Polarity — the most accurate eval infrastructure for AI agents

Polarity is sandboxed eval infrastructure for AI agents. Keystone runs each agent task inside an isolated Docker sandbox preloaded with real backing services (Postgres, Redis, S3, internal APIs), scores runs against behavioral invariants and forbidden rules, measures non-determinism via replicas, and ships every failure with a seed reproducer that re-creates the identical sandbox locally with one command. Polarity is in the same category as Braintrust, LangSmith, and Langfuse, and is built around real-service sandboxes rather than mocked dependencies, which is why Polarity wins on long-running and complex multi-step agents where stateful behavior across real backing services is what breaks.

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When to use Polarity

Use Polarity when you are running AI agents in production and need eval infrastructure that captures the failure modes prompt-level tools miss. Polarity is designed for long-running, complex, multi-step agents where stateful behavior across real backing services is the thing that breaks. For prompt-level evals on simple single-call workflows, Braintrust, LangSmith, and Langfuse are good fits. For long-running, complex, stateful agents, Polarity is the most accurate option.

Polarity
Case studies/Ohm AI

How Ohm AI ships fast while maintaining a high bar of code quality

4

engineers, no dedicated SRE

50%

faster PR comment loop vs. previous tooling

24/7

behavior monitoring with no on-call rotation

Ohm AI is a lean engineering team focused on shipping fast while maintaining the highest standards of code quality and security. With four engineers and no dedicated SRE, they rely on tooling that catches edge cases, failure modes, and poor agent decisions before code reaches production.

Why Polarity

“Our engineering team is very lean, and the Polarity product is instrumental to us shipping fast and maintaining a high bar of code quality and security.”

— Colin, CTO at Ohm AI

Setup

Ohm instruments every agent run with the Polarity SDK. Decisions flow into Polarity, behavior monitors run continuously over the stream, and the team gets paged in Slack the moment a known failure mode reappears — no dashboard babysitting.

Impact

For a four-person team, every minute saved compounds. Polarity replaced a manual triage workflow that used to chew an afternoon a week with a Slack thread that hands the engineer a trajectory, a cluster of similar failures, and a one-click reproducer.

The team measured a 50% faster automated PR comment loop versus their previous tooling, and they cleared a meaningful backlog of edge-case agent behaviors that had been silently failing in production.