How We Built an AI That Explains Every Crypto Trade It Makes

Why We Built This Most crypto trading bots are black boxes. They buy. They sell. They lose your money. And they never tell you why. We wanted to build something different: a platform where every single trade comes with a plain-English explanation written by an AI — not a template, not a lookup table, but actual reasoning about what the market was doing and why the algorithm acted the way it did. This is the technical story of how we built that. The Architecture at a Glance Our platform runs 26 trading strategies across 7 exchanges simultaneously. When a trade signal fires, it passes through three layers before execution: Signal scoring — A LightGBM model evaluates 20+ market factors to assign a probability score Trade explanation — An Ollama/Llama 3.1 8B instance generates a natural language explanation Portfolio AI — A meta-layer decides position sizing and risk allocation Let's dig into each. Layer 1: ML Signal Scoring with LightGBM Before any trade executes, it gets scored by a grad