Internal RAG Solution: Document Base + LLM

Internal RAG Solution: Document Base + LLM

A RAG solution lets you query your documents (PDF, Word, wiki, FAQ) via a conversational assistant. The LLM relies on the actual content of your files, not its general knowledge — contextualized and sourced answers.

What we set up

• Ingestion: text extraction, chunking, embeddings

• Vector store: storage and semantic search (e.g. ChromaDB, Qdrant, pgvector)

• LLM: local model or API (OpenAI, Mistral, etc.) depending on your GDPR constraints

• Interface: chat or API to integrate with your tools (intranet, Slack, etc.)

Typical use cases

• Internal assistant for HR, legal, support

• Search across technical docs, procedures, FAQ

• Decision support on internal data

Deliverables

• Configured and documented ingestion pipeline

• Operational vector store

• Q&A interface (or API)

• Operations and maintenance documentation

On quote. Duration depends on document volume and desired complexity.