got the trust of the researchers. And the researchers go directly to them because they trust their ability to deliver quality, and they trust that it speeds up the cycle rather than running an RFP process.

Speaker #1: And that's what's giving me a lot of confidence in the Appen Global momentum that we're seeing, because of the conversations that we're having.

Speaker #1: In specific labs, and it's across multiple labs, they're really satisfied with our work. The quality is really great. That's leading to bigger opportunities, but it is backed up by their confidence that we are delivering high quality.

Ryan Kolln: It is on the back of their confidence that we are delivering high quality, and that we can turn around the data really quickly for them. The thematic that we're seeing with some of our competitors is really starting to play out within Appen Global.

Speaker #1: And that we can turn around the data really quickly for them. So the thematic that we're seeing with some of our competitors is really starting to play out with an Appen global.

Speaker #4: Right. And just moving on to Appen Join or another stellar result, obviously, but when we look at that business, now it looks and we've seen, I think, what probably one thing that's changed a little bit since we last talked is just the rapid release including, I think, even yesterday one of the sort of GLM3 coming into one of the Chinese models coming in at sort of record things.

Josh Kannourakis: Great. Just moving on to Appen China, another stellar result, obviously. When we look at that business, and we've seen, I think, well, probably one thing that's changed a little bit since we last talked is just the rapid release, including, I think, even yesterday, one of the GLM coming in, one of the Chinese models.

Josh Kannourakis: Coming in at record things. Then Qwen and the like as well, coming out with some fantastic models.

Speaker #4: So, and then Quin and the like as well coming out with some fantastic models. I mean, there's been a lot of talk around the geopolitical aspects here, but it does feel like the Chinese models are definitely trying to accelerate into the U.S. and other markets as fast as possible.

Josh Kannourakis: There's been a lot of talk around the geopolitical aspects here, but it does feel like the Chinese models are definitely trying to accelerate into the US and other markets as fast as possible. I think some of the OpenRouter stuff

Speaker #4: And I think some of the OpenRouter stuff is saying it's over 60% of the tokens that are coming through from those models there.

Ryan Kolln: Yeah

Josh Kannourakis: is saying it's over 60% of the tokens that

Josh Kannourakis: is saying it's over 60% of the tokens that are now coming through from those models there. I'm just interested in maybe under the hood, what the trends you're seeing and how should we think about the breakup of that work, the continuation of that trend. It looked like obviously

Josh Kannourakis: are now coming through from those models there. I'm just interested in maybe under the hood, what the trends you're seeing and how should we think about the breakup of that work, the continuation of that trend. It looked like obviously

Speaker #4: So, I mean, I'm just interested in maybe, under the hood, what trends you're seeing, and how should we sort of think about the breakup of that work and the continuation of that trend.

Speaker #4: It looked like, obviously, Q4, there was a bit of an acceleration. And then margins are also tracking. So maybe just a bit of context around the type of work you're seeing, the type of customers, your confidence in the revenue momentum, and then confidence around further margin upside there.

Ryan Kolln: Yeah

Josh Kannourakis: in Q4, there was a bit of an acceleration, and then margins are also

Josh Kannourakis: in Q4, there was a bit of an acceleration, and then margins are also tracking. Maybe just a bit of a context around the type of work you are seeing, the type of customers, your confidence in the revenue momentum, and then confidence around the margin upside there.

Josh Kannourakis: tracking. Maybe just a bit of a context around the type of work you are seeing, the type of customers, your confidence in

Josh Kannourakis: the revenue momentum, and then confidence around the margin upside there.

Speaker #1: Yeah, and look, there's some incredibly exciting and impactful work coming out from the open source model builders in China, which I think we all get a lot of visibility into, and we can all kind of predict that that's going to be a continued focus.

Ryan Kolln: Yeah. Look, it is some incredibly exciting and impactful work coming out from the open source model builders in China, which I think we all get a lot of visibility into, and we can all kind of predict that that is going to be a continued focus. I think some of the things that we see on the ground in China, which do not get as much exposure outside is the real focus on, I will call it consumer-based AI, where through the super apps, the companies in China, the AI labs, the focus on things like healthcare advice, financial advice. We are starting to see a lot of video generation, AI video generation, particularly in short-form videos. I think they are a fair way ahead of the US on the video generation side, or at least getting the applications out that are supported by these models.

