The reliability platform for AI agents.

Every agent run is captured automatically the moment it happens — no sampling, no manual instrumentation. Search thousands of traces by status, model, agent, tool, environment, or time, and read spans, tokens, cost, and latency for each without opening a single row.

Open any run into a full span waterfall that lays out every LLM call, tool invocation, and memory lookup in order — each one timed and priced. A live inspector shows the exact input, output, tokens, and errors for whichever span you select, so the failing step is obvious in seconds.

Related traces are grouped into user sessions so you can analyze whole conversations, not isolated calls. Replay any multi-turn interaction end to end, with cost, duration, and error count rolled up per session and full-text search across first messages.

Zespan auto-discovers your delegation topology — which agent hands off to which — and renders it as a live graph. Coordinator and specialist roles are mapped for you, with per-hop cost and delegation frequency on every edge, so multi-agent behavior stops being a black box.

Track success rate, latency, cost, and failures across every tool call your agents make. A colour-coded health map surfaces the tools quietly breaking, and every tool is auto-discovered straight from your spans — nothing to register.

See model-level usage, cost, and reliability across every provider in one place. Compare Claude, GPT, and Gemini side by side on p50/p90/p99 latency, spend, and error rate to know exactly where your budget and your failures are going.

Score every trace automatically with LLM-as-judge and rule-based evaluators, so quality regressions surface before your users hit them. Use built-in evaluators or your own criteria, and watch pass rate and scores trend over time as you ship.

Version, compare, and roll back prompts across deployments without touching code. Every version carries its own live cost and error rate, production labels track what's actually serving, and you can A/B test changes directly in production.

Promote real production traces into curated datasets in a single click — build regression sets from the failures that actually happened, not synthetic ones. Reuse them for evals and batch runs so fixed bugs stay fixed.

Replay agent scenarios against new prompts or models before you ship, so you know the pass rate before production finds out. Batch-run scenarios with assertions and compare runs side by side to catch regressions early.

One-click protections run before and after every request to block PII leaks, prompt injection, jailbreaks, runaway loops, and out-of-budget calls. Nine quick-install threat patterns cover the common cases, each configurable to block or redact at the PRE or POST stage.

Track spend per model, per day, and per token type, with input, output, and cached tokens broken out. Built-in anomaly detection flags cost drift and spikes the moment they happen — not when the invoice arrives.

Get exact cost attributed to every agent, tool, model, and user, with no manual tagging and no spreadsheet reconciliation. Break spend down along any dimension and see per-call cost and error rate for each.

Project cost and latency forward with confidence bands built from your recent telemetry. Upper-bound budget alerts warn you before you overspend — not after — so surprises stay off the invoice.

Monitor latency, throughput, and reliability across every trace, with p50/p90/p99 broken out by model and by span kind over time. Timeout and rate-limit rates are tracked alongside, so slowdowns surface before users complain.

Set threshold and evaluator-based alerts on the metrics that matter — latency, cost, error rate, and eval scores — and route them to email or PagerDuty the moment they fire. Every rule keeps a full firing history so you can see what has been noisy.

Error spikes, model changes, and prompt deploys are correlated into single incidents automatically, each with an AI-written root cause instead of just a red graph. Severity, affected requests, and mean-time-to-resolve are tracked so you know what to fix first.