RAG & Knowledge Systems
Give your AI access to what your company knows.
Retrieval-Augmented Generation (RAG) connects your LLM to your private knowledge — documentation, contracts, tickets, product data — so it gives accurate, contextual answers rather than hallucinating. We build production RAG systems that scale.
What we deliver
Every engagement is scoped, priced, and delivered against these capabilities.
Vector Store Architecture
Design and implement vector databases (Pinecone, Weaviate, pgvector) with optimal chunking, embedding, and indexing strategies for your content type.
Hybrid Search
Combine semantic vector search with keyword (BM25) search for best-of-both retrieval — especially effective for technical and domain-specific content.
Advanced RAG Techniques
HyDE, query rewriting, re-ranking, contextual compression, and multi-query retrieval. We implement the technique that fits your accuracy requirements.
Document Ingestion Pipelines
Automated ingestion from Confluence, Notion, SharePoint, S3, databases, and APIs — with automatic re-indexing when documents change.
Access Control & Security
Document-level permissions enforced at retrieval time. Users only see answers grounded in content they're authorised to access.
RAG Evaluation Framework
Systematic evaluation using RAGAS, custom benchmarks, and human review. We measure retrieval accuracy, answer faithfulness, and hallucination rate.
How we work
A predictable process that keeps you informed and in control at every stage.
Knowledge audit
Inventory your knowledge sources, assess quality, and define the retrieval scope for version one.
Pipeline design
Design chunking strategy, embedding model selection, vector store schema, and retrieval configuration.
Baseline & evaluate
Build baseline RAG, run evals on representative queries, and iterate on retrieval quality.
Production pipeline
Automated ingestion, real-time indexing, API endpoints, and monitoring dashboard.
Technologies we use
Vector Stores
Embeddings
Frameworks
Evaluation
Ready for AI that actually knows your business?
Tell us about your knowledge base and we'll design the right RAG architecture.
Response within 24 hours. NDA available on request.