Q1 2024 C3.ai Inc Earnings Call
Okay.
Good day and thank you for standing by welcome to the C. Three Adi's first quarter fiscal year 2020 for a conference call. At this time all participants are in a listen only mode. After the speaker's presentation. There will be a question and answer session to ask a question. During this session you will need to press star one one on your telephone.
Please be advised that today's conference is being recorded I would now like to hand, the conference over to your speaker today amid Berry. Please go ahead.
Good afternoon, and welcome to <unk> earnings call for the first quarter of fiscal year, 'twenty, 'twenty, four which end.
On July 31st 2023, My name is Barry and I lead Investor Relations at <unk> with me on the call today is Tom Siebel, Chairman and Chief Executive Officer, and Evo Parkman Chief Financial Officer.
After the market closed today, we issued a press release with details regarding our first quarter results as well as a supplemental to waters out both of which can be accessed through the investor Relations section of our website at IR Dot Ctrip Dot AI.
This call is being webcast and a replay will be available on our IR website. Following the conclusion of this call.
During today's call, we will make statements related to our business that may be considered forward looking under federal Securities laws. These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date, we disclaim any obligation to update any forward looking statements or outlook.
Fans are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations for.
For a further discussion on the material risks and other important factors that could affect our actual results. Please refer to our filings with the SEC.
All figures will be discussed on a non-GAAP basis, unless otherwise noted.
Also during the course of today's call, we will refer to certain non-GAAP financial measures a reconciliation of GAAP to non-GAAP measures is included in our press release.
Finally at times in our prepared remarks and responses to your questions. We may discuss metrics that are incremental to our usual presentation to give greater insight into the dynamics of our business or our quarterly results. Please be advised that we may or may not continue to provide this additional detail in the future and with that let me turn the call over to Tom.
Thank you Matt Good afternoon, everyone and thank you for joining our call today.
We're off to a strong start for fiscal year 'twenty four.
Our revenue came in at the high end of our guidance exceeded analyst consensus and we're seeing significant traction across our business. This is the 11th consecutive quarter as a public company in which we have met or exceeded our revenue guidance.
Following the release of chat GPT in November of 2022, we're seeing a dramatic increase in demand for enterprise AI adoption in Q1, we experienced strong traction with our enterprise applications, and especially strong traction with C. Three generous AI.
Let's take a look at our revenue highlights for the first quarter total revenue for the quarter was $72 4 million coming at the high end of guidance.
It was 70 to $72 5 million and exceeding the analysts' consensus.
<unk> revenue for the quarter was $61 4 million constituting 85% of total revenue gross profit for the quarter was $45 million, representing a 56% gross margin.
non-GAAP gross profit for the quarter was $49 6 million, representing a 69% non-GAAP gross margin.
GAAP RP O.
$334 6 million current IP.
It was $176 million gap.
GAAP net loss net loss per share was <unk> 56.
non-GAAP net loss per share was nine SaaS, both exceeded analysts' consensus expectations.
Substantially.
We finished the quarter with $809 6 million in cash cash equivalents and investments exceeding the average analyst consensus of $774 3 million.
Net cash provided by operating activities was $3 9 million.
And free cash flow was negative.
$8 9 million significantly exceeding analysts' consensus that was.
We're going to have $38 7 million.
The market interest in applying enterprise AI to business processes appears to be expanding exponentially fueled by the interest in chat GPT and other consumer generative AI tools initially released in late.
Late last year.
Ceos business leaders military leaders and investors are all focused on how they can take advantage of these powerful new tools to improve operational processes.
In Q1.
We entered into new and expanded agreements with Saudi Arabia is smart city.
Nucor Steel company Roche.
Sugar producer Panther Leon in Central America Ball Corporation, Cargill Con, Ed Shell Tyson foods, and the US Department of defense.
Our partner ecosystem continues to expand in Q1, we closed 60% of our agreements with and through our partner network, including Google Cloud AWS, Microsoft and Booz Allen Hamilton.
A qualified partner opportunity has increased by over 100% in the past year and our qualified pipeline with our cloud providers grew by 61% from Q4 to Q1 Q4, 'twenty three to Q4 'twenty one.
She's here as federal business is showing significant strength federal bookings up 39% compared with the year ago quarter. The company continues to expand its first work with the U S Department of defense.
With new and expanded projects with a chief digital and AI office CBA O U S. Marine Corps U S Air Force that missile Defense Agency and the defense Counterintelligence Security Agency.
Ccs commercial customers, including shell, Georgia Pacific Coke Industries Bank of America.
And others and the U S Department of Defense continues to expand their C. III application footprint increasingly now, including <unk> generative AI, realizing outsized economic benefit from digital transformations using <unk> enterprise AI, let's talk about a few of these.
First the department of defense.
Our business relationships with the department of attaching our extensive and rapidly expanding.
