Qualify AI Runtimes for Data Residency
Regional and data residency requirements can limit model choices. ProofMap helps teams test which approved runtimes still meet quality goals.
Get StartedWhy Choose ProofMap
Compare regional options
Evaluate models available in required regions or compliant provider environments.
Test quality tradeoffs
See whether residency-friendly runtimes pass the same product objectives as global defaults.
Document decisions
Keep evidence for why each regional runtime is approved, limited, or rejected.
Comparison
| Workflow | Without ProofMap | With ProofMap |
|---|---|---|
| Evaluate AI behavior | Teams rely on demos, logs, and manual spot checks. | Run objective-bound evaluations against prompts, models, MCP tools, and runtime mappings. |
| Handle change | Prompt, model, context, schema, memory, or vendor changes create hidden regressions. | Compare candidates to baselines and promote only qualified packages. |
| Support developers | Developers trace failures across tools, providers, data, and one-off scripts. | Failures become repeatable tests with clear evidence and recommended fixes. |
| Control production risk | Fallbacks, permissions, and degraded modes are invented when pressure hits. | Approved mappings and fallback paths are ready before launch, incidents, or migration deadlines. |
Frequently Asked Questions
Why does data residency affect AI runtime choice?
Some models or providers may not be available in required regions, which can change quality, cost, or latency.
Can ProofMap support regional fallback?
Yes. Teams can qualify region-specific runtime mappings and fallback paths.
How does this save developer time?
It makes evaluation, debugging, approval, and regression testing repeatable instead of forcing developers to rebuild evidence for every AI change.
What does ProofMap produce?
ProofMap produces objective-bound evaluations, failure evidence, recommendations, and approved prompt or runtime mappings for production use.