Speaker #1: I think some of the things that we see on the ground in China, which don't get as much exposure outside, is the real focus on what I will call consumer-based AI. Through the super apps, the companies in China, the AI labs, there's a focus on things like healthcare advice and financial advice. We're also starting to see a lot of video generation—AI video generation—particularly in short-form videos.

Speaker #1: And I think they are a fair way ahead of the US on the video generation side, or at least getting the applications out that are supported by these models.

Speaker #1: And then the third really big driver in what we're seeing in China is the international support required to assist Chinese technology companies that are heavily reliant on AI.

Ryan Kolln: The third really big driver in what we are seeing in China is the international support required to support Chinese technology companies that are heavily reliant on AI. You can think about social media companies, e-commerce companies. There is a really big driver for supporting their international ambitions.

Speaker #1: So, you can think about social media companies and e-commerce companies—there's a really big driver for supporting their international ambitions.

Speaker #4: Okay, great. And just a final comment there, just on margins. Obviously, that second quarter margin was very strong. Do you think that can continue?

Josh Kannourakis: Okay, great. And just final comment there just on margins. Obviously the Q2 margin was very strong.

Josh Kannourakis: Okay, great. And just final comment there just on margins. Obviously the Q2 margin was very strong. Do you think that can continue and how should we think about, I guess, the cost base versus margin perspective there in terms of what further expansion we could see across this year from China?

Josh Kannourakis: Do you think that can continue and how should we think about, I guess, the cost base versus margin perspective there in terms of what further expansion we could see across this year from China?

Speaker #4: And how should we think about, I guess, the cost base versus margin perspective there in terms of what further expansion we could see across this year from China?

Speaker #1: Yeah, we certainly expect that trend to continue, and we're seeing good operating leverage come out of the China business. That's a trend we expect to continue also.

Ryan Kolln: Yeah, we certainly expect that trend to continue and we are seeing good operating leverage come out of the China business and that is a trend we expect to continue also.

Speaker #4: Okay, great. Thanks very much. I appreciate it.

Josh Kannourakis: Okay, great. Thanks very much. Appreciate it.

Speaker #1: Thanks, Josh.

Ryan Kolln: Thanks, Josh.

Speaker #2: Thanks, Josh. Next question, sticking with China: Is your Chinese lab revenue recurring in nature—a valuation and data that's refreshed every model cycle—or are they one-off data set bills?

Sam Wells: Thanks, Josh. Next question, sticking with China. Is your Chinese lab revenue recurring in nature, evaluation and data that is refreshed every model cycle or one-off data set builds? And a follow-up to that, roughly how much of the USD 175 million run rate would repeat if customers shipped to new models next year?

Speaker #2: And a follow-up to that: Roughly how much of the $175 million run rate would repeat if customers shift to new models next year?

Speaker #1: Yeah, thanks, Sam. So, it is a mix of what we do. There is work that is directly related to the development of new models.

Ryan Kolln: Yeah, thanks, Sam. It is a mix of what we do. There is work that is directly related to the development of new models. There is a lot of work that we do, which is related to the evaluation of existing models, making sure that they are working in applications, et cetera. There is also a lot of work that we do that is very experimentive with the researchers that actually may never make it into a model. It is a difficult one to dissect because the needs at a project level change and vary on an ongoing basis. But I think, what we are seeing in both the Chinese and the US market, there is certainly no slowdown in the model advances and the model release cycles. If anything, it is speeding up.

Speaker #1: There's a lot of work that we do which is related to the evaluation of existing models, making sure that they're working in applications, etc.

Speaker #1: There's also a lot of work that we do that is very experimental with the researchers that actually may never make it into a model.

Speaker #1: So it's a difficult one to dissect because the needs at a project level change and vary on an ongoing basis. But I think what we're seeing in both the Chinese and US markets, there's certainly no slowdown in the model advances and the model release cycles; if anything, it's speeding up.

Speaker #1: So, I think the notion of, 'If China stopped building models, what would happen?'—there's not one that we're too worried about. We're very focused on supporting them as they evolve.

