Lucid Computing builds hardware-rooted AI verification infrastructure that cryptographically proves where AI chips are located and what they are processing, enabling enforceable compute governance and regulatory compliance.
Lucid Computing builds hardware-rooted AI verification infrastructure that cryptographically proves where AI chips are located and what they are processing, enabling enforceable compute governance and regulatory compliance.
People
Updated 05/18/26By grantmaking.aiDirector of Policy and Strategy
CTO and Co-Founder
Chief Executive Officer
Chief Product Officer & Partnerships
Funding Details
Updated 05/18/26By grantmaking.ai- -
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Org Details
Updated 05/18/26By grantmaking.aiLucid Computing was incorporated in March 2025 and is headquartered in San Francisco, California. Co-founded by Kristian Rönn (CEO) and Gregory Kollmer (CTO), the company builds a hardware-rooted AI verification platform designed to make AI deployments cryptographically auditable and policy-compliant.
Kristian Rönn previously founded Normative, a carbon accounting platform that helped shape EU and UK climate disclosure rules, and began his career researching existential risk at Oxford's Future of Humanity Institute. Gregory Kollmer holds a Master of Science in Mechanical Engineering from Columbia University. As of early 2026, the team is approximately 7 people.
Lucid's core technology uses Trusted Execution Environments (TEEs) — including Intel TDX and NVIDIA confidential computing — to create hardware-encrypted enclaves where AI models run with cryptographic guarantees about data residency, model integrity, and inference provenance. Their platform verifies that every inference meets compliance requirements before reaching end users, and generates tamper-proof audit trails automatically.
Key product lines include: (1) Cryptographic compliance modules for GDPR, HIPAA, EU AI Act, ITAR, and ISO 42001; (2) Digital Embassies — sovereign cloud enclaves that allow organizations to expand into regulated markets with cryptographic proof of regulatory alignment; and (3) physics-based remote location verification using latency measurements bounded by the speed of light to prove hardware location without relying on legal agreements alone.
Lucid also publishes policy research focused on AI export control enforcement, arguing that effective compute governance requires cryptographic verification of GPU locations and usage rather than simply counting chips. The company has documented methods used to circumvent US export controls and has proposed hardware verification frameworks informed by arms control and climate treaty regimes.
Lucid Computing Labs, a research arm operating from a testbed facility at Equinix SV4 in Sunnyvale, California, provides free access to researchers working on verification, compute governance, AI safety, or hardware trust, on the condition that findings are published under open licenses.
The company was part of Seldon Lab's inaugural AI security startup accelerator batch (Summer 2025), alongside Workshop Labs, Andon Labs, and DeepResponse. Collectively, those four companies raised over $10 million and closed contracts with AI labs including xAI and Anthropic. Lucid's investors include Seldon Lab, Juniper Ventures, and Lionheart Ventures.
Theory of Change
Updated 05/18/26By grantmaking.aiLucid Computing's theory of change holds that effective AI governance — including safety and export controls — requires cryptographic enforcement rather than relying on legal agreements or voluntary compliance. If regulators, governments, and enterprises cannot verify where AI chips are located and what they are processing, safety policies and export controls cannot be meaningfully enforced. By building hardware-rooted verification infrastructure (using TEEs, remote location proofs, and cryptographic audit trails), Lucid aims to make compute governance technically enforceable at scale. This creates the foundation for international AI treaties, export control regimes, and safety standards to have real-world effect — reducing the risk that advanced AI capabilities proliferate to unaccountable actors or that AI systems are deployed without meaningful oversight.
Grants Received– no grants recorded
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