Use Case

RAG Applications

Build retrieval-augmented generation at enterprise scale

Ground every LLM response in your proprietary data. Hanzo's vector database, embedding pipeline, and inference gateway let you build production RAG in hours — not months.

What's included

Every feature you need to ship fast and scale confidently.

Managed Vector Store

pgvector on Hanzo Base — no separate infrastructure. Index billions of embeddings with sub-10ms retrieval.

Embedding Pipeline

Auto-embed documents on ingest. Supports Zen3-embedding, OpenAI, Cohere, and custom models.

Hybrid Search

Combine dense vector search with BM25 keyword search for best-of-both precision.

Context Window Management

Smart chunking, re-ranking, and context compression to fit retrieved knowledge into any model.

Observability

Trace every retrieval step. Debug hallucinations by inspecting exactly what context was injected.

Multi-tenant Isolation

Namespace indexes per customer. Keep enterprise data siloed with row-level security.

Use cases

Real workloads, real teams, real impact.

  • Internal knowledge bases and enterprise search
  • Customer support with grounded, accurate answers
  • Legal and compliance document analysis
  • Medical and scientific literature review
  • Code repository search and assistant

Start building today

Get up and running in minutes. Our documentation covers everything from quick start to production deployment.

Also available on

AWS MarketplaceAzure MarketplaceGCP Marketplace

Enterprise ready

Deploy with confidence

SOC 2 Type II certified. GDPR and CCPA compliant. 99.99% SLA. Dedicated support engineers for Enterprise plans.