Stop Guessing, Start Tracing
Why AITracer stores every agent run as a trace — and how that powers local training.
Production AI fails quietly: wrong answers, wasted tokens, no record of what the model actually said.
AITracer’s answer is simple — save every run as a trace (prompt, response, model, tokens, latency). For local work that means Ollama in Agent Lab at $0. For production apps it means SDK or API ingest from your cloud provider.
What tracing gives you
- A history of runs — search by action name, model, or time in the dashboard.
- Training data — export JSONL or build an Ollama model from curated examples.
- Optional coach — paid model reviews a local draft; you pick what goes into the dataset.
What tracing is not
Tracing is not magic compliance. Governance, SHA-256 verification, and audit vault features exist for teams that ingest production traffic and need those controls — they are not required to run Agent Lab or export training data.
Start with Quick Start if you have not run your first local agent yet.