Ryan Kolln: I think the notion of if China stopped building models, what would happen is not one that we are too worried about. We are very focused on supporting them as they evolve into new models. But as I called out also, different applications, particularly on things like short-form video, robotics, speech, there is coding development. There is a very rich ecosystem of applications that sit on top of the existing models.

Speaker #1: Into new models, but as I called out also, different applications—particularly on things like short-form video, robotics, speech, and coding development. There's a very rich ecosystem of applications that sit on top of the existing models.

Speaker #2: Okay, great. Thank you. And just to follow up there, does anything built in China—like data sets, tooling, or capacity—get sold back to global customers, or do sovereignty and customer requirements keep the two segments commercially separate?

Sam Wells: Okay, great. Thank you. Just to follow up there, does anything built in China, like data sets, tooling, capacity, get sold back to global customers? Or does sovereignty and customer requirements keep the two segments commercially separate?

Speaker #1: It is largely separate, and the data export controls in China mean that there's no data being sold back to global customers.

Ryan Kolln: It is largely separate, the data export controls in China kind of mean that there's no data that's sold back into the global customers.

Speaker #2: Okay, great. Thank you. And switching to Appen Global, can you just elaborate on the board's long-term strategy for the global business? Will growth be primarily organic, or is there the ability for acquisition-led growth?

Sam Wells: Okay, great. Thank you. Switching to Appen Global. Can you just elaborate on the board's long-term strategy for the global business? Will growth be primarily organic or is there the ability for acquisition-led growth? If organic, which higher value services and initiatives will drive growth to improve gross margin?

Speaker #2: And if organic, which higher-value services and initiatives will drive growth to improve gross margin?

Speaker #1: Yeah, we're certainly focused on growth in Appen Global—profitable growth. We think there is a significant pathway and runway through organic growth in the business.

Ryan Kolln: Yeah, we're certainly focused on growth in Appen Global, profitable growth. We think there is a significant pathway and runway through organic growth in the business. So inorganic growth right now isn't a high priority for us. In terms of the services that we provide, it's continuing to work very closely with the AI labs to meet their needs. We called out in the presentation some of the ways that we're evolving, that is in kind of really close response and feedback to what we're hearing and getting requests for from the AI labs. So we will continue to evolve to meet the needs of the data for AI training, for AI evaluation, across LLMs and the future variants of AI models.

Speaker #1: So, inorganic growth right now isn't a high priority for us. And in terms of the services that we provide, it's continuing to work very closely with the AI labs to meet their needs.

Speaker #1: And we called out in the presentation some of the ways that we're evolving. That is in really close response and feedback to what we're hearing and the requests we're getting from the AI labs.

Speaker #1: So, we will continue to evolve to meet the needs of data for AI training and AI evaluation across LLMs and future variants of AI models.

Speaker #2: Great, thank you. And sticking with Appen Global—how deep and durable are Appen's relationships with core clients? Is Appen pursuing frontier AI companies, such as Anthropic?

Sam Wells: Great. Thank you. Sticking with Appen Global, how deep and durable are Appen's relationships with core clients? Is Appen pursuing frontier AI companies such as Anthropic? How does it convert pilots into recurring larger scale work?

Speaker #2: And how does it convert pilots into recurring, larger-scale work?

Speaker #1: Yeah, so our target customers are all of the leading AI labs. We work with a real majority of them today. There are a few that we’re targeting and making really good progress on to break into.

Ryan Kolln: Yeah, so our target customers are all of the leading AI labs. We work with a real majority of them today. There are a few that we are targeting and making really good progress on to break into. In terms of how we convert a pilot into a larger project, this is a very typical sales cycle where we come in and do a small piece of work and based off the ability to deliver really high quality at speed for that piece of work, building a trust with the researchers and then showing them our capabilities and the work we are doing across different clients.

Speaker #1: In terms of how we convert a pilot into a larger project, it is really, and this is a very typical sales cycle, where we come in and do a small piece of work.

Speaker #1: And based off the ability to deliver really high quality, at speed, for that piece of work, building a trust with the researchers, and then showing them our capabilities and the work we're doing across different clients—that confidence that we build, based off the project, based off what we're seeing elsewhere, and the conversations that we have and the way that we bring value to the AI labs—is the best way to get up that, we'll call it the revenue curve, as quickly as possible.