The D O D C O three CRE AI platform and <unk> AI applications across many services components and combatant commands to realize significant improvement in readiness.
A decision advantage.
One example, beginning in 2017, we started work for the U S Air force to improve.
The readiness.
And applied predictive maintenance for the <unk> hundred <unk> century, and aircrafts that you probably know is the wax.
By fusing the handwritten maintenance notes with a flight logs and historical inventory.
Okay and.
And pilot logs.
<unk> readiness improved there.
The Air Force's legacy maintenance procedure substantially following this initial project.
The United States Air Force Rabbits, Sustainment office selected <unk> for additional readiness projects.
Actual residential projects called.
Ken can condition based maintenance plus CBS plus to apply similar analytic space predictive maintenance approaches to the B, one strategic bomber and other aircraft weapon systems.
This configuration of Ctrip readiness for the United States Air Force called the predictive analytics and decision assistant our Panda went live into production and has now scaled out to over.
16 Air Force.
Aircraft weapon systems.
This system Pandar with Samsung was selected as the system of record for all United States Air Force predictive maintenance applications.
This is the only system of record for an AI application in department of defense that we're aware of.
The goal of <unk> is to realize up to a 25% increase in overall aircraft mission capability.
And when rolled out to all aircraft in the United States Air Force.
This is budgeted to realize.
A $3 billion cost savings.
In maintenance and readiness.
Okay.
Talk for a minute about the.
<unk>.
The Department of Defense, Chief Digital and AI Office. This is the organization that is chartered with choosing it was lagging the AI platform of record for all Dod.
We began working with them less than a year ago.
Initially to bring with <unk> AI platform in production across.
A number of unclassified secret and top secret Enquires as part of <unk> advantage ecosystem, a centralized data provides the jewelry for the entire department of defense.
Our first project showed out nodal analysis in congested logistics can radically improve when AI systems are applied to the U S Transportation command, our trans Comdata.
This application took a simulation based approach to provide options in response to global logistics disruptions were able to accelerate the time. It takes to conduct this kind of notable analysis from days to minutes.
C. III AI has now been engaged less than a year later and a dozen projects through the seed through CDO CDA out including contested logistics.
Strategic force readiness.
Supply chain visibility.
Commanders dashboards.
And combined joint all domain command and control.
Let's take a look at shell shell has been an important customer since 2018.
The C. J applications are continuing to expand across the entire shell asset base, including upstream downstream integrated gas renewables and retail to address asset integrity optimization, ESG and predictive maintenance today.
Three.
Shell Cta I predictive maintenance program monitors almost 20000 pieces of equipment.
And because <unk> can identify failure in advance with very high levels of accuracy. This can both increase production and Pradesh and prevent potential disasters, such as offshore oil rubbed failures, the cost of which may be incalculable, the economic benefits for shelf is enormous.
And they have given presentations at bank of America, and other conferences, where they estimate it to be in excess of $2 billion per year.
In the past three months <unk> further expanded deployments applying AI based estimation techniques and subsurface reservoir management.
<unk> deployed a new <unk> based shallow oil condition monitoring application for its customers to reduce unplanned downtime and optimized maintenance of heavy duty assets and expanded Chelsea is.
Of the C III AI ESG solution.
Let's switch to Coke industries, we indicate we continue to expand our partnership with Koch, particularly at Georgia Pacific at foothills resources.
We generated we generate almost 4 million monthly predictions across 300 plus assets using our reliability.
And Ctrip AI supply chain applications.
Georgia Pacific is realizing up to 5% improvement in overall equipment effectiveness.
Coke also initiated two generative AI projects chop process data.
Documents and files.
Georgia Pacific is improving efficiency, and triaging and resolving equipment in production and maintenance issues to automate processes for paper manufacturing.
Black Hills resources is using C. III generative AI to increase efficiency and improve information access.
In commodity trading operations.
Okay.
The bank of America, or <unk> applications are deployed to deliver customer insights optimize business workflows and provide recommendations to liquidity product specialists and treasury sales officers liquidity team is responsible for managing the bank's cash flows every day.
Over 500 liquidity and sales users log in to the <unk> AI applications. The bank is applying AI AI.
AI based techniques to access client spots of this SaaS client responsiveness.
And sensitivity in a fluctuating interest rate environment.
Three applications are in production today at Bank of America, and others area developer all are expected to generate significant annual benefits.
Especially in a higher interest rate environment, where balance retention optimal pricing of interest rates and efficiency of sales and operations become important drivers of profitability and expense reduction.
Yeah.
Let's talk for a minute about.
<unk> generative AI, because ladies and gentlemen, this is big.
By combining the power of the tried and tested and proven Chichi AI platform that we've built in the course of the last 14 years with large language models.
<unk> been reading about every day.
Regenerative AI enables immediate interaction.
With the relevant and frequently man.
