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Services / Data & Artificial Intelligence

Data & Artificial Intelligence

Governed AI that is wired into the way you work.

We pick the right use cases, put governance around them from day one, keep people in control of important decisions and connect AI to your data and workflows so it changes how work gets done.

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What we do in data & artificial intelligence

Generative AI, copilots and agentic automation

Generative AI, copilots and agentic automation

Secure assistants and agents that act across systems, with permissions, logging and human approval gates.

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AI governance, risk and compliance

AI governance, risk and compliance

Policy, AI inventory, risk tiers and oversight, mapped to ISO/IEC 42001, NIST AI RMF and the EU AI Act.

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Data foundations and advanced analytics

Data foundations and advanced analytics

Clean, governed data, dashboards and models that AI can rely on.

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AI Prototyping and MVP Development

AI Prototyping and MVP Development

From a working prototype to a minimum viable product, built on real data with governance from day one.

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Enterprise AI

Enterprise AI

Secure, governed AI built into enterprise workflows.

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A proven path for data & artificial intelligence

  1. 01

    Assess

    Review data, processes, skills and risk.

  2. 02

    Prioritise

    Rank use cases by value, feasibility and risk.

  3. 03

    Prototype

    Prove value on real data in weeks.

  4. 04

    Govern

    Add controls, testing and human approval before launch.

  5. 05

    Scale

    Integrate, train, monitor and extend.

Insights on data & artificial intelligence

Executive and risk manager discussing AI governance in an office corridor
Guide

AI governance, risk and compliance: the complete guide

Governance is not a brake on AI. It is the set of rules, owners and checks that lets you use it at scale and defend what it does. A practical 90-day plan.

AI governance, risk and compliance / 6 min read

Support team reviewing an AI-suggested reply before sending
Guide

Generative AI, copilots and agentic automation: the complete guide

Generative AI drafts and answers; agents plan and act. How to choose use cases, deploy copilots safely, automate documents and set limits that keep agents in check.

Generative AI, copilots and agentic automation / 6 min read

Team preparing to launch an MVP to real users
Article

From prototype to MVP: what changes

A prototype shows that something can work. An MVP must work reliably for real users, with proper security, real integrations, named owners and monitoring from day one.

AI Prototyping and MVP Development / 5 min read

Team agreeing success measures for a prototype
Guide

Writing success measures before you build

Agreeing how you will judge a prototype before you start prevents arguments later. Pick the metric, set the threshold and write the stop rule on day one.

AI Prototyping and MVP Development / 6 min read

Team working through a readiness checklist for a predictive model
Checklist

Predictive analytics: is your problem ready?

Prediction needs history, consistency and a decision that will change as a result. Use this checklist before you commission a forecasting or machine learning model.

Data foundations and advanced analytics / 3 min read

Team agreeing shared definitions at a whiteboard
Perspective

Definitions matter more than tools

If sales and finance define revenue differently, no analytics platform will settle the argument. Agreed, published definitions do more for data quality than any new tool.

Data foundations and advanced analytics / 4 min read

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