Q1 2026 Corvex Inc Earnings Call
Operator: Hello, everyone. Thank you for joining us, and welcome to Corvex Q1 2026 Earnings Call. I will now hand the call over to J. Cogan, CFO. Please go ahead, sir.
Operator: Hello, everyone. Thank you for joining us, and welcome to Corvex Q1 2026 earnings call. I will now hand the call over to Jay Cogan, Chief Financial Officer. Please go ahead, sir.
Speaker #1: Hello everyone. Thank you for joining us and welcome to Corvex First Quarter 2026 earnings call. I will now hand the call over to Jay Kogan, CFO; please go ahead, sir.
Speaker #2: Thanks, Kara. Good afternoon, everyone, and welcome to Corvex's first quarter 2026 earnings conference call. Joining me today are Corvex CEO Jay Crystal, and co-founder and director Seth Dempsey.
Jay Cogan: Thanks, Kara. Good afternoon, everyone, and welcome to Corvex's Q1 2026 earnings conference call. Joining me today are Corvex Chief Executive Officer, Jay 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 could 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.
Jay Cogan: Thanks, Kara. Good afternoon, everyone, and welcome to Corvex's Q1 2026 Earnings Conference Call. Joining me today are Corvex CEO, Jay 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 could 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.
Speaker #2: 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.
Speaker #2: 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.
Speaker #2: Today's discussion also includes references to non-GAAP financial measures. A reconciliation to the most directly comparable GAAP measure is included in our press release and on our IR website.
Speaker #2: 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.
Jay Cogan: On 19 March 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 23 March 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 31 March 2026, each share of Series B preferred stock automatically converted into 1,000 shares of common stock.
Jay Cogan: On 19 March 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 23 March 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 31 March 2026, each share of Series B preferred stock automatically converted into 1,000 shares of common stock.
Speaker #2: 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.
Speaker #2: 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.
Speaker #2: 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.
Jay Cogan: 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 30 March 2026. The stock dividend was distributed on 6 April 2026. Turning to Q1 2026 results. Our reported financial results for the Q1 reflect our legacy healthcare business for the entire period and the inclusion of Corvex's AI platform for the 12 days following the 19 March merger closing.
Jay Cogan: 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 30 March 2026. The stock dividend was distributed on 6 April 2026. Turning to Q1 2026 results. Our reported financial results for the Q1 reflect our legacy healthcare business for the entire period and the inclusion of Corvex's AI platform for the 12 days following the 19 March merger closing.
Speaker #2: 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.
Speaker #2: 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.
Speaker #2: 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.
Jay Cogan: In today's press release and in a separate 8-K we published this afternoon alongside our March 2026 Q1 Form 10-Q, we also provided pro forma results for Q1 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 Q1 2026, and we reported an operating loss of $4.8 million for the period.
Jay Cogan: In today's press release and in a separate 8-K we published this afternoon alongside our March 2026 Q1 Form 10-Q, we also provided pro forma results for Q1 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 Q1 2026, and we reported an operating loss of $4.8 million for the period.
Speaker #2: 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.
Speaker #2: Again, the reported results only reflect Corvex's AI platform for 12 days in the quarter, whereas our legacy healthcare operations were included on a full quarter basis.
Jay Cogan: Again, the reported results only reflect Corvex's AI platform for 12 days in the quarter, whereas our legacy healthcare operations were included on a full quarter basis. On a pro forma basis, which assumes the acquisition closed on 1 January 2025, our Q1 2026 revenue was $3.65 million, nearly all of which was generated from Corvex's AI platform. Adjusted pro forma EBITDA for the Q1, which excludes depreciation, stock compensation expense, interest expense, and taxes, as well as one-time merger transaction costs, was a loss of $933,000. At 31 March 2026, total assets were $604 million, including more than $29 million in cash. With that, I'll turn the call over to Corvex's Chief Executive Officer, Jay Crystal.
Jay Cogan: Again, the reported results only reflect Corvex's AI platform for 12 days in the quarter, whereas our legacy healthcare operations were included on a full quarter basis. On a pro forma basis, which assumes the acquisition closed on 1 January 2025, our Q1 2026 revenue was $3.65 million, nearly all of which was generated from Corvex's AI platform. Adjusted pro forma EBITDA for the Q1, which excludes depreciation, stock compensation expense, interest expense, and taxes, as well as one-time merger transaction costs, was a loss of -$933,000. At 31 March 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.
Speaker #2: 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.
Speaker #2: Adjusted pro forma EBITDA for the March quarter, which excludes depreciation, stock compensation expense, interest expense, and taxes, as well as one-time merger transaction costs, was a loss of $933,000.
Speaker #2: 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.
Speaker #3: Thanks, Jay. 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.
Jay Crystal: Thanks, Jay. 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 neocloud and AI inference markets.
Jay Crystal: Thanks, Jay. 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 neocloud and AI inference markets.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: We believe Corvex represents one of a limited number of publicly traded companies that provide investors with direct exposure to the emerging neocloud and AI inference markets.
Speaker #3: A 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.
Jay Crystal: 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 three 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.
Jay Crystal: 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 three 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.
Speaker #3: Scalable infrastructure capacity, efficient inference delivery, and security for sensitive AI workloads. Our strategy is centered on operating across three 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 in sensitive data.
Speaker #3: 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.
Speaker #3: 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.
Jay Crystal: 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.
Jay Crystal: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Jay Crystal: We believe the AI inference market increasingly requires inference platforms capable of delivering reliability, auto-scaling, 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 datasets, and proprietary inference workloads.
Jay Crystal: We believe the AI inference market increasingly requires inference platforms capable of delivering reliability, auto-scaling, 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 datasets, and proprietary inference workloads.
Speaker #3: We're also investing into inference optimization technologies intended to improve model performance and economics. We believe the 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.
Speaker #3: 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.
Speaker #3: 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.
Jay Crystal: 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. 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.
Jay Crystal: 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. 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Jay Crystal: 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 Q1, 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.
Jay Crystal: 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 Q1, 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.
Speaker #3: 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.
Speaker #3: 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 disconnect.
Operator: Ladies and gentlemen, thank you for joining us. This concludes today's call. You may now disconnect.
