Making AI agents reliable enough for the workflows that matter.
Reinforce Market Labs was founded to close the gap between impressive AI demos and reliable production agents — with control infrastructure built for complex markets.
Principles
Production over demos
The next wave of enterprise AI will not be won by the most impressive demo, but by the systems that can be governed, measured, trusted, and improved in production.
Hardest domains first
We start where reliability and auditability are non-negotiable — finance — and extend the control-layer philosophy to every workflow where agents touch real decisions.
Product-led, battle-tested
Every infrastructure primitive we build is tested in production, first in our own systems, then made available to the teams we work with.
Embedded, not bolted on
We work like forward-deployed engineers: inside your infrastructure, on your real constraints, at the core of the market problem — not at the edges.
The missing layer between agents and operations.
Most agent projects stall between prototype and production. The gap is not model capability — it is orchestration, policy enforcement, evaluation discipline, and operational accountability. That is the layer we build.
Our platform gives teams policy gates, evaluation harnesses, full-run observability, and audit-ready records — so autonomous systems can operate in workflows where mistakes are expensive, with oversight built in from the start.
Built by scientists, engineers, and operators
David has spent 15 years building zero-to-one AI where failure isn't an option — global-scale personalization for Apple App Store Ads, AI for cloud observability as Chief Scientist at Vorstela, and agentic systems and reinforcement learning deployed at scale on live capital at DB Macro Research.
He earned his Ph.D. at Georgia Tech, where he researched decision-making under uncertainty — the same problem he now builds AI agents to solve in the world's most complex markets.
Work with Reinforce Market Labs
Whether you are exploring agentic AI for the first time or bringing production discipline to an existing agent stack, we would like to hear from you.
Get in touch