Martin Georgiev

Director, Application Security; Advisor, Investor

๐Ÿ“ United States๐Ÿ”„ Updated October 2026๐Ÿ’ผ 1 investments๐Ÿ“… 2 years investing๐Ÿ—“ Last invested Aug 2024
Angel investor๐ŸŒ United States
1
Total investments
1
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0
Mid stage
0
Late stage
2y
Years active

Portfolio

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Seed Investor
Aug 2024
Causal Dynamics Lab is the Causal AI Lab for Autonomous Reliability. Current AI systems optimize for sounding correct rather than being correct. They pattern match, hallucinate confidently, and cant actually understand the systems they operate in. A better approach is possible: Causal AI, because the โ€œwhyโ€ matters. What we build: Every product starts with the same foundation: the Production World Model, a living representation of your production environment connecting code, configuration, infrastructure, policy, and the decisions behind every change. We build AI that reasons through cause and effect, then act. Why Causal AI: Traditional tools rely on correlation - they tell you what happened. We use causal reasoning to tell you what will happen. This is deterministic proof, grounded in the Pearl Causal Hierarchy. Built by operators, powered by deep research: Founded by the team that built reliability at Uber during hyperscale. Backed by deep R&D partnerships with Top AI Labs from a prestigious University, and advisors from Google DeepMind, Microsoft Research, and Hugging Face. Ship at the speed of AI without compromising production stability.
Experience ยท 1 entries
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Investments (1)
2024
Seed Investor
Aug 2024
Causal Dynamics Lab is the Causal AI Lab for Autonomous Reliability. Current AI systems optimize for sounding correct rather than being correct. They pattern match, hallucinate confidently, and cant actually understand the systems they operate in. A better approach is possible: Causal AI, because the โ€œwhyโ€ matters. What we build: Every product starts with the same foundation: the Production World Model, a living representation of your production environment connecting code, configuration, infrastructure, policy, and the decisions behind every change. We build AI that reasons through cause and effect, then act. Why Causal AI: Traditional tools rely on correlation - they tell you what happened. We use causal reasoning to tell you what will happen. This is deterministic proof, grounded in the Pearl Causal Hierarchy. Built by operators, powered by deep research: Founded by the team that built reliability at Uber during hyperscale. Backed by deep R&D partnerships with Top AI Labs from a prestigious University, and advisors from Google DeepMind, Microsoft Research, and Hugging Face. Ship at the speed of AI without compromising production stability.