Ryan Kolln: That confidence that we build based off the project, based off what we are seeing elsewhere, and the conversation that we have and the way that we bring value to the AI labs is the best way to get up that, we will call it the revenue curve as quickly as possible.

Speaker #2: Got it. Thank you. Just a follow-up question from Josh at Baron Jolly. Josh, please unmute your line and go ahead.

Sam Wells: Got it. Thank you. Just a follow-up question from Josh at Barrenjoey. Josh, please unmute your line and go ahead.

Speaker #4: Great, thanks, Sam. Just a follow-up, guys, on the robotics side of things: there's been some interesting news this week. Figure 1, one of the big humanoid robot companies, has come out with a platform for building real-world training data.

Josh Kannourakis: Great. Thanks, Sam. Just to follow up, guys, on the robotics side of things, there's been some interesting

Josh Kannourakis: Great. Thanks, Sam. Just to follow up, guys, on the robotics side of things, there's been some interesting news this week. Figure, one of the big humanoid robot companies has come out with a platform for building real-world training data. I am just interested, obviously they are big, they are very well-funded, but what is the opportunity you guys see in robotics? If you think about the capability and the muscle you have had to build, are there any other options to create a specific sort of more white label product or a specific product for robotics that could be used by some of these humanoid companies, both in the US but also in China, which is obviously a huge focus?

Josh Kannourakis: news this week. Figure, one of the big humanoid robot companies

Josh Kannourakis: has come out with a platform for building real-world training data. I am just interested, obviously they are big, they are very well-funded, but what is the opportunity you guys see in robotics?

Speaker #4: And I mean, I'm just interested—obviously, they're big, they're very well-funded—but what's the opportunity you guys see in robotics? And if you think about the capability and the muscle you've had to build, are there any other options to create a specific, sort of more white-labeled product or a specific product for robotics that could be used by some of these humanoid companies, both in the US, but also in China, which is obviously a huge focus for the government there?

Josh Kannourakis: If you think about the capability and the muscle you have had to build, are there any other options to create a specific sort of more white label product or a specific product for robotics that could be used by some of these humanoid companies, both in the US but also in China, which is obviously a huge focus?

Ryan Kolln: Yeah

Josh Kannourakis: for the government there?

Speaker #1: Yeah, no, thanks, Josh. Good question. So, you can think about three sources of data that are needed to train, particularly the humanoid robotics, which are getting a lot of focus at the moment.

Ryan Kolln: Yeah. No, thanks, Josh. Good question. You can think about three sources of data that are needed to train, particularly the humanoid robotics, which are getting a lot of focus at the moment. One is what is called egocentric data collection, where data is being collected by humans who would typically have cameras strapped to their body, sometimes on the forehead, sometimes in different positions on the body. This is capturing what humans are doing in the real world around things like, anything that requires some type of physical manipulation, particularly with the hands and arms. That is a really big focus, and that is some of the data that Figure AI released was around these egocentric data sets. This part of the market is very interesting.

Speaker #1: So, one is what’s called egocentric data collection, where data is being collected by humans who typically have cameras strapped to their bodies, sometimes on the forehead, sometimes in different positions on the body.

Speaker #1: And this is capturing what humans are doing in the real world around things like anything that requires some type of physical manipulation, particularly with the hands and arms.

Speaker #1: That's a really big focus, and that's some of the data that Figure AI released, which was around these egocentric data sets. This part of the market is very interesting.

Ryan Kolln: It is a little bit of a commoditizing really quickly because there are many companies that are out there and going, collecting the data, et cetera. The second part of data needs are related to the annotation of that data. It is less about the annotation of what we saw with autonomous driving, which is putting a bounding box around all of the images. It is more assessing and filtering for quality standards, making sure that the instruction set matches the image, because there is really vast quantities of data. There are LLMs being run across it, but what we are finding is that there is demand for human involvement in the quality assessment of that data that is being captured. The third data source is more simulation-based, where it is getting humans to describe, in a simulated environment, the task that the robot should be completing as a way to provide the training data.

Speaker #1: It's a little bit of a commoditizing really quickly because there are many companies that are out there and going, collecting the data, et cetera.

