Good day, and thank you for standing by. Welcome to the C3.ai third quarter fiscal year 2026 earnings call. At this time, all participants are in a listen-only mode. Please be advised that today's conference is being recorded. After the speaker's presentation, there will be a question-and-answer session. To ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. I would now like to hand the conference over to your speaker today, Amit Berry. Please stand by. The conference will resume momentarily. Good afternoon, and welcome to C3.ai's earnings call for the third quarter of fiscal year 2026, which ended on January 31st, 2026. My name is Amit Berry, and I lead Investor Relations at C3.ai. With me on the call today are Stephen Ehikian, Chief Executive Officer, and Hitesh Lath, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our third quarter results, which can be accessed through the investor relations section of our website at ir.c3.ai. This call is being webcast, and a replay will be available on our IR website following the conclusion of the 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. These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a further discussion of 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. During today's call, we will refer to certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP financial measures, to the extent reasonably available, is included in our press release. Finally, at times in our prepared remarks, in response 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. With that, let me turn the call over to Stephen. Thank you, Amit. Good afternoon, everyone. Our results this quarter were clearly inadequate and well below our objectives. We failed to close business as planned, and in particular, our performance in North America and Europe was disappointing. I came to this company two quarters ago after 12 years building AI companies, followed by a fascinating tenure leading a U.S. government agency, deploying AI and fighting fraud, waste, and abuse. I joined with the expectation that there is an opportunity for C3.ai to win in enterprise AI. Over the past six months, I spent nearly all of my time visiting customers, prospects, government agencies, partners, and our employees, and dealing with market participants and investors. What I consistently hear is that every CEO is making AI a top strategic priority, and they want to realize measurable economic value from it. That is exactly what our products deliver. It became clear to me that our cost structure was simply too high and we were not organized correctly for the opportunity. I have assessed the business with the management team, and we have built an exacting execution plan with 5 strategic initiatives. First, we are immediately rightsizing our cost structure and reducing our cash burn. Second, we are flattening our sales organization, realigning our strongest sales personnel with those sales leaders who are proven, who now report directly to me. Third, in product, we are focusing on those product areas where we have clear market leadership, a demonstrated track record of success, and where we deliver fast economic value to our customers. These include AI and automation across a business value chain, asset performance, supply chain optimization, and procurement for industries such as energy, manufacturing, healthcare, and public sector, including defense, intelligence, and government services. Fourth, we are focusing our sales motion to prioritize large-scale, enterprise-wide transformations with accelerated proof of value, with a concerted focus on bookings and RPO. Fifth, we are increasing the velocity of development and have fundamentally reengineered the way we design and deliver our product offerings. In the past five weeks, I have restructured products, engineering, sales, marketing, and customer services to leverage state-of-the-art agentic AI across these business entities to dramatically increase the productivity of our people, in many cases by up to 100 times. For example, in sales, we are leveraging agentic AI to generate customer-specific, product-specific, benefit-specific sales proposals at an order of magnitude faster and higher quality than previous pipeline generation technologies. In marketing, we are leveraging agentic AI to design, develop, and redeploy our website. This process previously took nine to 12 months and many millions of dollars. It will now take weeks. Additionally, in products and engineering, we are now leveraging agentic coding tools, including Cloud Code, to increase the productivity of our people and the quality of our platform, AI applications, and agentic AI workflows by up to two orders of magnitude. Considering these productivity enhancements, my management team and I have identified expense reductions of $135 million in non-GAAP operating expenses in the coming year. Headcount-related changes are $60 million, which represents approximately a 26% reduction in headcount. All workforce-related changes tied to this restructuring are now substantially complete, and we will continue to evaluate additional non-employee expense reductions as necessary to attain profitability. Yes, we have fewer people, but I'm expecting productivity of our business functions to increase multifold across the board. To be clear, these actions will not impact our ability to serve our customers. In fact, they will increase our ability to serve. We have taken a measured approach to ensure we preserve critical capabilities while substantially improving quality and speed of execution and value delivery. With a more agile company, we are empowering employees to execute with ownership and speed as we concentrate resources on our highest value strategic priorities. As we move forward, we'll be disciplined about taking additional costs out of the business across all functions by applying AI directly to our operations, including leveraging our own technology to automate work and simplify processes. I'm doing this in engineering, I'm doing this in marketing, I'm doing this in FP&A, in all aspects of the business. I've also implemented a series of targeted changes to increase velocity across the business. In sales, I have flattened the organization, with sales leadership