How Our AI Crypto Predictions Work — and How We Keep Them Honest

The internet is full of AI trading predictions with no accountability. Our approach is different by design: every prediction our system publishes is a testable statement, and we grade it in public.

The pipeline

When you request an analysis, the terminal assembles a data packet: live price and recent candles, funding rate, taker net volume, smart-money flow, whale-alert counts, the Fear & Greed Index and relevant macro news. This packet goes to DeepSeek, which returns a structured forecast: directional bias, confidence, a target price and an expected range over a defined time horizon.

The accountability layer

Each prediction is logged with its timestamp, target, range and horizon. An automated job checks every prediction after its horizon expires, fetches the actual market price, and records two numbers: the percentage error against the target, and whether the price landed inside the predicted band.

The results feed a public scoreboard — total predictions, hit rate, average error — that anyone can inspect. If the AI has a bad week, the scoreboard says so. We believe this is the only honest way to run an AI prediction service.

The limits

No model predicts news. A sudden ETF decision, hack or macro shock can invalidate any forecast in minutes. Use predictions as one structured input among many, size positions accordingly, and never trade money you cannot afford to lose. Nothing on this site is financial advice.