Find failures before flight.
Crucible builds verifiable simulation environments where AI agents can act through physical scenarios, learn from failures, and prove they are ready before they touch the real world.
Product
Real software, running now.
Autonomous agents maneuvering through a defended corridor. Real-time simulation with full observability and agent control.
Platform
A proving ground for AI agents.
Environment
Model the scenario, assets, constraints, and objectives an agent must understand.
Act
Put decision-making AI inside the environment instead of only scoring human choices.
Test
Run the agent through varied physical scenarios and expose failures before deployment.
Decide
Turn results into replayable evidence for training, gating, and go/no-go decisions.
Existing modeling tools help people analyze scenarios. Crucible is building the environment where autonomous agents prove they can make decisions.
Signals
What has to be tested first.
Decision quality
Whether an agent chooses the right action under pressure.
Comms degradation
Latency, loss, stale state, and partial observability.
Scenario pressure
Hard physical situations that reveal brittle behavior.
Deployment evidence
Records that show what the agent did and why it passed or failed.
Artifacts
The output is a decision record.
agent_trial:
scenario: denied_air_corridor
objective: protect_package
action: reroute + hold_fire
result: mission_failed
replay: deterministic
verdict: do_not_deployPilot
Bring a scenario. Leave with a test environment.
We integrate with the simulator or scenario source you already have, put agents in the loop, and produce evidence about where they are ready and where they fail.