Services  ·  Digital transformation  ·  AI, cloud, data

Engineering business outcomes, not projects

Cloud, enterprise AI, data engineering and automation — connected to the business problem they were bought to solve.

Start With Your Objective See how we work
Capabilities
Eight areas
Framework
Six stages
Industries
Six sectors
Outcome
One connected enterprise

01 — Challenge

Six constraints that stall transformation

Legacy

Systems built for yesterday

They limit today's integration and tomorrow's scale.

Data

Fragmented information

No single view, so decisions wait.

Operations

Disconnected workflows

Cost rises, productivity does not.

Intelligence

AI not yet ready

No governed data foundation underneath.

Cloud

Migrated, not modernized

Same architecture, new invoice.

Agility

Change costs too much

Every shift needs a reengineering project.

Technology creates value when it changes how the business performs.

02 — Sequence

Foundation, then intelligence, then reach

FoundationBuild the ground first
Cloud modernizationData engineeringDigital engineering
▼
IntelligenceThen make it think
Enterprise AIIntelligent automationIgnis AI platform
▼
ReachThen put it in hands
Experience designIndustrial IoTAdoption
An AI programme without the data foundation stalls at the pilot. Order matters more than the shopping list.

Most engagements start in one layer and pull in the next.

03 — Framework

Problem to durable capability

01

Discover

Objective, people, constraint.

02

Assess

Landscape, data, risk, readiness.

03

Design

Experience, architecture, operating model.

04

Engineer

Secure, integrated, built to evolve.

05

Deploy

Controlled release with the teams who run it.

06

Optimize

Strengthen what production proves works.

Optimize feeds Discover. New priorities come from what production reveals, not the original plan.

04 — Cloud

Migration is not modernization

Rehost

Same architecture, new location.

➞
Replatform

Managed services, less to operate.

➞
Refactor

Cloud-native where it earns its cost.

➞
Rebuild

Only where the constraint demands it.

Lift and shiftCloud-native
Cost follows architecture. Rehosting moves the bill; it rarely reduces it.

05 — Automation

From scripts to intelligent workflow

Level 0Manual

People move work between systems.

Level 1Scripted

Fixed rules, brittle to change.

Level 2Orchestrated

Workflow engine owns the process end to end.

Level 3Intelligent

Decisions informed by models, exceptions routed to people.

Level 4Adaptive

The process tunes itself within defined limits.

Simplify before you automate. Automating a broken process makes it fail faster.

06 — Readiness

What has to be true before AI ships

Use case

A decision worth improving.

Value + feasibility
Data

Available, owned, documented.

Quality + lineage
Platform

Somewhere to build and run it.

Security + access
Adoption

Someone who will act on the output.

Production

Monitored, owned, funded.

Every gate is a stop. Skipping one is how pilots become permanent pilots.

07 — Effort

Where transformation effort actually goes

LeastShowcase AIThe demo everyone remembers. A fraction of the work.
SomeModels & automationOnly as good as the two layers beneath.
MoreIntegration & workflowConnecting systems that were never meant to meet.
MostData & platformUnglamorous, and where programmes are won or lost.
Budgets are usually shaped like the top of this pyramid. Delivery is shaped like the bottom.

The mismatch is the most common reason a transformation stalls in year two.

08 — Operating model

Done to you, or done with you

Project model

Delivered, then handed over

  • Fixed scope and end date
  • Capability leaves with the vendor
  • Change requests for every shift
  • Success measured at go-live

Works for bounded, well-understood change.

Product model

Owned, then improved

  • Standing team against a roadmap
  • Capability stays in the business
  • Priorities reset each cycle
  • Success measured in production

Works when the thing being built will keep changing.

Most transformations need both, in different places.

09 — Rollout

One wave at a time

Pilot

One site, one process, real users.

Evidence of value
Wave 1

Adjacent teams, same pattern.

Operating model holds
Wave 2

Scale across regions.

Support model in place
Standard

The new default way of working.

Big-bang rollouts fail quietly. Waves give you a point where stopping is still cheap.

Each gate is a decision to continue, adjust or stop.

10 — Capabilities

Eight capability areas

01

Cloud Modernization

Resilient, scalable platforms built for continuous change.

  • Strategy and assessment
  • Application modernization
  • Hybrid and multi-cloud
  • DevSecOps and governance

02

Enterprise AI

AI inside enterprise data, governance and security.

  • Generative AI and copilots
  • AI agents and RAG
  • Knowledge search
  • AI governance

03

Data Engineering & Analytics

Governed foundations for analytics, automation and AI.

  • Lakehouse and pipelines
  • Microsoft Fabric, Databricks
  • Governance and MDM
  • BI and reporting

04

Intelligent Automation

Workflows that connect people, process and systems.

  • Hyperautomation
  • Process intelligence and RPA
  • API integration
  • Document automation

05

Digital Engineering

Platforms that evolve without a rewrite.

  • Enterprise applications
  • Platform and API engineering
  • Microservices
  • Modern architecture

06

Experience Design

Adoption depends on whether people can use it.

  • UX research
  • UI design
  • Design systems
  • Accessibility

07

Industrial IoT

Operations connected to real-time intelligence.

  • Smart manufacturing
  • Asset monitoring
  • Edge computing
  • Predictive maintenance

08

Ignis AI Platform

Enterprise knowledge, agents and workflow in one place.

  • Enterprise search
  • AI agents
  • Workflow intelligence
  • Business insight

11 — Industries

Six sectors, different constraints

Manufacturing

Connected operations

Production, enterprise and industrial data in one picture.

Financial services

Secure operations

Modernize while governance and resilience strengthen.

Healthcare

Connected care

Interoperability inside regulatory requirements.

Retail & CPG

Connected customers

Commerce, inventory and engagement together.

Energy & utilities

Resilient operations

Assets, field work and enterprise data joined up.

Public sector

Services that scale

Accessible, secure, delivered faster.

12 — Engagement

Four ways to start

Assessment

Landscape, readiness and a prioritised roadmap.

➞
Focused build

One capability, delivered end to end.

➞
Programme

Multiple workstreams under one architecture.

➞
Managed

We run and evolve the platform.

WeeksOngoing

What changes

Measured in performance, not deployments

Operations

LeanerManual effort falls as workflows connect and automation takes the repetitive load.

Decisions

SoonerTrusted data reaches the people making the call while it still matters.

Platform

ReadierModern foundations make the next capability an increment, not a programme.

FAQ

Frequently asked questions

They help organizations modernize operations through cloud, AI, automation, data engineering and digital platforms, to improve efficiency, strengthen decision-making and support long-term growth.
With an assessment of the current technology landscape, business priorities, operational constraints and future objectives. The output is a roadmap tied to measurable outcomes.
Migration moves workloads. Modernization redesigns applications, infrastructure, integration and operations to improve resilience, security, scalability and long-term value.
AI is most effective with trusted data, connected workflows and clear governance. It should improve business processes and employee decisions rather than operate in isolation.
Yes. Modernization can improve integration, user experience, cloud readiness and data access while preserving functionality the business relies on.
Enterprise AI, SAP ecosystems, SAP Business Data Cloud, Microsoft Fabric, Databricks, Azure, AWS, cloud-native engineering, automation and data platforms.

Work with us

Start with the business objective

Legacy modernization, enterprise AI, or the next cloud initiative — we can help define the right path and the order to take it in.

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