Speaker #1: The second part of data needs are related to the annotation of that data. And it's less about the annotation like what we saw with autonomous driving, which is putting a bounding box around all of the images.

Speaker #1: It's more assessing and filtering for quality standards, making sure that the instruction set matches the image, because there are really vast quantities of data.

Speaker #1: There are LLMs being run across it, but what we're finding is that there is demand for human involvement in the quality assessment of that data that's being captured.

Speaker #1: The third data source is more simulation-based, where it's getting humans to describe, in a simulated environment, the tasks that the robots should be completing as a way to provide the training data.

Ryan Kolln: The third data source is more simulation-based, where it is getting humans to describe, in a simulated environment, the task that the robot should be completing as a way to provide the training data. There is one fourth bucket, which is related to teleoperations, which we do not really play in too much, but that is another interesting evolution of the market. It is like the LLM front, it is evolving very quickly, and the needs of the robotics builders are changing really quickly. We are trying to find the best place, as you say, Josh, that has got a durable and longstanding value add, but is also going to generate good margins for the business.

Speaker #1: There is one fourth bucket, which is related to teleoperations, which we don't really play into much, but that's another interesting evolution of the market.

Ryan Kolln: There is one fourth bucket, which is related to teleoperations, which we do not really play in too much, but that is another interesting evolution of the market. It is like the LLM front, it is evolving very quickly, and the needs of the robotics builders are changing really quickly. We are trying to find the best place, as you say, Josh, that has got a durable and longstanding value add, but is also going to generate good margins for the business.

Speaker #1: So it's like the LLM front—it's evolving very quickly, and the needs of the robotics builders are changing really quickly. We're trying to find the best place, as you say, Josh, that's got a durable and long-standing value add, but is also going to generate good margins for the business.

Speaker #4: Great. And just final one from me. Just in terms of obviously being quite a bit of movement and change in strategy from one of your potentially big social media customers out there, I know you had a fair bit of work from them towards the end of last year.

Josh Kannourakis: Great. Just a final one from me. Just in terms of, obviously being quite a bit of movement and change in strategy from one of your potentially big social media customers out there. I know you had a fair bit of work from them towards the end of last year. Have you seen any of those larger projects start to resume or get any signaling on when you expect some of those projects to resume?

Speaker #4: Have you seen any of those larger projects start to resume, or have you received any indication on when you expect some of those projects to resume?

Speaker #1: Yeah, so we're still, I mean, both communicating with all of our clients on their needs, and what we find is that these shifts can come very, very quickly.

Ryan Kolln: Yeah. We are still in close communication with all of our clients on their needs. What we find is that these shifts can come very, very quickly. There is a lot going on across all our clients. They are changing strategy really quickly, and we stay super close to meet their needs.

Speaker #1: So there's a lot going on across all our clients. They're changing strategy really quickly, and we stay super close to meet their needs.

Speaker #4: Got it. But yeah, not—hasn't sort of resumed some of those larger ones as of yet? Just more so a second-half story?

Josh Kannourakis: Got it. But yeah, hasn't sort of resumed some of those larger ones as of yet, just more so a H2 story.

Speaker #1: Yeah, look, there's always a traditional skew to the second half, so we're confident that we'll see that growth come through.

Ryan Kolln: Yeah. There is a traditional skew to the H2. We are confident that we will see that growth come through.

Speaker #4: Okay. Thanks, guys.

Josh Kannourakis: Okay. Thanks, guys.

Speaker #2: All right, thanks, Josh. Next question comes from Connor O'Prae. Can I call you Connor, please? Unmute your line and go ahead.

Sam Wells: Thanks, Josh. Next question comes from Conor O'Prey at Canaccord. Conor, please unmute your line and go ahead.

Speaker #3: Yep, hopefully I've managed the technology. Ran, a back to if we go back to the I guess if we go back a few years to the previous peak of the business, one of the defining characteristics was a heavy customer concentration, really around two customers.

Conor O'Prey: Yep. Hopefully, I've managed the technology. Ryan, a couple of questions. I guess if we go back a few years to the previous peak of the business, one of the defining characteristics was a heavy customer concentration, really around two customers driving a lot of the revenue growth. I'm wondering, and I think you and I were both, you were in the business, me observing the business from the outside, we're both around that. I'm wondering what, at that time, I wonder what lessons you're taking from that, especially in the China business, which is going through a similar analogous kind of growth path. Are you able to diversify the revenue across more customers to lessen those risks?

