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We build RAG-based AI systems that are fast, grounded, and secure.


RAG (retrieval-augmented generation) connects large language models with your own data — so your AI assistant or automation can deliver real answers, not just predictions.

Use cases

AI assistants with internal document search

Smart support bots with source citations

Private, role-based knowledge tools

Custom integrations with Notion, Airtable, Drive, or your stack

Curious if RAG makes sense for your product or workflow?

Let’s map it out together.