Toward Autonomous Markets
We make it safe, efficient, and scalable for AI models to operate within financial markets.
Every year, thousands of extraordinary minds enter finance instead of curing disease, solving energy, or exploring space. We teach AI to run capital markets so humans don't have to.
AI can talk about money.
It can't safely use it.
Frontier models can talk about finance but can't safely operate. We build the infrastructure that bridges that gap.
Decision Data
AI labs have price data, news data, and market data. What they don't have is decision data.
We generate RL trajectories with real traders in the loop and real capital on the line. Tool use, constraint navigation, decisions, and outcomes, all sourced from a production trading environment.
Agent Infrastructure
Real trading infrastructure is tuned for years in live markets. LLMs don't change that.
Financial agents need to process large, continuous, and diverse information streams. Our inference engine orchestrates dozens of models to reduce cost by 99% while preserving frontier performance.
Trust Layer
The starting line for financial agents is perfect reliability. The rest is trust-building.
Every product that touches money will eventually need embedded AI. We provide the policy engine, compliance tooling, and audit trails to accelerate toward this outcome.
What running 750+ agents taught us
We started building agentic finance before the term existed. Three years of live operations, real capital, and multiple market regimes produced a set of convictions about what this technology actually requires.
Every trade tunes the next one.
Millions of placed trades, each one shaping how we tune the harness and structure every trajectory. The agents running today are products of every decision that came before them.
You can't accelerate time in production.
Reliability is a Lindy effect. So is the feedback loop between agents and the humans who deploy them. Our agents have won their trust across 3 years of live market operation and trillions of tokens processed.
Economics matter as much as intelligence.
Inference cost comes straight out of PnL. Our agents accomplish with $1 of compute what takes $50-100 elsewhere. At scale, that difference is the entire margin.
Financial AI is inevitable.
Coding agents went from novelty to necessity overnight. Financial agents are next. Our mission is to accelerate toward a world where capital can allocate itself.
When machines learned to farm, humanity built civilization.
When machines learn to allocate capital,
we build everything else.
Build with us.
Work with our team to deploy and train frontier financial agents.
For Financial Platforms
Give your users access to autonomous agents that have been battle-tested across three years of live market operation.
Learn About HarnessFor Research Labs
Access the decision data frontier models are missing. Complete trading episodes with reasoning traces, tool calls, and verified outcomes.
Explore Decision Data