Solutions/Data for AI
Your AI strategyis a data strategy first.
Every agent you build is only as accurate, as safe and as traceable as the data underneath it. Build that foundation once, and every agent works from the same version of the truth as your people.
What a data-first AI strategy gives you
- One version of the truth, for people and agents alike
- Personal and sensitive data kept where it belongs
- Governance that keeps pace as the estate grows
- Every AI answer traceable to its source
A lesson already learned
AI is about to repeat the problem data warehousing solved
Before data warehousing, every report began with someone hunting for the data, writing a one-off extract to get it out, and fixing its quality by hand — then doing it all again the next month. Warehousing solved that by doing the work once, in one governed place, for everyone.
An AI strategy without a data strategy goes straight back to the start. Every agent needs data, so every agent project finds its own, extracts its own and cleans its own. It is the same manual effort, multiplied by every agent you build — and this time the output answers with confidence whether the data was right or not.
Where it goes wrong
The same four problems, once per agent
Finding the data
Each project starts by hunting across systems nobody has mapped, and what it learns about where the data lives stays with that one team.
Extracting it
One-off extracts built for each agent, unmonitored and unowned, copying data into places it was never meant to go.
Fixing its quality
Clean-up done by hand by every team, each a little differently, so two agents give two answers to the same question.
Moving what is sensitive
Personal and confidential information passed to models and services outside your control, and residency broken without anyone deciding to break it.
Data first, then AI
Build the foundation once, and extend your AI from it
The platform
An enterprise data platform in your own cloud, built to serve AI and analytics from the same governed estate.
The corporate models
Data extracted, validated and aligned so one customer, citizen, product or asset is one record, defined once for the whole organisation.
Agent-specific data
Each agent gets the specific dataset it needs, built on top of the corporate models rather than copied out of the source systems beside them.
The agents
Built on that data, inside your environment — so what they can reach is decided by you, and what they say can be traced.
Many agents will need many specific sets of data. Built on the corporate data rather than beside it, every one of them inherits the same single version of the truth, whether an answer is read by a person on a dashboard or produced by an agent.
Safe and secure by design
Agents that only see what they should
- Will personal data reach a model?
- Where does the data go?
- What can an agent reach?
- Can we explain an AI answer?
Governance at scale
An estate too big to govern by hand
Every agent adds datasets, and every dataset adds something to govern. Past a point no team can keep track of it manually, and the risk grows faster than anyone can check it.
A governed platform gives data governance tools — Microsoft Purview, for example — one estate to look across. They can classify sensitive data, map lineage and apply policy automatically, so the risk is managed by the estate itself rather than by people remembering to.
And because people and agents work from the same models, everything that follows is done once: maintenance, lineage, traceability, and the understanding of what a number means. When someone asks why an agent said something, the answer is the one you would give for a dashboard.
Where to start
Start with the data your AI will need
Data, analytics & AI review
Where your data stands, an honest answer on AI, and a costed roadmap. Twelve weeks, fixed scope, fixed price.
Cloud Data Platform
The secure, governed foundation, configured in your own cloud to serve analytics and AI alike.
Data Framework
Extraction, validation and record alignment, ready-built and managed for you on a subscription.
Have an AI strategy? Let us look at the data under it.
A short conversation about where your data stands today and what your agents will need from it.