Massive corp of data documents and signals associated with enterprise demand for example machines factories systems supply chain natural phenomena biological systems and operating divisions, we use.
Natural language interface to rapidly locate retrieve and present relevant data across an entire enterprise information systems, allowing users to use the full power of AI to optimize productivity monitor system forecast demand and in general understand what is happening what will happen.
How to plan.
But how to maximize efficiency.
The production adoption and customer success since our initial March 2023, she three generative AI release has been immediate.
In the last quarter <unk> closed eight new agreements for <unk>, three generative III addressing new use cases across multiple industries, including agriculture consumer packaged goods defense intelligence manufacturing state local government oil and gas and utilities to date, we have closed 12.
Generative AI agreements and have a pipeline of more than 140 qualified generator.
C III generative AI enterprise opportunities over 140 to get out in less than six months.
So putting this in perspective, our qualified pipeline of generative AI sales opportunities exceeds that of <unk>.
Any other product hit on a product line that we've reduced that we've all.
Of all the products, we've released over the last 14 years.
This is big.
To meet market demand.
<unk> today announced the immediate availability of the new C. III generative AI suite, including 28, new domain specific generative AI solutions for industries business processes and enterprise systems.
G III generative AI provide fine tuned tailored domain specific degenerative AI solutions that mitigate the crippling problems that prevent the widespread industry adoption of <unk>. The market response to our generative AI offerings generative AI offerings is simpler.
Staggering.
We believe with the advent of generative AI may more than double the addressable immediately addressable market opportunity available to <unk> and now with our January <unk>.
Our suite of generative AI products out the door you can expect that will be an investment that we will be investing in the coming quarters to promote market and support these initiatives.
The 28 applications that we released today and are available today include our in three categories.
C III generative AI for industries. This includes generative and AI for aerospace for defense for financial services.
<unk> generative AI for healthcare intelligence manufacturing chassis regenerative AI for oil and gas for Tel Aviv communications or utilities.
Our family of products to address the requirements of business processes include C. III generative AI for customer service <unk> regenerative AI for energy management see three generative AI for ESG Cc generative AI for finance for human resources for process optimization.
For reliability and C. III generative AI for supply chain finally, we're releasing a family and importantly.
Okay sheath regenerative AI for enterprise systems.
Okay.
Ladies and gentlemen, this is that slide where that's being offered by software vendors. This is production software available to order today available to ship today and available to solve tomorrow and it will be live in 12 weeks. These products include seafood generative AI for database C. III generative AI for Microsoft dynamics <unk>.
Five CCA generative AI for Oracle ERP.
<unk> generated AI for Oracle and that suite C. III generative AI far pallet tier for our sales force for <unk>.
For our service now for a snowflake and C III generative AI for workday.
L. L. M support is immediately available in these products for Falcon 40 prefer for al.
40, <unk> Lama to plant five Zurich Gpt's, three five AWS AWS bedrock quad to Google Palm to open.
Open AI Gpt's viewpoint five M. P. M. P. T 70, additional support will be announced for leading allo Ams as the market developed by.
By combining the power of <unk>.
Yeah.
And generative AI.
With the tried and tested and proven <unk> AI platform, we believe C. III generative AI solves the traveling problems endemic to all other generative AI solutions currently being proposed in the marketplace. Firstly, the answers from Ctrip generative AI, our deterministic not random.
I mean every time you asked the same question do you get the same answer.
That's.
That's all answers are immediately traceable was one click to ground truth. So honestly the allo labs that you're playing with on chat GPT, Okay, Google bought or whatever you. They don't tell you where the answers come from.
They don't know where the answers coming from where C. III II. We can tell you. We gave you the link where you can go to ground truth no matter. What the question is how am I doing I guess right diversity goals in North America, Okay, which of my product lines are the least profitable.
By doing Thats, why how am I readiness levels out F 35 squadrons.
In Central Europe , how am I doing where are the gaps in my satellite coverage and then end up paying you'll forgive me the answer and I'd tell you that exactly where the answer came from.
With seasonally AI.
The Illinois.
Yes.
By combining.
The yellow lab and user utilizing all of the investment of the platform.
Our firewall from the data minimizing the risk of Hello, and cause data extra allocation see Samsung for details you've all read about it and closing.
The many.
Well all of them cost cyber attack vectors.
<unk> are now becoming evident there is a lot of research if you look at what's going on the research the Zika culture is doing.
Carnegie Mellon, you'll see that they're fighting really trouble like cyber security problems associated with the sale items that did not manifest themselves in the <unk> solution.
The <unk> platform, the <unk> generate AI solutions assures the enforcement of all enterprise access and cyber security controls in addition to providing and factor authentication and data encryption both in motion and at rest.
L. L. M reasoning is limited to enterprise one an enterprise license data in mitigating that potentially unbounded risks that you are now starting to reopen read about okay in the literature associated with IP liability.