Speaker #3: Driving a lot of the revenue growth, and I'm wondering—and I think you and I were both in the business, observing the business from the outside.

Speaker #3: We're both around that, and I'm wondering—at that time—I wonder what lessons you're taking from that, especially in the China business, which is going through a sort of similar, analogous kind of growth path.

Speaker #3: Are you able to diversify the revenue across more customers to sort of lessen those risks?

Speaker #1: Yeah, Connor, it's certainly a focus for us. And I think the difference between what that period that you're explaining, whether it's kind of a couple of big customers that contribute a lot of their revenue—the China AI ecosystem—there are some very dominant players, but there's a decent number of them. But it's not a market skewed towards two big kind of customers like it was traditionally.

Ryan Kolln: Yeah, Conor, it's certainly a focus for us. I think the difference between that period that you're explaining, where there are a couple of big customers that contribute a lot of the revenue. The China AI ecosystem, there are some very dominant players, but there's a decent number of them that it's not market skewed towards two big kind of customers like it was traditionally. The focus for us is, we want to serve the big accounts for the best that we can. There's a huge amount of growth potential there. We also work with a really large number of customers in the China business. This covers the tier 1 labs, tier 2 labs, startups that are getting into the space. I'm less worried about that diversification risk that we had previously, vis-a-vis what's happening in China at the moment.

Speaker #1: So the focus for us is we want to serve the big accounts to the best that we can; there's a huge amount of growth potential there.

Speaker #1: We also work with a really large number of customers in the China business. This covers the tier-one labs, tier-two labs, and startups that are getting into the space.

Speaker #1: So, I'm less worried about that diversification risk that we had previously, vis-à-vis what's happening in China at the moment.

Speaker #3: Thanks. And then just back on Global, is it fair to characterize the revenue trends there as kind of the legacy business—the old, I guess we would call it, the Content Relevance piece—is that in a sort of structural decline?

Conor O'Prey: Thanks. Just back on Global, is it fair to characterize the revenue trends there as the kind of the legacy business deal? I guess we would call it the content relevance piece.

Conor O'Prey: Thanks. Just back on Global, is it fair to characterize the revenue trends there as the kind of the legacy business deal? I guess we would call it the content relevance piece. Is that in a sort of a structural decline? Is that a decline? How would you characterize that on one hand, and we're sort of seeing that possibly swamp all the other kind of good stuff that's going on? Or is it, I'm guessing it's more complicated than that, but maybe you can sort of break that apart a little bit for us.

Conor O'Prey: Is that in a sort of a structural decline? Is that a decline? How would you characterize that on one hand, and we're sort of seeing that possibly swamp all the other kind of good stuff that's going on? Or is it, I'm guessing it's more complicated than that, but maybe you can sort of break that apart a little bit for us.

Speaker #3: Is that a decline? How would you characterize that, on one hand? We're sort of seeing that possibly swamp all the other kind of good stuff that's going on, or is it—I'm guessing it's more complicated than that, but maybe you can sort of break that apart a little bit for us?

Speaker #1: So there’s certainly an element of that, Connor, where we’ve seen some of our more traditional work decline as LLMs are able to replicate some of that work.

Ryan Kolln: There's certainly an element of that, Conor, where we've seen some of our more traditional work decline as LLMs are able to replicate some of that work. What we have seen, particularly in the H1 of this year, some good stabilization across some of the vast majority of the work that we're doing. We are seeing the uptick in the newer areas related to LLM development. It is certainly a factor, what you're describing there, and quite accurate. We are, as you know, as we called out in the presentation, seeing the stabilization of some of the revenue from more of our traditional work.

Speaker #1: But what we have seen, particularly in the first half of this year, is some good stabilization across some of the vast majority of the work that we're doing.

Speaker #1: And we are seeing the uptick in the newer areas related to LLM development, so it is certainly a factor. What you're describing there is quite accurate.

Speaker #1: But we are, as we called out in the presentation, seeing the stabilization of some of the revenue from more of our traditional work.

Speaker #3: Thanks.

Conor O'Prey: Thanks.

