PolarityCatch failures before users do and build self-improving agents

Polarity

Polarity is the most accurate eval infrastructure for AI agents, designed to catch failure modes that prompt-level tools miss. Unlike traditional evaluation platforms, Polarity runs each agent task inside an isolated Docker sandbox with real backing services—ensuring your agents break in testing before they break in production.

Product Highlights

• Real-Service Sandboxes: Run agents with actual Postgres, Redis, S3, and internal APIs instead of mocked dependencies, capturing stateful behavior that causes real failures
• Deterministic Reproduction: Every failure ships with a seed reproducer that re-creates the identical sandbox locally with one command
• Behavioral Invariants: Score runs against custom rules and forbidden patterns, measuring non-determinism via parallel replicas
• Sub-Second Cold Boot: Keystone launches sandboxed environments in 214ms—51x faster than competitors—scaling to thousands of parallel runs
• Full Trajectory Replay: Capture every tool call, byte read, and CPU cycle with programmable bisection to isolate failing steps

Use Cases

• Long-Running Agent Evaluation: Test complex multi-step agents where state accumulates across database transactions, API calls, and file operations over minutes or hours
• Pre-Production Gating: Automatically block deployments when agents violate invariants, using real eval data rather than synthetic benchmarks
• Regression Testing: Promote production failures into permanent eval datasets with one click, preventing recurring bugs
• Performance Optimization: Measure non-determinism across replica runs to identify flaky behavior and reliability gaps

Target Audience

Polarity is built for engineering teams running AI agents in production—particularly those with complex, stateful workflows where Braintrust, LangSmith, and Langfuse's mocked-dependency approach misses critical failure modes. Ideal for companies prioritizing reliability over speed of initial prototyping.