Provided for most all of them.
Virtually unlimited IP liability associated with other solutions.
Because see three AI generative AI is not agnostic not not specifically dependent okay. We allow enterprise data.
Interchange Llm's that will taking advantage of the ongoing massive innovation that we're going to see <unk> coming in in the coming years and you can just switch went in and switch went out and they all the applications keep Ryan.
Finally, the way that <unk> structured yes.
Three generative AI is structured the fact that we have a firewall LLM from the data itself as we go along on this some of their time.
Basically almost eliminated any risk of a hallucination. So it doesn't basically does not elucidate if it doesn't know the answer comes back and says I don't know the answer I cant tell you the answer or the answer that I don't have access to the answer is that going to make up some line of creative pros, but you've all seen AAA.
Hello, I am so that you've played with the internet.
All three generative AI applications can be fully deployed within 12 weeks for $250000 and they are available today.
Yeah, right now actually on the AWS marketplace, the Google cloud marketplace, and the Azure marketplace. The license model the licensing model is straightforward.
<unk> supports the customer to bring its AI application in their production.
We do it in 12 weeks after that the customer continues to pay per the CPU or VC.
C G CPU hour with volume discounts.
But generally the AI market appears huge.
Bloomberg intelligence predicts this market will reach one three trillion by 2032 much of this will accrue to chip manufacturers cloud service providers and professional service providers.
Alex will accrue to January of AI applications.
If we double click on this generative applications box expected by Bloomberg Sebree H $280 billion in the same timeframe. We believe the bulk of this will accrue to providers of software that enables businesses to apply algorithms to improve business processes and associated decision.
<unk> now.
Now.
Countless startups today, a proposed <unk> companies based on generative AI for one Andrew sheet niche or another.
Okay.
Whether it big doctors' offices, or insurance or automotive or pharmaceutical companies or what have you, they're taking their pitches around the venture capitalists, all up and down in Silicon Valley and many are getting significant funding in some cases with private market valuations in billions of dollars and they're big idea in each case, a handful of farmer.
Okay.
A handful of entrepreneurs proposed to apply algorithms developed market specific business process specific and application specific analog solutions well.
Well <unk> offers these solutions today, and we offer them from a well capitalized company with almost 1000 seasoned professionals partnered with powerful.
Market partner ecosystem, and our global footprint the market opportunity appears enormous.
We have demonstrated in recent quarters that we have a solid management and expense controls in place.
In Q4 of last year, our cash flow operations from operations was a positive $27 million.
In Q1 of 'twenty four cash flow from operations was $3 9 million.
non-GAAP operating loss substantially beat market expectations in both.
Q4 of 'twenty three in Q1 of 'twenty. Four we finished Q1 up 24 with $809 6 million in cash and investments a decrease of $2 8 million from the prior quarter.
No.
After careful consideration with our leadership and our marketing partners. We have made the decision to invest in January of AI to invest in lead generation to invest in branding to invest in marketing awareness and to invest in market and customer success related to our January of AI solutions there Margaret.
Opportunity is immediate and we intend to seize it.
While we still expect to be cash positive in Q4.
This year and in.
Yeah.
Especially you're 25, we will be investing in our generative AI solutions at this time do not expect to be non-GAAP profitable in Q4 of 24, you can expect that we're still we want to see what actually happens in the market in the next couple of quarters of how this plays out but right now you can expect.
Yes.
We will update you on this as we know more but you can assume thats happened someplace, you that Q2 to Q4 timeframe of fiscal year 'twenty five.
Yes.
We have a tight rein on financial controls, we're operator disciplined business.
And we're making this decision to invest in generative AI because we are confident that is in the best interest of our shareholders.
<unk> was well ahead of its time predicting the scale of the opportunity in enterprise AI applications. When we began the market was nascent.
And as the market has developed and expanded we have expanded our branding and our marketing offers.
Marketing offerings to meet market expectations.
While we believe for over a decade that this market would be quite large.
Even we could.
Could not have anticipated this.
Size and growth rate of the AI market that we now address.
C. III has spent the last 14 years preparing for this opportunity and now the market is coming to US. Our technology Foundation has tried tested and proven we have a strong portfolio of enterprise applications in place, we have a pricing and distribution model meets the needs of the market.
We have a quality brand.
Strong partner ecosystem, and a long list of SaaS side customers, we're armed with a battalion, our professional services employees are professional employees deployed around the world our partner ecosystem with Google Cloud AWS Azure Booz Allen Baker, Hughes and others as well developed is expanding.
The company is well capitalized with a senior leadership team and now I'll turn it over to my colleague U haul Parker and our Chief Financial Officer will talk about.
More specific financial details associated with our performance last quarter.
Thank you Tom I will now provide a recap of our financial results and some color around the expected drivers of our financial results for the remainder of the year and walk you through our second quarter and full year fiscal 'twenty four guidance. Finally, I will conclude with some additional information related to the consumption based revenue model, we introduced a year ago.
