Corvex (MOVE) Q1 2026 Earnings Transcript

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DATE

Tuesday, May 19, 2026 at 4:30 p.m. ET

CALL PARTICIPANTS

• Chief Executive Officer — Jay Crystal
• Co-Founder and Director — Seth Demsey
• Investor Relations Lead — Jeremy Cogan

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TAKEAWAYS

• Merger and Corporate Actions -- Corvex (NASDAQ:MOVE) completed the acquisition of Corvex Legacy Holdings, Inc. on March 19, 2026, changed its name to Corvex, and issued Series B, C, and D convertible preferred stock as part of the transaction.
• Reported Revenue -- $510,000 for the quarter, which includes legacy healthcare business results for the full quarter and only 12 days of Corvex's AI platform contributions.
• Pro Forma Revenue -- $3.65 million for the quarter, assuming Corvex AI platform results included for the entire period, with nearly all revenue generated by the AI platform.
• Operating Loss -- $4.8 million operating loss on the reported basis for the quarter.
• Adjusted Pro Forma EBITDA -- Loss of $933,000 for the quarter, excluding depreciation, stock compensation, interest expense, taxes, and merger costs.
• Total Assets -- $604 million as of March 31, 2026, with cash exceeding $29 million.
• Share Conversions -- Each Series B preferred share automatically converted into 1,000 shares of common stock on March 31, 2026; Series C and D shares are pending or eligible for conversion pending shareholder approval.
• Stock Dividend -- A stock dividend of 0.358 shares for every share outstanding was declared as of March 30, 2026, and distributed on April 6, 2026.
• Strategic Focus -- The company is targeting three complementary layers: AI infrastructure ("AI factory"), AI inference ("token factory"), and confidential computing, with the stated goal of offering differentiated, vertically integrated AI solutions for enterprise, hyperscaler, and government customers.

SUMMARY

Corvex (NASDAQ:MOVE)'s inaugural earnings call as a newly public company centered on the integration of its AI platform following the merger, highlighting a substantial shift from legacy healthcare operations to AI infrastructure and inference markets. Management emphasized a vertically integrated strategy comprising proprietary AI infrastructure, scalable inference services, and confidential computing as core drivers of future differentiation and growth. The transcript revealed management's intent to serve high-demand segments such as AI model labs, hyperscalers, regulated enterprises, and federal clients through advanced hardware and software offerings. The company also provided disclosure that pro forma financials may better represent operational trends than GAAP results due to the timing and scope of the merger close.

• Management described Corvex as "one of a limited number of publicly traded companies that provide investors with direct exposure to the emerging neo-cloud and AI inference markets."
• The CEO highlighted the intent to serve deployments "ranging from approximately 2,000 GPUs to hyperscale clusters exceeding 100,000 GPUs," targeting scale and capacity-demanding customers.
• The transcript stated strategies for cross-selling and software licensing, noting that confidential computing software could generate leads for infrastructure sales and recurring revenue streams.
• No forward guidance or specific future financial targets were provided; management did not take analyst questions on the call.

INDUSTRY GLOSSARY

• AI factory: Corvex's term for high-density GPU-based infrastructure designed for large-scale AI workload training and deployment.
• Token factory: Corvex's term for its AI inference platform delivering scalable API-based access to AI models for enterprise and government clients.
• Confidential computing: Hardware- and software-based technologies securing AI model weights, data, and inference traffic from unauthorized access during deployment and operation.
• Hyperscaler: Large-scale cloud service provider with massive infrastructure footprints serving enterprise and governmental computing needs.
• Kubernetes: Open-source orchestration platform for automating deployment, scaling, and management of containerized applications, cited as a supported environment by Corvex.
• SLURM: Open-source workload manager for scheduling and managing compute clusters, noted as a deployment environment in Corvex's product stack.

Full Conference Call Transcript

Jeremy Cogan: Thanks, Kara. Good afternoon, everyone, and welcome to Corvex's First Quarter 2026 Earnings Conference Call. Joining me today are Corvex's CEO, J Crystal; and Co-Founder and Director, Seth Demsey. A press release detailing our results was issued this afternoon and is available in the Investor Relations section of our website. A replay and transcript will be posted following the call. During today's call, we will make forward-looking statements based on current expectations. Our actual results may differ materially from such statements. Descriptions of the risks and uncertainties associated with Corvex are included in our SEC filings, which can be accessed through our website. Today's discussion also includes references to non-GAAP financial measures.

Reconciliation to the most directly comparable GAAP measure is included in our press release and on our IR website. On March 19, 2026, Corvex, Inc., formerly known as Movano Inc., acquired Corvex Legacy Holdings, Inc., also known as Corvex OpCo. The company was renamed Corvex Inc. effective March 23, 2026. Pursuant to the merger agreement, at closing, we issued to the prior security holders of Corvex OpCo 240,562 shares of Series B convertible preferred stock, representing no more than 19.9% of our outstanding common stock immediately prior to closing as well as 23,551.5195 shares of Series C preferred stock and 30,227.0524 shares of Series D preferred stock.

On March 31, 2026, each share of Series B preferred stock automatically converted into 1,000 shares of common stock. In the coming weeks, subject to stockholder approval of the conversion proposal at our upcoming annual meeting, each share of Series C preferred stock will automatically convert into 1,000 shares of common stock and each share of Series D preferred stock will be convertible into 1,000 shares of common stock. As part of the merger agreement, we also declared a stock dividend of 0.358 shares of common stock for every share outstanding at the close of business on March 30, 2026. The stock dividend was distributed on April 6, 2026. Turning to Q1 2026 results.

