Zapata Quantum Inc

Good day and welcome to Zapata Computing Holdings Incorporated Second Quarter 2024 Financial Results and Business Update Conference Call. As a reminder, this conference is being recorded. It is now my pleasure to introduce your host, Eduardo Royas. Thank you, Mr. Royas. You may begin.

Thank you, Kat. On today's call are Christopher Savoy, Chief Executive Officer and Co-Founder Sumit Kapoor, Chief Financial Officer, and John Zorio, Chief Revenue Officer of Zapata AI. Earlier today, Zapata AI issued a press release announcing its second quarter 2024 results. Following prepared remarks, we will open up the call for questions. Before we begin, I'd like to remind you that this call may contain forward-looking statements. While these forward-looking statements reflect Zapata AI's best current judgment, they are subject to risks and uncertainties that could cause actual results to differ materially from those implied by these forward-looking statements. These risk factors are discussed in Zapata AI's filings with the SEC and in the release issue this morning, which are available in the investor section of the company's website. Zapata AI undertakes no obligation to revise or update any forward-looking statements to reflect future events or circumstances except as required by law. With that, I would now like to turn the call over to Christopher Savoy, CEO and co-founder of Zapata AI. Christopher?

Thank you, Eduardo, and good day to all. We saw strong momentum across various fronts during the second quarter of 2024. As you'll hear more about during this call, this is evidenced by the step up in revenues and gross margins versus Q1 2024 and the year ago quarter. The expansion of existing and the formation of new strategic partnerships and the healthy growth we saw in our qualified pipeline of prospective customers, which today stands at more than $30 million. Before elaborating on these highlights, we think it is critical to touch on the bigger picture, and most importantly, how Zapata AI is carving out a compelling niche in the industrial AI marketplace. Understanding of generative AI, its applicability, its practicality, and the business model and economics behind it is evolving daily. Enterprise users of this technology are coming to appreciate that there can be different horses for different courses. Let me elaborate. As disclosed in a report published by a prominent investment banker earlier this summer, generative AI can be very expensive. As noted in the report, the tech sector is poised to spend more than $1 trillion with a T on generative AI CapEx in the coming years. Similarly, a leading venture capital firm evaluated AI investments and calculated that the entire industry needs to make $600 billion annually to break even on its initial expenditures. The root of these high dollar figures is technology centered around large language models or LLMs. There is in our mind, no doubt, a large market for LLMs, but LLMs are not a be all end all when it comes to generative AI and industrial AI. At Zapata AI, we firmly believe that the value of generative AI is not going to come exclusively from a one large model that rules the world approach. Rather, there is a vast market for an approach to AI for enterprises and customers that is based on ensembles of highly tailored, highly specific, and relatively small models. This is the approach we have been taking at Zipod AI from day one. LLMs are limited in their ability to solve truly complex business problems, especially those involving the handling of structured numeric or time series data. But large enterprises in the Fortune 500 have mission-critical use cases which involve numbers and time series data, not only text. Small, precise models can tackle these deficiencies, and Zapata helps businesses build and optimize these specialized models to reduce costs and increase revenue. Further, our small ensemble model approach allows us to address high CapEx hurdles for training and deploying AI. Our quantum-informed mathematical models are incredibly efficient and do not require vast amounts of compute, unlike traditional LLMs. As we've all now seen, compute can be extremely expensive and are largely inaccessible given the limited chip supply. Further, the energy models needed to require the power of these compute-intensive LLMs are significant. Lastly, as you've heard from me before, but it bears repeating, we build applications using our customers' data on our SOAR Orchestra platform, our software platform, which can be deployed on any customer's cloud in their own secure environment, including on the edge. This is key to avoiding vendor lock, which we've been hearing from customers as a major concern, while removing data governance, security, and privacy concerns. Our leadership team, global business development staff, and world-class engineers are out there speaking with prospective customers every day delivering this message, and we routinely see the proverbial light bulbs going off. Over the past several months, and especially in the few months since we closed our acquisition with Andretti Acquisition Corp., we have seen increased interest on how we can deliver value to customers with our small model ensemble approach. The BD and sales discussions we are having in many instances with very, very large organizations in the Fortune 250 are the mainstay of what we're doing. Relationship building and decision-making are time-intensive processes that involve alignment across multiple facets of an organization. We remain incredibly optimistic that these conversations will continue through the typical sales conversion cycle and that we will convert several of these exciting opportunities into commercial agreements as we get deeper into the second half of this year and beyond. Once we are in with a customer, the relationships we have established are incredibly sticky, and the opportunities to diversify and scale within an organization are tremendous. This is well evidenced by how we've expanded our partnership with Andretti Global and AI by expanding use cases beyond race strategy and into digital transformation and operational optimization. Same goes for our DARPA relationship, which goes back to 2022 and which has expanded over time. As we look forward, we are optimistic about further scaling up and expanding revenue per account with our existing customer base. Against this backdrop, I would like now to introduce Sumit Kapoor, our CFO. At the time of our last call in mid-May, as you may know, Sumit was just coming on board. After a few months in the seat, he is well positioned to talk in more detail about the process and platform that we have. In essence, how we bring our customers up to speed on our compelling value proposition. Sumit.