Report AI Risk With Evidence
Boards ask about AI risk, cost, and control. ProofMap helps teams turn technical evaluations into a clear story about readiness and governance.
Get StartedWhy Choose ProofMap
Summarize exposure
Show where critical workflows depend on models, providers, prompts, and tools.
Show progress
Track qualified fallbacks, safer prompt packages, and cost-saving runtime changes.
Support decisions
Use evidence to explain tradeoffs around speed, spend, quality, and risk.
Comparison
| Moment | Without ProofMap | With ProofMap |
|---|---|---|
| Evidence request | Teams assemble screenshots, anecdotes, and raw logs after the question arrives. | Qualification reports show prompt, model, tool, fallback, and approval evidence. |
| Production change | Prompt, model, schema, or permission changes are reviewed informally. | Changes run through objective-bound evaluations before promotion. |
| Business pressure | Audits, launches, renewals, and customer escalations force rushed AI decisions. | Teams use existing tests and approved mappings to respond with confidence. |
| Developer workload | Developers chase failures across transcripts, tools, providers, and one-off integrations. | Failures become repeatable tests with clear evidence and approved fixes. |
Frequently Asked Questions
What should boards know about AI systems?
They need to understand material risks: provider dependence, quality regressions, data access, cost volatility, incident readiness, and governance controls.
Can ProofMap create executive evidence?
It creates the underlying qualification data that teams can summarize for executive and board reporting.
What makes this useful for developers?
It turns AI behavior changes into repeatable tests, reduces manual investigation, and provides concrete evidence for prompt, model, MCP, and runtime decisions.
What does ProofMap produce?
ProofMap produces objective-bound evaluations, failure evidence, recommendations, and approved prompt or runtime mappings for production use.