Custom RAG Knowledge Base
Your company documents, SOPs, knowledge base — queryable by AI, 100% private.
What is this?
Your data, your AI, your answers
RAG (Retrieval-Augmented Generation) is the technique that makes your AI actually useful for work. Instead of relying on the model's training data alone, RAG lets your AI search through YOUR documents — company SOPs, policy manuals, product specs, client briefs — and generate answers grounded in your actual data, with source citations.
Everything stays on your Mac. Your proprietary data never touches the cloud. No third-party APIs, no data leakage risks, no compliance concerns. Just powerful, private document intelligence running on your own hardware.
We set up the complete pipeline: document ingestion (PDF, Word, CSV, TXT), text chunking and preprocessing, local embedding models, a vector database for semantic search, and integration with Open WebUI so you can query your knowledge base in a familiar chat interface.
Every answer includes source citations so you can verify the information and trace it back to the original document. This is enterprise-grade document intelligence without the enterprise price tag or the privacy trade-offs.
How it works
From documents to answers
graph LR
A[Upload docs] --> B["PDF/Word/CSV
parser"]
B --> C[Text chunker]
C --> D[Embedding model]
D --> E["Chroma/Qdrant
vector DB"]
E --> F[Semantic query]
F --> G[Top-k retrieval]
G --> H["LLM answer
with sources"]
What you get
Everything included
- Document ingestion pipeline (PDF / Word / CSV / TXT)
- Text chunking and preprocessing
- Local embedding model setup
- Vector database (Chroma or Qdrant)
- Semantic search configuration
- Source citation in AI responses
- Open WebUI RAG integration
- Up to 500 pages of initial document processing
- Document update workflow guide
Who is this for?
Built for knowledge-driven teams
Companies
With internal knowledge bases, SOPs, and policy documents that staff need to query.
Legal & Compliance
Teams handling sensitive documents that cannot be uploaded to cloud AI services.
Customer Support
Teams needing instant access to product docs, FAQs, and troubleshooting guides.
Research Organisations
Working with large volumes of papers, reports, and technical documentation.