All figures will be discussed on a non-GAAP basis, unless otherwise noted.
First quarter revenue increased 10, 8% year over year to $72 4 million subscription revenue was up seven 6% and represented 85% of total revenues.
We discussed last quarter, we expected professional services to be within our historical range of 10% to 20% with our actual professional services coming in at 15% of the mix.
Gross profit for the first quarter was $49 6 million and gross margin was 68, 6% I would like to remind everyone on the call that we expect short term pressure on our gross margin due to a higher mix of targets, which carry a higher cost of revenue during the pilot phase of our customer lifecycle.
We are pleased with our progress in managing expenses and our success in getting the entire employee base bought into a mission of managing our company with expense discipline. Our success in expense management is reflected in our first quarter operating loss of $20 7 million, which was better than our guidance of a loss of <unk> 25 to 30 million opt.
Tom mentioned, the generative AI opportunities. So massive we believe it is in the best interest of our company and for shareholders together, it's our first mover advantage to seize the market opportunity by making incremental investments in sales marketing and customer success.
As a result, we are revising our 2024 expense guidance to reflect these investments I will provide details when I discuss guidance.
Turning to our bookings.
Reported GAAP <unk> of $334 6 million, which is down 27% from last year. This was expected as we transition to consumption based agreements.
GAAP <unk> was $170 6 million, which is down one 7% from last year.
We continue to see positive trends diversifying our project bookings with Q1 pilots representing eight industry sectors, turning to cash flow operating cash flow was $3 9 million in the quarter and free cash flow was a negative $8 9 million, reflecting expenses related to the build out of our new corporate headquarters we closed the quarter.
With a strong balance sheet with $809 6 million of cash cash equivalents and investments.
Total cash and investments balance was decreased by only $2 8 million from last quarter, we continue to be very well capitalized.
Our accounts receivables are in good shape with $122 6 million at the end of Q1 compared to $134 6 million to go after quarter total allowance for bad debt remains low at 359000, and we have no concerns regarding collections.
It relates to a consumption business model I would like to provide two key upticks.
We previously told you that we are assuming a 70% conversion great a pilot phase engagement to production phase at <unk>.
And we have signed a total of 73 pilots 70 of these are active meaning that they were either convert it in the original six month term extended for one to two months or are currently negotiating for a production license.
Second regarding consumption data or actual V. CPU consumption from the last three quarters is slightly higher than our original estimates.
Finally, our customer engagement increased to 334 from 287 in Q4 23.
Now turning to guidance.
We're guiding Q2 revenue to a range of 72 million to $76 5 million, we expect our non-GAAP loss from operations to range from negative 27 million to negative $40 million.
As mentioned before degenerative AI opportunity is so massive that we have decided to invest for success.
As a result, we expect to cross the non-GAAP profitability in the course of FY 'twenty five we will provide more updates on this in future calls.
Right.
We expect to be cash flow positive for Q4, 24, and the full fiscal year FY 'twenty five.
For full year FY 'twenty four we are maintaining our previous guidance for revenue in the range of $295 million to $320 million and increasing the non-GAAP loss from operations to a range between negative $70 million and negative 100 gig.
I would now like to turn the call over to the operator to begin the Q&A session.
Okay.
Thank you.
As a reminder to ask a question you will need to press star one on your telephone please stand by while we compile the Q&A roster.
Okay.
Yeah.
Our first question comes from Patrick Wall Ravens with JMP Securities You May proceed.
Oh, great. Thank you very much.
So it's great to hear about the the demand levels in all of the activity. Tom can you talk a little bit about how the.
The linearity in the quarter, how that was and how things close out.
At your Investor event.
You told US that you had closed 16 agreements.
We ended up with.
But if you look back a quarter you had 10 at the middle and he ended up with 43.
So it makes it seem like maybe the second half it wasn't quite as good as you would hope, but I don't know, maybe maybe I'm interpreting that wrong.
Or maybe in the first half was great.
Alright, okay.
Well, let's talk about half glass full model.
I would say that if the.
Uh huh.
This might have been.
Best quarter ever in terms of linearity I am not sure. Okay in terms of being in terms of predictability.
No.
Without getting too specific I would say.
You mean.
The business volume in the course of the quarter was activity in the course of the quarter was quite consistent.
Okay.
And then if we multiply the the average TCE times the number of deals right. Then we get a total TCE number.
I mean, you guys are the only ones who disclose it. So thank you for that transparency and if you look at that that was around $26 million this quarter.
You know in the last quarter again was.
Two almost twice as much so I just want to make sure we understand what's going on here is the TCT not a good.
Indication of Hello, how are you.
During the quarter.
Well, we used to compensate people on <unk> and that's back when we used to be 10, 20, $30 $40 $50 million deals Pat and now we're doing.