Our reported financial results for the first quarter reflect our legacy healthcare business for the entire period and the inclusion of Corvex's AI platform for the 12 days following the March 19 merger closing. In today's press release and in a separate 8-K we published this afternoon alongside our March 2026 quarter Form 10-Q, we also provided pro forma results for the first quarter of 2026 and fiscal year 2025. We believe the disclosure of pro forma financials provides further insight into the combined company's recent operating performance. On a reported basis, our revenue was $510,000 in the first quarter of 2026, and we reported an operating loss of $4.8 million for the period.

Again, the reported results only reflect Corvex's AI platform for 12 days in the quarter, whereas our legacy health care operations were included on a full quarter basis. On a pro forma basis, which assumes the acquisition closed on January 1, 2025, our first quarter 2026 revenue was $3.65 million, nearly all of which was generated from Corvex's AI platform. Adjusted pro forma EBITDA for the March quarter, which excludes depreciation, stock compensation expense, interest expense and taxes as well as onetime merger transaction costs, was a loss of $933,000. At March 31, 2026, total assets were $604 million, including more than $29 million in cash. With that, I'll turn the call over to Corvex's CEO, Jay Crystal.

Jay Crystal: Thanks, J. Good afternoon, everyone, and thank you for joining Corvex's first earnings call as a public company. We believe AI is driving a once-in-a-generation transformation in global computing infrastructure. As AI models become larger, more capable and more deeply integrated into enterprise and government workflows, demand for secure, scalable, high-performance AI infrastructure is accelerating. Corvex is being built to address this shift. Our platform combines AI infrastructure, AI inference software and confidential computing technology to help customers train, deploy and secure AI workloads at industrial scale. We believe Corvex represents one of a limited number of publicly traded companies that provide investors with direct exposure to the emerging neo-cloud and AI inference markets.

At Corvex, we're building a vertically integrated AI infrastructure platform that's designed to address what we believe are some of the most important requirements emerging in the AI computing market, scalable infrastructure capacity, efficient inference delivery and security for sensitive AI workloads. Our strategy is centered on operating across 3 complementary layers of the AI stack, AI infrastructure through our AI factory platform, AI inference through our token factory and confidential computing software designed to secure AI workloads and sensitive data. We believe integrating these layers into a unified platform differentiates Corvex from more commodity-oriented computing providers. Within AI factories, we're primarily focused on serving the needs of AI model labs, hyperscalers, government-backed AI initiatives and enterprises.

These customer segments increasingly require dedicated production scale computing infrastructure as well as greater speed to deployment and security. We're investing in capabilities intended to support deployments ranging from approximately 2,000 GPUs to hyperscale clusters exceeding 100,000 GPUs. We believe one of our key differentiators is how we seek to accelerate customer access to power and computing capacity through strategic partnerships and over time, a vertically integrated approach that spans data center capacity and computing capacity. At the same time, we're extending beyond traditional bare metal infrastructure through software and orchestration capabilities that support flexible deployment environments, including Kubernetes and SLURM.

We believe this combination of infrastructure scale, deployment speed, flexibility and operational support well positions Corvex to address the needs of AI factory customers. Our upcoming token factory represents the second layer of our strategy and is focused on delivering scalable AI inference capabilities for AI native companies, enterprise customers and federal organizations. We believe the AI inference market increasingly requires inference platforms capable of delivering reliability, autoscaling, cost efficiency and enhanced security across environments. Corvex's upcoming token factory is designed to provide scalable API access to premium open source and customer-provided AI models operated across both Corvex-owned infrastructure and third-party computing environments. We're also investing into inference optimization technologies intended to improve model performance and economics.

We believe this software-centric layer creates opportunities for more recurring and asset-light revenue over time while also positioning Corvex to grow token factory customer relationships into consuming additional layers of our platform. Finally, confidential computing represents the third layer of our strategy and an increasingly important area of differentiation for Corvex. We believe confidential computing will become foundational for regulated enterprises, federal customers and AI model labs seeking stronger security assurances around sensitive intellectual property, regulated data sets and proprietary inference workloads.

Our confidential computing technologies are being designed to secure model weights, inference requests and proprietary training data through a layered security architecture that combines hardware-based confidential computing with software that's designed to protect sensitive AI assets throughout deployment and runtime operations. While we intend to license our confidential computing software for use on third-party infrastructure in addition to our own, we believe that third-party licensing will ultimately serve as a lead source for future Corvex AI factory deployments. We also intend to embed confidential computing directly into our token factory in order to strengthen our ability to serve security-conscious and regulated customers. Our capabilities in confidential computing further differentiate Corvex from commodity infrastructure providers.

And more broadly, we believe our strategy is differentiated by our focus on investing in higher value layers of the AI stack rather than participating solely as a provider of commodity compute infrastructure. By combining infrastructure deployment and orchestration capabilities, inference software and confidential computing into a scalable unified platform, we believe Corvex is positioned to address the evolving performance, economic and security requirements of rapidly growing attractive customer segments while also expanding our opportunities for recurring infrastructure and software revenue over time. While we are early in our development as a public company, we believe the strategic foundation we are building positions Corvex well for the evolving demands of the AI infrastructure market.

Given our reported results reflect only a limited operating period during the first quarter, we will not be taking questions on today's call. However, we are excited about the opportunities ahead and very much look forward to updating investors on our execution and progress in the quarters to come.

Operator: Ladies and gentlemen, thank you for joining us. This concludes today's call. You may now..

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