now reporting directly to me. This change removes friction and increases accountability, allowing us to respond with greater speed to customers and more effectively align resources around market opportunities. My goal is to instill greater sales discipline, enforce rigorous upfront qualification, demonstrate proof of value quickly, and enable our teams to think bigger as they engage CXOs with a clear, value-driven narrative. Over the past six months, I've been deeply engaged in the federal business, and I've changed the way we operate. During this time, what I've seen firsthand is that demonstrating economic value early is a powerful accelerant. It quickly establishes trust, builds credibility, and shortens sales cycles. We are now applying the same approach across our commercial business. Our goal is to solve the highest value problems for the right customers. Accordingly, we are prioritizing large-scale, enterprise-wide transformation opportunities. To do this, we will rapidly demonstrate value through accelerated proofs of concept in IPDs. This is how we help the world's leading enterprises master AI at scale. We are concentrating on areas where we have demonstrable leadership, proving success, and the right to win, especially industrial asset performance, supply chain optimization, and generative AI. In R&D, I want to fundamentally reinvent how we build with C3.ai. We are investing in a platform to dramatically reduce the time from idea to deployment, enabling both our teams and our customers to build AI-driven systems more effectively. Ultimately, this allows the focus to shift from writing code to orchestrating, validating, and scaling AI-driven systems. To increase velocity immediately, we have increased focus on a smaller number of high-priority items while enforcing tighter ownership and higher execution standards. This restructuring is a strategic reset that we believe will make the company stronger, more focused, and allow us to win long term. Notwithstanding the challenges of the past quarter, there continues to be strong customer validation. We closed 44 agreements, including new and expansion agreements with the U.S. Department of Agriculture, the U.S. Department of Energy, the NATO Communications and Information Agency, the Royal Navy, GSK, Talos, ExxonMobil, U.S. Steel, C-SPAN, and McLaren, among others. We saw increased strong traction in the federal business. Total bookings across federal defense and aerospace increased by 134% year-over-year, accounting for 55% of total bookings. The federal opportunity is increasingly large and important. We are leaning into this market as demand accelerates for secure, commercial, off-the-shelf, enterprise-scale AI platforms designed to support mission-critical operations. This quarter, the U.S. Department of Agriculture selected C3.ai to deploy an enterprise-scale AI solution to modernize the department's intergovernmental and public engagements. By unifying its data environment with the C3 agentic AI platform, USDA is automating how large volumes of information are analyzed and processed, enabling inquiries to be handled faster and more consistently. This solution creates an AI-enabled decision platform designed to strengthen compliance oversight, improve real-time visibility, and enhance efficiency across key functions. At the same time, international demand for our solutions, originally developed for U.S. federal customers, continues to grow. During the quarter, the NATO Communications and Information Agency selected C3.ai to support logistics planning and operations across its 32 member states. Adoption is also expanding among allied defense organizations, including Japan's Ministry of Defense and the U.K. Royal Navy. In the commercial sector, we have extended our long-standing partnership under a new multi-year agreement with one of the world's largest E&P companies. This company has arguably built one of the largest and most successful enterprise AI reliability deployments in any industry. It is extending the C3.ai Reliability application and introducing agentic AI capabilities, with C3.ai agents acting as virtual subject matter experts that continuously identify issues, diagnose root causes, and initiate corrective actions to improve safety, reliability, and utilization in real time. At a European provider of subsea engineering and construction services for the offshore energy industry, we are applying C3 generative AI to automate complex engineering reporting, decreasing the time and effort from months and weeks to days. After a successful IPD, they're now scaling the solution across additional report types, cutting report production time from weeks to hours while improving accuracy and consistency. Overall, this quarter's results fell short, contain clear areas of strength, including strong federal, defense, and aerospace bookings, and continued expansion in leading global organizations. From a market perspective, the demand for enterprise AI is massive and rapidly accelerating. As AI CapEx approaches $500 billion, the focus is on demonstrating return on that investment. It is clear that the days of pilot purgatory are over, as organizations plan to roll out AI in full enterprise-scale production now. Honestly, people, the day we have been talking about over the last 15 years has arrived, we believe it's about 1,000 times bigger than we could have imagined. After six months in this role, and after speaking extensively with our customers, partners, and employees, what I've heard firsthand only strengthened my conviction. C3.ai is uniquely positioned to be a winner in enterprise AI. In a market crowded with fragmented point solutions and widespread stagnation of pilot programs, our differentiation is unmistakable. We operationalize AI at the core of the enterprise, unifying data across systems to deliver scalable, production-grade systems that drive measurable business outcomes. LLMs are extremely powerful, but they will not run your supply chain, manage your most valuable assets, or run contested logistics for the U.S. Navy. We have built a strong foundation and are equipped with all the assets required to win. The data fusion layer, the semantic layer, purpose-built AI workflows and applications, and human