$250000.
Our projects in January of AI, and $5 million projects in.
For the balance of our enterprise products.
The general Air products last 12 weeks. The other pilots last project last generally last up to six months generally six months. So it's a consequence.
Sure.
<unk>.
It follows directly that.
TCE goes down.
P O goes down.
And by the way at gross margins go down in the short run.
Because gross margin when you when we're doing these generative AI pilots for a quarter of a million dollars wherever it may be I mean.
There is no way, we are not going to succeed at any cost, let's say on the first 50 of these guys.
And if we have to over invest to make that pilot successful we're going to do it.
So okay.
Hey, guys. So I am not certain that IPO is meaningful going forward.
I'm not certain <unk> I've been trying to drive that down as you are well aware for.
Well 15, 20 quarters 20 quarters ago, our <unk> was about $15 million average contract with I guess about $15 million and now average contract value I think it's less than a $1 million or 800, okay.
So that that.
This is a good thing.
Okay, Great and then lastly, you have probably for you.
You have a footnote on the balance sheet, where there's a related party, presumably Baker Hughes, but.
Still has about $75 million you saw a $75 million in accounts receivable from them. That's the same as last quarter.
Are you guys, okay with that.
It's a lot bigger than 75 total.
Yes.
Okay.
I'm not sure how to interpret your question and we have no collection concerns from.
Any of our customers our bad debt reserve is only up 359000, and all of our customers are paying on time and enforced so no concerns there.
Okay. Thank you.
Thank you.
One moment for questions.
Our next question comes from Mike <unk> with Needham You May proceed.
Hey, I appreciate the new pronunciation on the last name.
Thanks for taking my questions here guys.
A couple of questions first on the guidance and I appreciate this.
With pivot and you guys are trying to take advantage of this opportunity where it really feels like the <unk>.
Come online right.
My question is more around the guidance, if you will and where I'm going with this is given the increase that we're talking to and the go to market investments, which is obviously acting as a drag on your your operating losses no question about it but why aren't we seeing some sort of benefit when looking at the fiscal 'twenty four revenues why maintain that.
Guidance as we sit here today.
Mike.
Mike.
I think we've been doing the best we could do since we've been a public company to be credible in setting expectations and we have met or exceeded expectations. In every quarter that we've been a public company. Okay. Now we are in uncharted territory still with the consumption pricing model and we're definitely.
Unchartered territory with.
With.
Generative AI, Okay now, let's take this I were to take the sum of all the spreadsheets of all of our product groups and our business plans and you can be sure that they comp to a larger larger number than we've talked about in guidance. Okay.
We were the opposition as we filled with the guidance with a comfortable that with the guidance that's out there today, okay and.
At the same time.
Do you feel comfortable that after a couple of quarters of acceleration where to be able to look you straight in the eye and say well gosh.
So we're planning on significantly accelerated growth, but I don't want to do it prematurely I don't want to lose credibility and I think this is a responsible thing to do.
Alright, Thank you for asking that I appreciate that and I guess, another one and totally understand the commentary on the on our appeal and even see our apio declining I guess, it's more for you here, but.
With the transition to the consumption model.
Should we be.
Seeing <unk> remained more resilient to these consumption pilot starts to convert.
Or or consumption pilots, even when they move to production not necessarily going to be showing up in <unk> can you can you provide any more color on that please yeah, yeah, absolutely. So effectively the <unk> is flat right the way the consumption.
Based model works is that we start with a pilot phase that higher amount.
Amount would be <unk> in the given quarter that we signed that deal the consumption face on the rest of the customer were to sign up for volume discounts is never going to be an <unk> because it's going to be after consumed invoicing, so you'll only see ever that in revenue.
Or 100% consumption model IPO would be zero that is exactly right.
Okay and the expectation is that most of these customers we would not be signing up for those larger volume commitments. So that is going to be unexpected drag on the <unk> appeal then.
Yes, yes, yes, okay, alright, thank you for that and Thats why it makes it easier to buy rather than saying 10, 2030 40 50.
I think one deal we did was to have 1 billion, if I'm not mistaken okay.
Well 300 million plus a perfect.
They were saying Hey, it's add $1 million, if you like it keep it okay and.
So after they pay their half a million dollars if it goes that way there's no our appeal that's right.
Got it got it and maybe just one more if I could.
Apologies to be taken all the time here, but I did just wanted to circle up I know that you guys are talking about the C. Three generative AI pilots being $250000 12 weeks.
And the remaining product lines I believe and correct me if I'm wrong, but you have typically about six months for those pilots.
Could you help us think through.
Is it just the time to value on these gen. AI pilots is so much quicker that you would think that would be customers convert that much faster.
It is quicker Mike in one case, we might have to add all load all of the data model of supply chain and build machine learning models.
