The problem
When an AI agent produces a wrong answer, ordinary traces show what happened but leave teams debugging backward from the final response. The responsible step can be buried inside retrieval, planning, tool calls or synthesis.
Our approach
Black Box records each execution step, ranks likely causes from trace evidence and tests them through counterfactual replay. Its repair flow re-executes only affected steps, preserving trusted work and making the diagnosis inspectable.
What it enables
- Step-level execution traces
- Evidence-backed failure diagnosis
- Counterfactual replay and verified repair