Automatically build golden evaluation datasets from real production behavior, map your agent's capabilities, and catch regressions before you deploy.
The problem
Traditional software has unit tests. But when you tweak a system prompt to fix a login bug, you risk silently breaking ten other capabilities. Maintaining a golden dataset by hand takes hundreds of hours engineering teams don't have.
The solution
AutoEvals turns your production logs into a continuous testing suite — with zero machine learning knowledge required. We map your agent's code, capture real-world edge cases from live users, and auto-generate comprehensive testing rubrics.
Initialize AutoEvals inside your agent's codebase.
pip install autoevals-cli autoevals init
Stream live interactions and tool trajectories to our secure API.
from autoevals import AutoEvalsTelemetry telemetry = AutoEvalsTelemetry(api_key="your_key") telemetry.log_trace(user_input, agent_output, tools_fired)
Run heavy automated regression tests on every push.
- name: Run AutoEvals Benchmarks run: autoevals-eval --dataset $DATASET_ID --entrypoint main.py
$0
Free forever
Perfect for developers building side projects.
$79
per month
For small engineering teams with an agent in production.
$299
per month
For scaling AI startups demanding deep regression testing.
Custom
talk to us
For organizations with strict security and massive telemetry scale.
Agent data is highly sensitive. AutoEvals runs on a secure PostgreSQL architecture with row-level security, strict data isolation, and comprehensive PII scrubbing so user logs stay private.
Start evaluating for free