Project
Quant AI
⚙ In ProductionAn autonomous trading system that reasons like a desk and never trades on emotion.
The Problem
Retail traders face a structural disadvantage. They trade emotionally and inconsistently, watching one market at a time, while institutions run rules-based, multi-asset strategies executed by machines.
Most traders also repeat the same mistakes because they never systematically analyse why a trade failed.
Retail Trader vs Quant AI
Retail Trader
✕Emotional, inconsistent decisions
✕Watches one market at a time
✕No feedback loop on losses
Quant AI
✓Same rules applied every time
✓Scans 40+ instruments continuously
✓Learns from every closed trade
The Solution
Quant AI runs as a fully automated pipeline — from market scanning through to position management — applying institutional-grade discipline with an AI reasoning layer on top.
AI Reasoning Layer
Every trade candidate is evaluated by Claude against a structured institutional methodology before it's allowed to execute, reasoning about confluence, trend alignment, and risk in natural language.
Self-Improving Feedback Loop
Every closed position is automatically analysed by AI, which classifies why it won or lost and writes specific lessons that refine the rules over time — the system learns from its own trades.
Full Risk Governance
Automated circuit breakers, position sizing capped at 1% risk per trade, and portfolio-level risk caps are enforced programmatically before any AI decision can override them.
Built With
Who It's For
Individual traders and investors who want a systematic, emotion-free approach to markets but lack the time or technical background to build one themselves. More broadly, a showcase of what's possible when AI reasoning is layered on top of disciplined, rules-based systems.
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