For RAG systems already built

Find why retrieval fails — and which fix actually works.

Benchmark your current retrieval against realistic alternatives on your own data. See improvements, critical regressions and the exact configuration your team should implement.

Run a free retrieval audit View audit pricing

Your corpusYour query patternsNo production credentials

The questions an audit answers

Make the change with evidence, or avoid it with confidence.

Should we switch embedding models?

Would hybrid retrieval recover our identifiers?

Is re-chunking the corpus worth the migration cost?

Does reranking improve retrieval enough to justify a production latency test?

Need a retrieval evaluation?

Measure whether the right source is found before judging the answer.

Retrieval evaluation isolates the context-selection problem from answer quality and makes query-level evidence visible.

Explore RAG evaluation

Choosing an embedding model?

Compare it on your corpus before you re-index.

Keep the corpus, query set and retrieval conditions fixed so you can see which gains and regressions belong to the model.

Compare embeddings

Current → candidate → decision

Benchmark the fixes that can materially change retrieval.

RetrievalGate runs a bounded, opinionated comparison. The goal is enough evidence for a production choice, not an endless parameter search.

LayerCurrentCandidatesDecision signal

ChunkingYour setupFixed + structuralRecall by document type

EmbeddingsCurrent model2–3 realistic modelsGain and regression

RetrievalDense baselineBM25 + hybridExact vs semantic

RerankingOff / currentOne rerankerQuality vs added cost

Bring real evidence when you have it

Queries plus relevant documents change the quality of the answer.

Add a CSV containing a query and its relevant document. RetrievalGate can then measure the failures that matter to your users instead of relying entirely on synthetic questions.

query,relevant_idHow do I cancel?,termination.mdWhat is part 28-5147?,parts.csv

The output

An explicit release verdict.

GOGO WITH CONDITIONSNO-GOINSUFFICIENT EVIDENCE

Every verdict includes its supporting metrics, affected query segments, limitations and implementation settings.

Audit the retrieval layer

Test the change before you pay the cost of shipping it.

Start with a free snapshot on your own corpus. No SDK, production access or vector database credentials required.

Run a free retrieval audit Benchmark a new RAG