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The evidence behind

every claim we make.

No figure on this page ships without its source, its sample size and its date. Run the same benchmark yourself, or bring your own documents and see where you land.

Coming soon

RAG evaluator

Upload your own documents, pick your models, and run this exact benchmark against them. The evaluator is in build.

See for yourself.

This page shows results on different public benchmarks. We're the best on every one we've run. Toggle between them and check the evidence yourself.

  • 93/96 correct Two full runs of the question set (47 of 48 and 46 of 48), including the control question declined in all six repetitions.
  • 100% retrieval accuracy A correct source document reached for every answerable question, every repetition.
  • 40/48 most correct of five retrieval approaches, same documents, same questions, same model GPT-5.4 mini answering for every system: Hippocampus 40, OpenAI File Search 36 (average of two runs), PageIndex 33, OpenAI vector store search 29, the model alone 15.

Head to head

Which system gets the most answers right on the same documents?

Read the full report
  • Hippocampus 0.0% 40 of 48
  • OpenAI File Search (average of 2 runs) 0.0% 36 of 48
  • PageIndex 0.0% 33 of 48
  • OpenAI vector store search 0.0% 29 of 48
  • The model alone 0.0% 15 of 48

Result deep dive

Lookups are easy for everyone; the differences are elsewhere.

Every system with document access answered most of them (19 to 24 of 24), and the model alone answered half from its own knowledge, since these are public documents. Single-fact lookups separate the systems only a little.

See it on your own documents.

Free tier, no card, no API key. Import one document and ask it the question the alternatives get wrong.