Now building

Your agents break in ways you can't predict

Crucible is an evaluation and observability platform for autonomous AI agents. Not single LLM calls. Not simple chains. Real agents running real workflows over hours.

The Problem

Existing tools were built for a simpler world

Current State
57%
of organizations have agents in production, but quality remains the #1 barrier to deployment.
The Gap
Step 47
Your agent failed at step 47 of a 3-hour workflow. Current tools show you step 1. Crucible shows you why.
Fragmented
20+
platforms exist for LLM observability. None are purpose-built for autonomous, long-horizon agents.
Cost of Failure
Cascading
When an agent makes a bad decision at step 12, every subsequent step compounds the error. Silent failures cost more than loud ones.
How Crucible Works

Built for agents that think for themselves

01

Long-horizon tracing

Follow an agent's reasoning across hundreds of steps and hours of execution. See every decision, tool call, and branching point in a single timeline.

02

Failure ancestry

When an agent fails, Crucible traces back to the root decision that caused the cascade. Not just what broke, but where the reasoning went wrong.

03

Multi-agent coordination monitoring

Visualize handoffs between agents, track shared state mutations, and catch coordination failures before they compound across your agent fleet.

04

Regression detection

Run eval suites against every prompt change, model swap, or config update. Know if your agent got worse before your users do.

The Vision

Every agent in production deserves the rigor of a test before it ships

We're building the evaluation infrastructure that makes autonomous agents trustworthy. Because the future runs on agents, and agents need to be held accountable.