Building systems at the intersection of AI, infrastructure, and decision-making

I am interested in how decisions are made at scale and how systems can be designed to improve those decisions. I studied Economics and Statistics at Columbia University, where I developed a foundation in quantitative reasoning and data-driven modeling. Through research at Columbia Business School, I examined AI-enabled decision systems and the evaluation of intelligent models operating under uncertainty. My work focuses on building and understanding systems that operate in real-world environments, where uncertainty, incentives, and infrastructure constraints interact.

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I am currently building OpenMesh, a unified platform for agentic inference and evaluation designed to support the next generation of AI systems. OpenMesh enables intelligent routing, deployment, and continuous evaluation of AI workloads across multiple models and compute providers, treating inference as a dynamic system problem rather than a static pipeline. The goal is to establish the inference intelligence layer for AI agents, where model selection, execution, and evaluation are tightly integrated in real-world environments.

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I am the founding partner of Sky Arc Capital, a venture firm focused on investing in frontier technology companies. At Sky Arc, I work with founders building across artificial intelligence, infrastructure, and emerging technologies, including companies such as Standard Kernel, Dedalus Labs, and Eigent AI.