Azure‑native RAG search, API‑first

High-quality file ingestion for better chunking and retrieval.
Flexible retrieval: Vector, full-text, and hybrid querying capabilities.
API-first (no UI bloat): Serverless infrastructure that processes data and requests without paying for SKUs.

Coming Soon

Retrieval that Works Harder
and Costs Less

Ingest unstructured data, including text, images, audio, PDFs, and more, then search it instantly without paying for space you do not use.

Cut the Bulk,
Keep the Brains

RAG.DB is a vector search engine built for AI applications that need accuracy without delay. It handles multiple formats natively, so you skip the manual prep and feed your AI exactly what it needs.

Why Teams Switch to RAG.DB

Scales instantly

Serverless infrastructure that adapts to your load and scales up on-demand

AI-optimized search

Designed for Retrieval-Augmented Generation workflows

Real-time sync

Keeps your index fresh as soon as data changes

Multi-modal ingest

Accepts all major file types and data formats in a single system

Usage-based pricing

Pay only for the data you store and search

The Cost Advantage

Most platforms bill in fixed-size chunks. You end up paying for storage you never use. RAG.DB charges only for actual usage, saving up to 80 percent at the low end and 25 to 30 percent at full scale.

Contact RAG.DB Team