capital. These capabilities work together and enable customers to translate AI investments into tangible operational impact and economic value. This is not accidental. Tom had the foresight that enterprise AI would be a massive opportunity. Over 15 years, we've invested in building proven technology that now underpins mission-critical operations at many of the world's largest organizations. The opportunity ahead is clear. We are committed to capturing a greater share of the market. As I outlined in the beginning of my remarks, we have launched an execution plan centered on five strategic initiatives. First, to reduce the cost structure and reduce the burn. Second, restructure the sales organization. Third, concentrate efforts on fewer best-in-class applications. Fourth, prioritize large-scale, enterprise-wide transformations. Fifth, increase the velocity of how we design and deliver our product offerings. Most importantly, we are massively infusing our AI capabilities across all functions at C3.ai. This is now complete, and we are now moving forward. C3.ai is at an inflection point. We have made deliberate decisions to reposition the company with a long-term perspective. The work ahead will require discipline, urgency, and exceptional execution. I am counting on all of our employees for their focus, resilience, and commitment, and on our customers and partners for their continued trust. I've implemented a new cost structure, and I've implemented a path to non-GAAP profitability and a return to growth. We're moving forward with speed and enthusiasm, and I very much look forward to providing the report of our progress next quarter. Thank you. Now let me turn it over to Hitesh Lath to talk about the specifics of the quarter. Thank you, Stephen. I will share our financial results and provide additional color on our business. All figures are non-GAAP unless otherwise noted. Total revenue for the quarter was $53.3 million. Subscription revenue for the quarter was $48.2 million, representing 90% of total revenue. Professional services revenue was $5.1 million, of which $3.3 million was revenue from prioritized engineering services, or PES. Professional services represented 10% of total revenue during the quarter. Our subscription and PES revenue combined was $51.5 million and accounted for 97% of total revenue. Our bookings during the quarter were $46.9 million. Non-GAAP gross profit for the quarter was $19.6 million, and non-GAAP gross margin was 37%. Non-GAAP gross margin for professional services was 82%. Non-GAAP operating loss for the quarter was $63.4 million. Non-GAAP net loss for the quarter was $56.4 million and $0.40 per share. Free cash flow for the quarter was negative $56.2 million. We continue to be very well capitalized and close the quarter with $621.9 million in cash equivalents, and marketable securities. During the third quarter, we signed 14 IPDs, including five GenAI IPDs. At the end of the quarter, we had cumulatively signed 408 IPDs, of which 258 are still active. This means they are either in their original three to six-month term, or extended for some duration, or converted to ongoing subscription or consumption contract, or are currently being negotiated for conversion to ongoing subscription or consumption contract. As Stephen Ehikian said, in Q4, we launched a restructuring plan to materially improve our operating efficiency and position the company for long-term success. This plan includes expense reductions across our business to produce full-year cost savings of approximately $135 million. More importantly, it also reduces the annual cash burn by approximately the same amount. We expect to substantially complete the implementation of the plan by the second quarter of fiscal year 2027. Accordingly, the projected cost savings are expected to be fully realized starting the second half of fiscal year 2027. Included within our plan is reduction of our global workforce by about 26% or approximately 280 employees. This is comprised of headcount reduction of 25% in cost of revenue, 36% in sales and marketing, 25% in R&D, and 13% in G&A. This reduction in global workforce is substantially complete and will result in annualized cost savings of approximately $60 million. The plan also includes eliminating approximately $75 million from non-employee expenses, which we expect to fully realize starting the second half of fiscal year 2027. I'll move on to our guidance for Q4, fiscal year 2026. Our revenue guidance for Q4 of fiscal year 2026 is $48 million-$52 million. Our guidance for non-GAAP loss from operations for Q4 is $56 million-$64 million. Our revenue guidance for fiscal year 2026 is $246.7 million-$250.7 million. Our guidance for non-GAAP loss from operations for fiscal year 2026 is $219.5 million-$227.5 million. Our guidance for non-GAAP loss from operations for Q4 and fiscal year 2026 excludes pre-tax restructuring expenses of approximately $10 million-$12 million. With that, I'd like to turn the call over to the operator to begin the Q&A session. Operator? Thank you. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. One moment for questions. Our first question comes from Kingsley Crane with Canaccord Genuity. You may proceed. Hey, thanks for taking my questions. I think you closed eight GenAI agreements, five or six IPDs within that segment. That quantity is down a bit from, you know, a couple quarters ago. I guess just how would you characterize the quality of those IPDs and then just the total opportunity with those customers? Thanks. Yeah, in terms of IPDs, we have a much better qualification criteria in terms of our likelihood of generating enough economic value for the customer, as well as the likelihood of those IPDs converting to production contracts. We are being selective with the IPDs we sign up for, and we expect a higher likelihood of those converting to production contracts. Okay, thanks. Maybe this one be for Stephen. You know, given you're abstracting away AI complexity from customers, how are you evaluating models from various providers at various price points? Whether that's, you know, Opus 4.6 or Haiku or Gemini or Minimax, both from a functionality standpoint and then a cost structure standpoint, especially as it sounds like you're leaning in towards agentic coding at this point. Thanks. Yes, there's two questions as to what we're using internally and then what our customers are using. Maybe on the second point, we built our architecture, so it's model-agnostic, and it's really driven by the customer demands. Depending on the exact use case, and the capabilities, they can select which model they want to drive this. There's full flexibility. In terms of internally, we provide flexibility to our employees, just select the model that works best for them. We did this across engineering, you know, products, marketing, sales, and we've seen success across a wide swath of models today. Helpful. Thank you. Thank you. Our next question comes from Brian Essex with JP Morgan. You may proceed. Hi, good afternoon. Thank Thank you for taking the question. maybe start off one for Hitesh. 