Turn data into insight, not experimentation

AI delivers value only when it’s powered by trusted, governed, and accurate data. We help organisations create a Single Source of Truth (SSOT), break down siloes, and access near real-time insights that drive confident decisions, optimise services, forecast growth, and position the business competitively. Our approach builds the foundations and operating models needed to move AI initiatives into production and deliver measurable, repeatable business outcomes.

The Problems We Solve

Move from disconnected data and stalled AI to real business impact

Many organisations invest in data platforms and AI tools but struggle to turn them into value. Data grows faster than governance, teams work in silos, and AI initiatives stall after proof of concept. Without clear foundations and a roadmap, results remain hard to measure and scale.

Create a trusted data foundation

Establish reliable, governed data that teams can rely on for reporting, analytics, and AI. We address data quality, ownership, and platform gaps that undermine confidence and slow decision-making.

What this enables

A single, trusted view of business data
Clear ownership and accountability
Reduced data inconsistency and rework
Stronger compliance and auditability
Confidence in operational and executive reporting

Turn AI investment into real outcomes

Move beyond experimentation by aligning AI initiatives to clear business priorities and measurable value. We help organisations focus on use cases that justify investment and can scale safely.

What this enables

Prioritised AI use cases tied to outcomes
Clear success measures and value tracking
Faster path from idea to implementation

Better return on data and AI spend

Operationalise data and AI at scale

Design platforms, governance, and operating models that support production workloads, not just proofs of concept. This ensures insights and AI capabilities can be sustained over time.

What this enables

Faster transition from pilot to production
Near real-time reporting and insight
Secure, scalable data and AI platforms
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Lower operational and compliance risk
Repeatable, measurable outcomes across the business

How Organisations Benefit

Unlock AI and analytics value that scales.

Trusted, governed data that supports confident decision-making

Clear prioritisation of AI use cases tied to business value

Faster movement from proof of concept to production

Improved visibility through reliable, real-time reporting

Reduced risk through strong data governance and controls

AI initiatives with measurable and repeatable outcomes

How it Works

Build the foundations first, then scale what works

We take a pragmatic, staged approach that focuses on readiness, value, and operationalisation — not experimentation for its own sake.

Our process includes:

Step 01

Data Readiness & Maturity Assessment

Assess data quality, governance, platforms, and operating models to understand readiness for analytics and AI.

Step 02

Use Case Identification & Prioritisation

Work with business and technical teams to identify high-value data and AI use cases and define success measures.

Step 03

Platform & Architecture Design

Design modern, scalable data platforms that support analytics, reporting, and GenAI workloads.

Step 04

Governance & Operating Model Setup

Define ownership, controls, and processes to ensure data remains trusted, secure, and compliant.

Step 05

AI Enablement & Productionisation

Move validated AI initiatives from proof of concept into secure, scalable production environments.

Step 06

Ongoing Optimisation & Enablement

Support teams as data and AI capabilities mature, ensuring value continues to compound over time.

Solution & Accelerators

Practical accelerators that move data and AI from concept to business value

DNX Unified Data Platform

A scalable foundation for analytics, reporting, and AI workloads.

DataLabs

Low-risk environments to test, learn, and validate data and AI use cases.

AI Accelerator

A structured path to take AI from idea to production with clear value measures.

Data Strategy Diagnostic

Assess gaps, risks, and opportunities across data, analytics, and AI.

Related Case Studies

Explore how data and AI deliver measurable outcomes

Discover how organisations have improved decision-making, operational insight, and innovation by building strong data foundations and production-ready AI capabilities.

Case Studies

MachShip: Powering Freight Management at Scale with a Future-Ready AWS Cloud Foundation

3rd Dec 2025

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Nuix’s Cloud Migration Journey: Cutting Costs, Reducing Technical Debt, and Scaling with AWS

15th Oct 2025

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emite: Building a Stronger Foundation for Growth

4th Sep 2025