Corvex
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Corvex (MOVE) investor relations material

Corvex Q2 2026 earnings summary

Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.
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Q2 2026 earnings summary14 Aug, 2026

Executive summary

  • Completed merger with Corvex Legacy Holdings/OpCo on March 19, 2026, marking the first full quarter including the AI cloud computing business and exit from legacy healthcare assets as of June 30, 2026.

  • AI platform specializes in GPU-accelerated infrastructure, offering AI factories, Token Factory (inference platform), and confidential computing, with early-stage commercialization and ongoing infrastructure expansion.

  • Revenue for Q2 2026 was $3.8 million, all from the AI platform and services, under fixed-term contracts.

  • Contracted annualized recurring revenue (ARR) on live compute reached approximately $22 million as of August 2026.

  • Significant leadership appointments and board expansions were made to strengthen operational and governance capabilities.

Financial highlights

  • Q2 2026 revenue: $3.8 million; six-month revenue: $4.3 million (from March 19 to June 30).

  • Net loss for Q2: $12.8 million; net loss attributable to common stockholders: $12.8 million; six-month net loss: $17.8 million.

  • Adjusted EBITDA for Q2: -$3.2 million; for six months: -$4.8 million; AI platform and services contributed -$2.3 million for Q2.

  • Stock-based compensation expense was $9.7 million for Q2 2026, $11.9 million for the six months.

  • Ended quarter with $21.7 million in cash and cash equivalents.

Outlook and guidance

  • Focus on expanding contracted power and compute capacity to meet growing demand and scaling Token Factory.

  • Management expects continued net losses as investments in AI infrastructure and personnel continue.

  • Existing cash is expected to fund operations for at least the next twelve months; additional capital may be sought for future growth.

  • Key metrics for future reporting: contracted power, contracted ARR on live compute, and capacity brought into service.

  • Ongoing investments in automation and reliability to accelerate AI innovation.

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