Catch RAG Regressions Before Users Search
RAG quality shifts when content, retrieval, prompts, or models change. ProofMap helps teams test the full behavior, not just retrieval scores.
Get StartedWhy Choose ProofMap
Test answer quality
Evaluate whether retrieved context leads to correct, grounded, useful responses.
Detect retrieval drift
Find cases where new indexes, embeddings, or chunking strategies change outcomes.
Approve changes safely
Promote RAG updates only after they pass workflow-specific criteria.
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 RAG need regression testing?
RAG systems depend on changing content, retrieval settings, prompts, and runtime behavior, so quality can drift silently.
Can ProofMap test retrieval and generation together?
Yes. It evaluates the outcome of the full agent or workflow, including context use and final answer quality.
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.
Protect RAG quality
Test retrieval changes before they become user-facing regressions.
Start qualifying prompts