The foundations intelligence needs.
No agent is better than the context it can reach. That is why we do serious data foundations before promising intelligence, and why we wrote the books other teams use to do it.
Modern data foundations
Modelling, quality, governance and analytics engineering with SQL and dbt, by the people who wrote the O'Reilly books on the subject.
Company Brain, the organisation's context
The layer where organisational context lives: definitions, processes, decisions and history, so agents and people work from the same truth.
Self-service analytics with agents
Ask in natural language over governed models, with an answer traceable back to the definition and the data lineage. The dashboard stops being the only route.
Transaction intelligence, with LedgerLens
LedgerLens reads bank transactions over Open Banking, classifies, reconciles and explains variances before the month closes.
The agent layer
Four agents in production.
Modelling
Models, tests and documents.
Quality
Watches lineage and freshness.
Traceable answers
Answers in natural language, with sources.
Reconciliation
Classifies and reconciles transactions.
Client and case
A data and AI company, where the foundation and the agents were built jointly.
Authorship and teaching
Advanced SQL and Analytics Engineering with SQL and dbt, O'Reilly Media, alongside master's-level Data and AI teaching.
How we enter
From framing to the first governed layer in weeks, without replacing the stack that already works.
The position
Own the context, rent the model. This is where the context gets built.