AI AgentLive in the product
Learning Agent
Records every forecast, grades the outcome, and gets more accurate over time.
Example output
Calibration
Learning · daily
illustrative
What it watches
- Past forecast hit-rate
- Accuracy per symbol and per horizon
- Systematic over/under-confidence
Inputs
- Every recorded forecast
- The realized outcome at each horizon
- Rolling hit-rate history
What it produces
Calibrated probabilities — the shown confidence is adjusted by the model's real track record, so it improves as data accrues.
How it works
- 1Record each forecast to a history log
- 2Grade the outcome when the horizon elapses
- 3Compute hit-rate (Bayesian shrinkage)
- 4Calibrate future probabilities
See Learning Agent live on any symbol
Free to start — 15 agents, a 0–100 decision score and the full read on crypto, stocks, BIST and funds.