AI agent testing platform
for reliable agents.

Catch problems before users see them and spot issues in real interactions after launch. Choose scenarios to test before release, then use those same checks on what your agent does for real users.

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See Mibo in actionLive reliability check · no signup

Test the whole agent path

Reliable agents need more than a successful reply: they must take the right steps, use the right tools, and give useful answers before release and after launch.

Flexible trace ingestion

Capture production traffic for passive evaluation. Mibo supports OpenTelemetry (OTLP/HTTP JSON), its canonical HTTP API, and the Mibo Testing community node for n8n.

OTEL (OTLP)HTTP APIn8n Testing Node

AI-Driven Scenario Routing

Mibo uses an input classifier to route matching conditional test cases, while universal checks still run on every trace.

Incoming Trace→AI Classifier→Targeted Suite

Behavioral and response checks

Combine semantic checks for response quality with procedural assertions for tools, values, schemas, status, latency, and tokens.

Expected:Helpful Tone

Status: Passed✓

Stage Pipeline Health

See stage-level pass and failure rates, then expand each test to inspect the step-by-step breakdown behind a result.

✓✓✗✓

In KPMG’s April 2025 survey of 130 U.S. enterprise leaders, 65% said their organizations were piloting AI agents, while 11% reported full deployment.

How It Works

A practical workflow for turning agent behavior into evidence you can act on before and after release.

1. Define Your Mission:
Establish your environment in seconds. Define your project's scope and objectives to create a dedicated workspace for your agentic evaluation.

2. Orchestrate Your Stack:
Connect your stack. Use n8n, Flowise, oryour own HTTP API for active runs and trace ingestion. Manage multiple agents within a single project for unified oversight.

3. Secure Technical Provisioning:
Bridge the technical gap. Configure the connection used for active runs, from webhook URLs to auth settings. For passive evaluation, send completed traces through OpenTelemetry or Mibo's canonical HTTP API.

4. Evaluate & Improve:
Design test cases with semantic and procedural checks, set each test's passive behavior, and evaluate incoming traces. Use Stage Pipeline Health and Scenario Coverage to turn results into actionable next steps.

Connect your AI stack to a shared test suite

Use n8n when your agent lives in a workflow, Flowise with the maintained trace template, or OpenTelemetry and Mibo's HTTP API for a framework-neutral ingestion path.

n8nTest workflows actively and send their traces passively.OpenTelemetryExport OTLP/HTTP JSON from any instrumented stack.FlowiseSend traces from Flowise Cloud or self-hosted with Mibo's maintained template.HTTP APISend Mibo's canonical trace shape from a custom agent.

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