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Every stalled AI programme we have been called into stalled in the same place: not on the model, but on the data underneath it.
Nobody stalls a programme on purpose. It stalls because no one can say where a number came from, who owns it, or whether it is safe to use — and every model built after that inherits the doubt. So this is the half we do first.
The estate does not have to be perfect. It has to be explainable — to an auditor, to a model, and to whoever is on call at three in the morning.
A constant, heavy data influx with governance and quality handled by hand — and a regulator that does not wait.
Three parts, in order: profiling against defined rules with quality monitoring, standardisation through decomposition and cleansing, then governance enforced where data is created rather than audited after the fact.
Ask three teams for last quarter's figure and get one answer, with a name against it.
Every field traceable back to source, with impact analysis before a change ships.
Profiling and rules run inside the pipeline, not in a board pack after the fact.
Observable, tested and recoverable — supported like any other production system.
The unglamorous half, and the one that decides whether the second ships. Two areas — the governance and modelling that make data trustworthy, and the platforms that carry it to the people and systems that need it.
Data Management & Governance
Ownership, policies and stewardship that fit your operating model — decision rights and a working council, not a policy document nobody opens.
A model inventory, approval gates and human oversight, so every model in production has a named owner, a documented purpose and a review date.
A target-state blueprint for how data moves and where it lands, with a sequenced path from the estate you have to the one you need.
Conceptual, logical and physical models that carry the business definitions with them, so the same term means the same thing in every report.
A catalogue and end-to-end lineage — every field traceable back to its source, with impact analysis before a change ships.
Profiling, rules and remediation wired into the pipeline, with quality measured continuously rather than discovered in a board pack.
Golden records for customers, products and vendors, with survivorship and stewardship workflows that keep them golden.
Classification, access control, masking and retention aligned to your regulatory obligations across every environment.
Data Platforms & Integration
Lakes, lakehouses and operational stores sized to your workloads, with cost, performance and retention managed as ongoing concerns.
EDW optimisation and a shared semantic layer, so teams answer their own questions instead of raising a ticket for every report.
Batch, streaming and API integration across your estate, with contracts between systems that survive the next migration.
Unstructured content brought into the same governed estate — extracted, classified and made searchable alongside your structured data.
CI/CD, observability and drift monitoring for pipelines, models and agents, so what runs in production stays healthy and explainable.
Tell us where your estate is today and we will tell you what the first ninety days look like.