Optimizing AI Inference with Quant Strategies

Shubham is an ex-quant researcher who was a founding member of a hedge fund in New York. As the first hire of a three-person team, he helped grow the fund to $400M AUM with a $2B portfolio operating across the US, Europe, and China. Recognizing the correlation between the efficiency strategies used in high-frequency trading and the needs of modern AI, he founded Zeno to apply those same optimization principles to AI infrastructure.

Zeno is an AI inference infrastructure company. Operating as a low-level AI provider, it offers inference directly, similar to an open router but with a proprietary optimization layer built on top of other AI models. Zeno aims to provide high-performance inference solutions and is currently working on POCs to offer this infrastructure to enterprises.

The company is currently raising its seed round. The team is lean, with Shubham working full-time alongside a co-founder from his previous venture, Air Labs. While currently pre-revenue, they are deeply focused on deep tech and AI interface optimization, with plans to expand the sales team at a later stage.

Zeno is primarily designed as a B2B product for enterprises. However, Shubham plans to keep the platform open for consumers to try out and integrate into their workflows. The goal is to build an open router-style product that naturally drives enterprise adoption and B2B engagements.