What we build · Insights layer
AI and machine learning
We apply AI and machine learning to find the patterns, risks and forecasts people miss, and put them where decisions are made.
Talk to an architectFig. 1 — The intelligence pyramidSection A–A
- Intelligence05 What should we do?
- Insights04 Why, and what comes next?
- Knowledge03 How does it all connect?
- Information02 What is happening?
- Data01 What do we hold?
- Open by designUnder every layer
[01] The worry it answers
Pilots that never reach production
Every problem starts by asking where models can see what people cannot, and where human judgement must lead.
[02] What we build
Models find patterns, risks and forecasts.
- 01AI-first, judgement-led
Models where they see what people cannot; people accountable for the call.
- 02In production, not in pilots
Models built to run every week on governed data, with tests that keep them honest.
- 03Graph analytics
Centrality, communities, paths and link prediction; graph features for machine learning where they earn their place.
WHAT YOU SEE → ML and AI in production, not stuck in pilots; people accountable for the call.
[03] Tools and standards
Chosen for you, not for us.
Examples, not a preferred list. We use open-source components where they fit, and name every standard and licence in the design.
| Capability | Typical tools and standards |
|---|---|
| Models | Open-weight or commercial models, chosen per use case |
| Graph analytics | Graph data science libraries; graph neural networks where they earn their place |
| Evaluation | Tests for accuracy and groundedness on your own questions |