Data foundations
Catalogues, definitions, lineage, and quality rules that finance, operations, and audit can share.
Architecture-first platforms for startups and growing organisations
Estimate a programme
Services
Dashboards on dirty data are theatre. We put lineage, quality, and access control underneath the pretty picture — then we put the picture in the hands of people who must act.
The problem
Every department has a spreadsheet that disagrees with every other department’s spreadsheet. Leadership asks for a dashboard. What they need is a definition of the truth and someone accountable for it.
Approach
Definitions first. Then pipelines, quality rules, access, and only then visualisation. Where AI is useful — classification, anomaly, briefing — it sits on that governed layer, not instead of it.
Catalogues, definitions, lineage, and quality rules that finance, operations, and audit can share.
Warehouses, lakes, and serving layers sized to the organisation — not a hyperscale fantasy on a seed or SME budget.
Operational reports, executive packs, and exception queues tied to the workflow that will use them.
Models and agents that consume governed data, with explanations a founder or director can interrogate.
Outcomes we design for
Who this is for
Other practices
A target operating model and system landscape that startups and organisations can actually run.
Intelligent workflows and multi-agent systems that move real work — with humans still in command.
Identity, architecture, detection, and response designed so compromise is expensive for the adversary — not for you.
Next step
If the work needs architecture, security, and a team that will still be there at go-live, we should talk. Discovery conversations are with a senior architect — not a queue.