Precision RAG, Tailored to Your Data
The managed RAG platform that builds custom AI search models for your content. Deliver hallucination-free, truthful answers with unparalleled accuracy
API or Discord: Upload data, deploy RAG. No friction, pure development focus.
RAG-optimized search core, architected by Yandex veterans. Unparalleled retrieval precision.
Custom models evolve with your data. Continuous fine-tuning ensures peak search relevance.
How QuePasa Works
-H "Content-Type: application/json" \
-H "Authorization: Bearer $QUEPASA_API_KEY" \
-d '{
"engine": "answer",
"question": "Can I un-eat yesterday burrito?"
}'
# Use "engine": "answer" for RAG
# or "engine": "search" for chunks
Inside RAG
QuePasa Under the Hood
Semantic chunking algorithm splits documents into independent chunks. Each chunk = one complete meaning, ample context.
Custom domain-specific semantic core + third-party embedding models create multiple vectors per chunk. Our models are fine-tuned on your data for sharpened precision.
Fine-tuned taxonomy classification models extract class tree for each chunk, generating a unique knowledge graph.
Data enriched with domain-specific search features (FinTech, MedTech, Law and many more) to enhance filtering and search quality.
Custom, data-tuned gradient boosting formulas power hybrid search, delivering best-in-class results.
Final pass through a custom, fine-tuned reranker selects optimal top-k results for LLM context.
Top-tier language models, equipped with domain-specific lexicons, minimize hallucinations and maximize accuracy.
Pricing
out of the box
up to 100Mb storage
and medium business projects
up to 1Gb storage
API queries
with complex customization