Company
We connect the deepest context in the enterprise.
DeepRAGs was founded in 2026 by a team of retrieval, graph, and distributed-systems engineers who were tired of watching RAG break at enterprise scale.
What we believe
Context over keywords
Vector similarity is a starting point, not an answer. We model the relationships between facts so retrieval reasons, not just matches.
Federation by default
Enterprise knowledge lives in dozens of stores. We bring retrieval to the data instead of forcing fragile, lossy migrations.
Security is the product
Air-gapped images, data masking, and isolation aren't add-ons. They're how a knowledge engine earns a place in regulated environments.
Our mission
Every organization is sitting on an ocean of fragmented knowledge — documents, databases, tickets, code, and conversations that never connect. DeepRAGs exists to make that entire estate queryable as a single, reasoning-capable knowledge engine, so teams can ask their enterprise anything and get an answer grounded in the deepest available context.