Reduce AI Risk Before Renewals
Renewals expose unresolved product risk. ProofMap helps teams show what has improved and where AI workflows are qualified.
Get StartedWhy Choose ProofMap
Turn the moment into tests
Convert the customer renewal into objective criteria that prompts, models, MCP tools, and fallback mappings must pass.
Control the rollout
Compare candidates against the baseline and decide what can launch, what needs fallback, and what should stay blocked.
Give teams usable evidence
Produce evidence for retention conversations for product, engineering, sales, security, and leadership teams.
Comparison
| Decision | Ad hoc approach | ProofMap |
|---|---|---|
| Define readiness | Teams rely on demos, opinions, and scattered notes. | Define objective-bound evaluations for the workflow and release moment. |
| Review behavior | Reviewers inspect transcripts and debate edge cases manually. | Compare pass rates, failures, model behavior, tool use, and fallback options. |
| Approve rollout | Changes ship with unclear evidence and fragile ownership. | Promote only qualified prompt packages and runtime mappings. |
| Keep improving | Findings are lost after launch or review. | Failures become regression coverage for future changes. |
Frequently Asked Questions
When should teams use this?
Use ProofMap when the customer renewal creates pressure to prove AI quality, safety, cost, or reliability before a decision.
How does this help developers?
Developers get repeatable tests, concrete failure evidence, and approved mappings instead of rebuilding confidence from raw logs.
What gets approved?
Prompt packages, model choices, MCP tool access, fallback routes, and runtime mappings can all be qualified before production use.
What is the outcome?
Teams get evidence for retention conversations backed by evaluation data rather than guesswork.
Qualify the workflow before it matters
Use ProofMap to turn this moment into testable AI readiness evidence.
Start qualifying prompts