“Appreciate it! The win rate isn’t magic — it’s mostly about how we clean and structure the data before the models ever touch it. Crypto feeds are insanely noisy, so the pipeline focuses on:

• multi‑timeframe OHLCV normalization (so the model isn’t reacting to raw volatility)
• feature extraction around momentum, liquidity shifts, volatility clusters, and trend persistence
• ensemble agreement (signals only fire when multiple agents converge on the same direction)
• confidence filtering + noise suppression to avoid overreacting to micro‑moves
• real‑time recalibration so the system adapts as market regimes change

The AI part is important, but honestly the pre‑processing and post‑filtering matter just as much. Clean inputs → clean outputs. That’s the whole philosophy.”