36% reduction in sales and marketing, pretty substantial. I would love to get some thoughts about, you know, how you approach that cost reduction, where those reductions kind of manifested within the organization, and, you know, what can we expect from a investment in growth versus cost efficiency mindset going forward? Yeah, sure. Our cost reduction, it covers all locations and all functions across the company. When we started on this exercise, we took a hard look at our cost by function and by location and identified opportunities where we could be more efficient. We also compared our cost structure with other comparable companies in the software industry, and that reinforced our view that the cost reduction had to be across the board. In terms of reduction in cost across sales and marketing and other areas, I provided some perspective on that from a headcount reduction standpoint. The reduction in sales and marketing is primarily coming from reduction in our sales force as well as marketing spend. Yeah, very helpful. Maybe, maybe for Stephen Ehikian, if you could frame out, how are your customer conversations changing with respect to adoption of the platform? Is this purely an AI conversation? Is it more of a cost management conversation? You know, maybe conversely, is it a revenue-generating conversation? Are there any other budgets? Are these AI-specific budgets, or are these primarily projects within specific verticals and specific operations that are turning to AI to make themselves more efficient? Would love to just get your kind of take on what you've heard so far. It's a great question. I think the market's moving extremely fast, so let me just highlight. I've been here six months and spent all that time on the road talking to our customers, our partners, even our employees, and I feel that conversation is changing in real time, where every CEO is looking to make an investment in AI, but they're tired, and I kinda highlighted the pilot purgatory. They don't wanna just test out AI for the purpose of testing it and doing it for six months. They wanna move today and adopt an AI platform, not for a single solution, but they're looking for a transformational change across the departments. Think of the customers we sell into, industrials, manufacturing, federal governments. These are areas where there's massive transformation happening, and it's to grow and drive revenue and really, really imagine the business. When I think of some of our leading companies, one of the largest biopharma companies in the world, they're talking about this. We're solving a supply chain for them, but they're talking about this as a zero back office supply chain, right? Where you have a human on the loop, there's more autonomy. You think about asset performance, and we have the idea of an autonomous site manager. This is a much bigger transformational story, which reflects the changes we're making in the organization to get started faster and be able to provide a roadmap to a large transformation change for our, for our customers today. I think those are the conversations. I think I've been impressed with the speed, and urgency to adopt, and move beyond one use case to many use cases. That's where we're seeing value today, and that's where I'm doubling down onto. Great. Very helpful call. Thank you both. Of course. Thank you. Our next question comes from Sanjit Singh with Morgan Stanley. You may proceed. Hey, guys. Thank you for taking my question. This is Oscar on for Sanjit. You know, thank you for... You know, we appreciate all the details around the operational restructuring and strategic initiatives. I wanted to maybe get a bit of color or insights into, you know, as we look at the, at the decline in the top line, sort of beg the question on the recurring nature of the business. So, I, you know, I wanted to understand more how much of the business today is recurring in nature versus, you know, one time. With that in mind, how should we think about, you know, guided visibility, particularly as we think about growth in fiscal year 2027? Thank you. Yeah, sure, Oscar. As you heard in my commentary, 90% of our revenue this quarter came from subscription, the remaining 10% came from professional services. As it relates to subscription revenue, there was no non-recurring subscription revenue in the quarter. Got it. Okay. Maybe as a follow-up, in terms of the performance in the quarter, you know, you noticed some, like, weakness in North America and Europe. Maybe some more detail on what particularly went wrong there? I would just say simply it was sales execution, full stop. We're gonna fix that. You know, as part of this, I mentioned we're gonna flatten the organization. I did this in the federal space in Q2 with the sales team reporting to me. We were able to drive faster execution there. I'm gonna take that same playbook and apply to North America and EMEA. I think sales execution, first and foremost, that falls on me, full stop. I own that, and I'm gonna fix that. Got it. Thank you very much, guys. Appreciate it. Thank you. I would now like to turn the call back over to Stephen for any closing remarks. Well, thank you all for joining us today and for your continued engagement. We appreciate your questions and look forward to updating you on our progress next quarter. Thank you. This concludes the conference. Thank you for your participation. You may now disconnect.