Kalytera

Production agent failures compound silently when the only visibility you have is the final output. Kalytera evaluates every step of an agent run: you add a configure call at startup and a trace call after each step, or drop a decorator on each step function, and within 30 seconds the dashboard shows scored interactions broken down by step. Each failed interaction gets a verdict — a numeric score plus a sentence naming the step that caused the failure and a suggested fix, such as adding a timeout fallback before the agent guesses a policy outcome it cannot verify.

The differentiating behavior here is mid-workflow failure attribution. The vendor states that existing evaluation tools sample traffic and check only the final output, which means a tool timeout at step 3 that causes a hallucinated answer at step 4 appears in those tools as a vague quality dip rather than a traceable causal chain. Kalytera scores each step independently and links the scores, so the root cause — a timed-out API, a missed tool call, a decision made without grounding — appears directly in the dashboard without manual trace archaeology.

The tool fits teams running agents in production who need a quality signal faster than user complaints provide and who are already using a supported framework. Integration is additive: the vendor states that trace() never raises and always returns in under 5ms, so wrapping existing steps does not change agent logic or add latency risk. Where it breaks: there is no self-hosted option, so teams with data residency requirements cannot keep traces on their own infrastructure. The free tier’s 10,000-session monthly ceiling is a hard wall for high-volume deployments — teams running production agents at scale will hit paid-only territory quickly, and the depth of governance and rollback-prevention features at higher tiers is not detailed in public documentation.