Manufacturing - Global OEM
Connected factory across 40 plants on 18 countries' production lines.
Shared industrial data and AI-driven operations cut unplanned downtime 23% and released $180M in annualised inventory.
Build / AI & data
AI & data that changes the economics, not just the demo.
We build the data foundations, model-delivery systems, and workflow redesign required to make AI valuable in production. The goal is not more experimentation; it is better decisions, faster operations, and accountable commercial impact.
What this service category is built to do.
Most enterprises do not lack AI ideas. They lack a reliable path from fragmented data and isolated proofs of concept to governed workflows that teams will actually use. We start by building a data and decision spine that can support real operating change.
Our AI & data work blends platform engineering, analytics, model operations, and product delivery. That means data estates get cleaner, governance gets tighter, and the AI layer is connected to the workflow metrics executives care about rather than parked in a lab.
Talk to an AI & data leadThe strongest AI programmes connect governed data, production model operations, and workflow redesign into one operating system for value.
Outcomes we manage to
The build metrics clients hold us to.
75%
of AI engagements start with an explicit P&L or cycle-time commitment
140+
enterprise data estates modernised across cloud, hybrid, and regulated environments
<90 days
to first production workflow value in accelerated delivery tracks
35%
median cycle-time improvement where models are embedded directly into operations
Core capabilities
The workstreams inside the build model.
Capability 01
Data foundations and engineering
Lakehouse, streaming, master data, and governed pipelines built for reliability, discoverability, and reuse.
Capability 02
Applied analytics and decisioning
Forecasting, optimisation, and decision-support products wired into the places where operators and customers feel the outcome.
Capability 03
Generative AI in production
Retrieval, prompt management, evaluation, guardrails, and supervision loops that survive beyond the pilot stage.
Capability 04
MLOps and AI governance
Model lifecycle controls, observability, lineage, and release discipline that let AI scale without losing trust.
How we operate
A disciplined rhythm from opportunity to scaled adoption.
Phase 01
Find the value pool
We identify where better data and AI-driven decisions can change revenue, service levels, cost-to-serve, or operational risk materially.
Phase 02
Build the decision spine
Data contracts, pipelines, governance, and reusable model services are assembled so teams can ship reliably instead of rebuilding the basics.
Phase 03
Industrialise the workflow
Models, user experience, supervision, and measurement are delivered into the live process so adoption and economics improve together.
Where it shows up
See all case studies
Case studies that map to this service.
Energy - European utility
Grid-edge intelligence across 9 countries.
Signal fusion and dispatch intelligence reduced outage minutes 41% while speeding renewables integration.