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RAG implementations
AI assistants that answer from your own documents and data, with sources cited and access kept private.
Overview
Retrieval-augmented generation (RAG) lets an AI assistant answer questions using your own policies, manuals and records instead of guessing. We prepare your content, set up search over it and build an assistant that cites its sources and respects who can see what.
What's included
- Document ingestion
- Vector search
- Cited answers
- Access controls
Tools we use
- Vector search
- Embeddings
- LLMs
- Python
Related services
Often paired with.
07
AI agent development
AI agents that handle real work — answering customers, processing documents and running tasks across your tools.
03
APIs & integrations
Secure, documented APIs that connect your systems, payment providers and partners.
04
SaaS products
Subscription software taken from a first MVP to a reliable, multi-customer platform.
Need rag implementations?
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