Powering the next generation of trading intelligence.

Two years ago, AI couldn't code. Today, AI can't predict. Models were trained on the internet — and the internet has no alpha.

There are roughly 1,000 software engineers for every quant. Engineers publish on GitHub. Quants never share. So the models can write code but cannot trade.

We ran Claude, GPT-5, Gemini, Grok, and Qwen through our trading eval. Best Sharpe: 1.88. Threshold: 2.0. None passed. Our ground truth scores 2.784.

The prerequisites for being a quant are exactly two: the ability to code, and the ability to reason. The missing piece is institutional knowledge — market microstructure, order books, risk management — knowledge that lives inside firms, not on the internet.

We are building it. RL environments. Evaluations. Expert trading data. A live desk that turns every fill into training signal no competitor can access.

We call this the machine that makes machines that make money.