Service
Knowledge graphs & GraphRAG
We model your entities and how they connect, so agents answer questions about relationships from your own data rather than the model’s memory, and every answer traces back to a source.
The problem
Why teams come to us
The answers that matter are about connections: which accounts share a device, which issuer came back within a year, which deployment scenario applies here. Keyword search and plain vector search hide exactly those connections.
What we deliver
What you get
Ontology and graph design
An entity and relationship model built with your domain experts, refined with human-in-the-loop review rather than guessed from documents.
Ingestion from every format
Databases, spreadsheets, PDFs, wikis and APIs, validated on the way in so the graph stays trustworthy.
GraphRAG retrieval
Hybrid keyword, vector and graph search, queried by SQL, Cypher or plain English, with the source cited on every answer.
Graph machine learning
Graph neural networks, community detection and embeddings where the pattern is in the structure, as in fraud rings.
In practice
5 engagements where we built this
Banking — 1M+ transactions daily
Fraud detection on a transaction knowledge graph
Enterprise technology — support and field engineering
Knowledge-graph RAG for technical documentation
Agriculture — large-scale livestock production
Knowledge-graph precision agriculture
Healthcare & life sciences — consumer health and nutrition
Personalised meal planning on a nutrition knowledge graph
Blockchain — smart contract developer tooling
Knowledge-graph tuning for a smart-contract copilot
Have a workflow in mind?
Tell us about the workflow and the number you want to move. We will reply with how we would scope the first few weeks.