The that fit the scale of the enterprise as a cargill, which is roughly $100 billion business or.
The United States Air Force, which is a pretty big business, Okay, regenerative AI and yes, okay. We just lowered their data okay into a deep learning model, Okay, and it kind of takes the lion share of those data stores at a vectra score and we're kind of where the masters of the universe at aggregating structured data and <unk> data sets.
Our data enterprise data images, what have you into unified Federated Amish got it we have 14 years of that we're really good at that okay. So thats easy Okay and then okay.
All the map English I worked out by one deep learning model gave their stored in Investor day, our store and then the so we don't have these huge data science projects that we have at all of these other these other organizations. So yes. The time to value is is is <unk>.
After the implementation effort is easier and it's technically.
Honestly, it's an order of magnitude easier problem.
Thank you very much guys I appreciate there's nobody who doesn't want to talk about it.
Great to hear thank you guys.
Thank you one moment for questions.
Our next question comes from <unk> <unk> with Canaccord Genuity you May proceed.
Hi, Thanks for taking the question congrats on the result, it sounds like your plan is to invest more in Legion branding market awareness customer success.
Mentioned that you have more than 140 qualified leads and <unk>. It seems like you've done tremendously well and generating leads.
We think about the incremental change to the profit guidance are you balancing investments between customer success pilot conversion without a lead gen and brand awareness.
I'm sorry, what was the.
How we're balancing between customer succession lead gen. Okay. A lot of this is branding and Lee Chen.
So it is what it is what we're looking at okay kind of like we used to do in 202021, when we establish the brand for enterprise AI that worked out pretty well and we're going to plant a flag.
No.
On this January today, our market and we're going to work.
We're first to market.
Many companies out there have a 28 enterprise Saturday of AI solutions in the World I know, how many exactly one.
And we're going to communicate that we're going to make it available. So that's what the bulk of it is at the same time, if we have a customer in any one of these markets, where we need to throw an extra resource to make them successful with their pilot you can be sure we're going to make a success of what their project.
And as soon as we get down the learning curve will get increasingly efficient at it okay and gross margins go up.
Okay. Thanks, Tom that many product lines and so if I could ask one more.
Hoping you can give some clarity on the 28 specific generic solution. So for example, if youre in oil and gas customer you're building a solution sale and this is ultimately linked to the sales force is that requiring three separate absolute how would that be right.
Yes, that'll be one basically it's price per CPU.
I mean that looks like it's going to be on a judgment basis, whether they are discrete projects or whether it's a whether the union announced them as one generative I application, whereas you've described it the Indian Alabama is one generative I application it will be a quarter of million dollars to bring alive in 12 weeks and after that that <unk> 35 per <unk>.
<unk> or <unk>.
Okay very helpful keep up the good work. Thank you.
And as it relates to when it gets a run time pricing it doesn't really matter, whether its one application or whether it's three it's going to be the same amount of run time.
Yes.
Thank you.
Thank you one moment for questions.
Yeah.
Our next question comes from pendulum borrow at JP Morgan you May proceed.
Hey, guys. This is <unk> on for proposal and thanks for taking my questions.
So on the semi pilots that are interactive at the moment.
We exclude the pilots that have been.
And then one or two months is there any way to parse out how many of these pilots are under the microscope.
And I have a quick follow up.
I think thanks Noah for the question. So I think at this point the way the way. We are looking at is that there were 73 pilot deals that we've been doing 70 are either converted or in the process of the pilot or we're negotiating a production license Santos I think the meaningful amount or mean.
<unk> message you should take from this that at a 73 pilots. We only have three notes. So we have a pretty we feel very comfortable I'm very bullish about how that pilot program is currently progressing.
Understood and then maybe just to double click on the gross margins I know you commented that.
Thank you.
Let me, let me comment on the nose no. It wasn't that the pilot wasn't successful okay. The no go because I know these <unk>.
Exactly what they are okay, and they were hugely successful and say well what happened is the genius.
Oh, Okay. It went to the CEO would say Oh, we're going to build this ourselves out of a bunch of Tinker toys. So let him go do that okay. He's going to go do that for about two years, they're not going to be able to their cyber security problems IP infringement problems theyre going to have.
They're going to have data extra location problems, they're gonna have random answers and they'll be back.
So the sales cycle, there was just a little bit longer than we thought.
They are not large but it just lost they are just suspended.
Sorry.
No no no I appreciate that I appreciate the clarity.
And just a quick follow up on the gross margin just any way to kind of help us with our.
Model going forward in terms of how to think about gross margin.
You laid out some commentary about this quarter's impact, but just any additional thoughts there would be helpful for the year.
I think the punch line is that we're still expecting some margin pressure on it and there's going to be more pilots, it's going to be margin pressure until the consumption becomes a more dominant portion of the revenue stream, which would then offset it and start picking up that the margin. So.
Continue to expect some some pressures through onto gross margin.
