Semantic data models
The entities, relationships and definitions your domain actually uses, written down so systems can share them.
Services
Knowledge graph consulting and development
We design and build knowledge graphs, semantic data models and graph-based AI systems that connect information spread across different systems and sources.
When a knowledge graph helps
- Information sits in several systems that do not share identifiers.
- The relationships between things matter as much as the things themselves.
- Answers need to be traceable back to their sources.
- AI systems need connected context to reason over, not isolated documents.
What we build
Data integration into a graph
Pipelines that bring records, documents and sensor data together with consistent identities and provenance.
Entity and relationship extraction
Turning text and semi-structured sources into entities and relationships, with the source kept for each one.
Graph analytics and graph machine learning
Embeddings, link prediction and pattern discovery on top of the graph.
Interfaces and APIs
Ways to query, explore and visualise the graph, and to feed it into other AI systems.
How a project runs
Every project follows the same four steps.
- 01Understand
- 02Build
- 03Validate
- 04Deploy
Where we have applied it
Research
ReviewGraph
A peer-reviewed framework that turns customer reviews into a knowledge graph and predicts review ratings from graph embeddings and sentiment.
Read the research →Research
Vink Drug
Biomedical knowledge graphs that keep known evidence apart from model predictions.
See Vink Drug ↗