Sam Wells: Great. Thanks, Conor. Next question. Just on cost out, you've identified 12 million in annualized cost efficiencies in Appen Global, with 70% to be executed by the end of Q4 this year. At what point does the incremental margin benefit of this program start to visibly flow through the P&L?

Speaker #2: Great, thanks, Connor. Next question, just on cost out. You've identified $12 million in annualized cost efficiencies in Appen Global, with 70% to be executed by the end of Q4 this year.

Speaker #2: At what point does the incremental margin benefit of this program start to visibly flow through the P&L?

Speaker #1: Yeah, Justin, I'll pass that one to you.

Ryan Kolln: Yeah. Justin, I will pass that one to you.

Speaker #4: Yeah, thanks. Thanks, Sam. So, there will be some benefit towards the end of the year, but it's not going to be material, given the way the timing works.

Justin Miles: Yeah. Thanks, Sam. There will be some benefit towards the end of the year, but it is not going to be material the way the timing works. I think there will be incremental benefits in H2, then in Q1 with the full benefit from the start of Q2 next year.

Speaker #4: So I think there'll be incremental benefits in the second half, then in Q1, with the full benefit from the start of Q2 next year.

Speaker #2: Great, thank you. And just a couple of final questions here. Is the Board considering acquisitions or other strategic transactions? If so, what capabilities or businesses would Appen specifically target?

Sam Wells: Great. Thank you. Just a couple of final questions here. Is the board considering acquisitions or other strategic transactions? If so, what capabilities or businesses would Appen specifically target?

Speaker #1: Yeah, like I called out, M&A isn't— we're very happy with the organic capabilities that we're building. The market's changing very quickly, and we need to be dynamic and responsive to the needs.

Ryan Kolln: Yeah, like I called out, M&A is not a. We are very happy with the organic capabilities that we are building. The market is changing very quickly, and we need to be dynamic and responsive to the needs. We are largely focused on organic growth in the business.

Speaker #1: So we're largely focused on organic growth in the business.

Speaker #2: Okay, thank you. And final question: As profitability and cash flow recover, would the board consider share buybacks, dividends, or other capital returns?

Sam Wells: Okay. Thank you. And final question. As profitability and cash flow recover, would the board consider share buybacks, dividends, or other capital returns?

Speaker #1: So, the board will closely look at the capital allocation and consider all options as we continue to improve the cash reserves in the business.

Ryan Kolln: The board will closely look at capital allocation and consider all options as we continue to improve the cash reserves in the business. That is certainly for consideration.

Speaker #1: So, yeah, that's certainly for consideration.

Speaker #2: Okay, thank you. That's all the time we have allocated for questions today. If you do have any follow-ups, please feel free to send them through to me via email, and we'll endeavor to get back to you.

Sam Wells: Okay. Thank you. That is all the time we have allocated for questions today. If you do have any follow-ups, please feel free to send them through to me via email, and we will endeavor to get back to you. And maybe with that, Ryan, I will just pass it back to you for any closing comments.

Speaker #2: And maybe with that, Ryan, I'll just pass it back to you for any closing comments.

Speaker #1: Yeah, thank you, everyone, for your time today, and thank you for your continued interest in supporting Appen. We continue to play a major role in the AI ecosystem.

Ryan Kolln: Yeah. Thank you everyone for your time today, and thank you for your continued interest and support in Appen. We continue to play a major role in the AI ecosystem. It is a very fast and rapidly evolving space, as I am sure you have a keen interest in. But Appen's role is, for over 30 years now, has been at the forefront of AI, and we look forward to continuing to supporting our customers, and delivering great financial results for our shareholders.

Speaker #1: It's a very fast and rapidly evolving space. As I'm sure many of you are keenly interested in, Appen's role, for over 30 years now, has been at the forefront of AI, and we look forward to continuing to support our customers and deliver great financial results for our shareholders.

Speaker #2: Great, thank you. Thanks very much for joining. That concludes Appen's first half FY26 results call. Enjoy the rest of your day. Thank you and goodbye.

Sam Wells: Great. Thank you. Thanks very much for joining. That concludes Appen's H1 FY26 results call. Enjoy the rest of your day. Thank you and goodbye.

Operator: Goodbye

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