Yes.
Thank you.
One moment for our next question.
Our next question comes from Sanjay Singh with Morgan Stanley You May proceed.
Alright, Thank you for taking the questions I had one for Tom and one for you.
And what's the vision around sort of multimodal theres a lot of.
Interest around the language models, but do you think about the different distribution models video audio image.
What's the what's the vision around supporting those types of models.
<unk> multi modal becomes the <unk>.
Dominant deployment architecture for our for enterprise.
Yes.
Are you talking about data Sanjay.
No no no.
Certainly I understand the question Yeah, Yeah, what I was referring to is like obviously like the GPT models or language models and they've taken the world by storm, but there are other.
Other AI models that deal with image audio video with other sources of data as we think.
On the.
Large language models tend to be almost exclusively limited to okay text HTML and code.
So other sorts of data.
They don't know how to ingest okay now.
Okay. Good good Okay now we so let's talk about this we are the masters of the universe and ingesting what do you call multimodal data images, okay images from space trajectories of hypersonic high speed telemetry trading volume.
The rate at which electrons are going across the grid.
Enterprise data.
Pre tax and so where we're using our standard architecture to ingest those data. Okay. We're using one of our standard deep learning models to basically parse show this data and store all the relationships and a vector data store. Okay. All the large language model, we're using four is interacting.
With you in my.
To handle the the natural language to understand what we're saying and it takes the answer back from the data and give it to us.
And in pros, okay, rather than some gibberish that might be spirit out of SAP.
Right now I mean, they make.
Makes perfect sense.
That is one of the reasons why people find our generative isolation attractive as we're I mean, we're tried tested and proven at ingesting any kind of data that they could think of.
Understood.
Understood and then the question for Julian.
Looked at the presentation that we sort of look at where we are in in the sort of transition phase one phase two it sounds like we've just started sort of phase two and the glass sort of implies that we're you know we'll start.
But to get to revenue neutral by seven quarters in we're about four quarters in and then revenue accretive about eight quarters.
Quarter since about three or four quarters away is that still the timeline, we should be thinking about in terms of.
Revenue acceleration any any color around that would be it would be hugely helpful.
So Sanjay the chart you're looking at I think you should think about this as a kind of a per customer basis, right, but it's not necessarily the entirety of how our business is growing but the idea is that.
We now have some of the regional early pilots from last year's Q2, and Q3 Theyre starting into phase II.
Phase II category and as I mentioned on my prepared remarks, we have preliminary data on ax will be CPU consumption.
For the first three quarters, and it's slightly above what we've modeled before so so we are in this fourth quarter.
Of of the transition and we are starting to see some very positive indicators with respect to how the consumption.
We'll run for these consumption based deals.
Got it. Thank you I appreciate the context. Thank you.
Thank you.
Thank you and we have time for one final question.
Our final question comes from Michael <unk> with Keybanc capital markets. You May proceed.
Hey, Thanks for taking the question this is Eric.
Michael So I wanted to ask on banker views.
Part question just wondering if you can give us some color on what changed with that relationship that Theyre no longer consider Atlanta Party.
And then secondly on I hope this isn't too nuanced, but.
If I take the $16 $5 million of bigger revenue contribution for two months in the quarter kind.
Kind of extrapolate that out for an additional month I got about $24 million.
Alright, thank you around $20 million. So I guess my question is how does the banker Hughes contribution in the quarter compared to expectations in any way to understand how the nonbanks.
Relative to your guidance.
Well first of all Baker Hughes.
It's not a related party because they monetize some of their stock remember they bought some <unk> some time ago for about three bucks and they sell it for I forget what the restaurant for a while I think it would be off by a buck or two I don't know, but for nothing okay and they sold it for a lot. So it's a pretty darn good trade, okay, and today, because they own less than <unk>.
For less than 5% by definition, they're no longer a related party.
As it relates to the Baker Hughes revenue he should actually know that haven't didn't we didn't we provided that in the memo. So so in other words that we wrote like three quarters ago, That's right I mean, it's.
It's.
I'm, sorry, I forgot to ask the question.
What was your name.
Hey, Tom.
Keybanc.
Okay.
Actually it's on our website.
So you're going to be able to see what.
What the minimum bakery as revenue as it is.
We provided you that in great detail and it's on the IR site.
Any way to just kind of quickly frame.
How it was in the quarter relative to your expectations for contribution sorry, if some of them have progressed.
What would you expect that that's right exactly.
Exactly.
Alright, thank you.
Thank you.
I guess that was our last question.
Ladies and gentlemen.
So Tom and Euro are out. Thank you for your time. Thank you for your attention and we look forward to.
If you are providing an update at the end of our second quarter. So thanks, a lot stay tuned.
And hopefully we'll have some exciting things to report.
Thank you. This concludes today's conference call. Thank you for participating you may now disconnect.
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