Services

Architecture services for complex environments.

Five connected service areas. Each one is described by the problem it solves, the work we do, what you receive and when it is worth engaging us.

01 — Service

Enterprise Architecture

Connecting business strategy with technology strategy.

The challenge

The technology landscape has grown organically through projects, acquisitions and tactical decisions. Nobody can describe the current state accurately, investment cases compete with each other, and each programme designs its own version of the future.

What we do

Current-state assessment across business capabilities, applications, data and technology
Target architecture definition aligned to business outcomes
Architecture principles and decision framework
Capability mapping and application portfolio rationalisation
Technology strategy and multi-year architecture roadmaps
Lightweight architecture governance that delivery teams will actually use

What clients get

Current-state and target-state architecture
Architecture principles and standards
Capability model and application portfolio view
Prioritised transformation roadmap
Architecture decision records
Governance model and review approach

When to engage us

A multi-year transformation is being scoped and needs a coherent target
Application estate cost or duplication needs to be reduced
Several programmes are making conflicting technology decisions
An investment case requires an evidenced architecture position

02 — Service

Data Architecture

Designing the data foundations behind modern enterprises.

The challenge

Data is fragmented across operational systems, extracts and spreadsheets. Reporting is contested, the same measure has several definitions, and analytics or AI ambitions are blocked by the state of the underlying data.

What we do

Enterprise data architecture and domain modelling
Data platform and lakehouse architecture
Conceptual, logical and physical data modelling
Data integration, ingestion and CDC patterns
Data product definition, ownership and contracts
Data governance, quality, lineage and cataloguing approach
Data engineering architecture and delivery patterns

What clients get

Target data architecture and platform design
Data models and canonical definitions
Ingestion and integration patterns
Data product catalogue and ownership model
Governance, quality and security controls
Platform build roadmap and delivery patterns

When to engage us

A new analytics or data platform is being designed or replaced
Reporting is inconsistent and definitions are disputed
Data foundations must be strengthened ahead of AI initiatives
Multiple teams are building overlapping pipelines

03 — Service

Solutions Architecture

Turning business requirements into practical technology solutions.

The challenge

A specific initiative needs a design that is deliverable: something that fits the existing estate, meets non-functional requirements, and can be built by the teams available — not an idealised diagram.

What we do

Solution architecture and options analysis
Application and component architecture
Cloud architecture and landing-zone alignment
Integration, API and event-driven design
Non-functional requirements: performance, resilience, security, cost
Legacy modernisation and migration design

What clients get

Solution design documents and component views
Options analysis with trade-offs and recommendation
Interface and integration specifications
Non-functional requirements and test criteria
Migration and cutover approach
Build-ready backlog input for delivery teams

When to engage us

A programme needs a designed solution before build starts
An existing design needs independent review before commitment
A legacy application must be replaced or re-platformed
Systems need reliable integration across boundaries

04 — Service

AI & Data Modernisation

Building the architecture foundations that AI initiatives depend on.

The challenge

AI pilots produce interesting demonstrations but do not reach production, because the data is not trusted, access controls are unclear, and there is no integration path into business applications.

What we do

AI-readiness assessment of data, integration and security foundations
AI-ready data architecture and semantic or knowledge layer design
Generative AI architecture: retrieval, grounding, evaluation and traceability
Data platform and cloud modernisation
Enterprise AI integration into existing applications and processes
Legacy modernisation where it blocks AI adoption

What clients get

AI-readiness assessment and gap analysis
Target AI and data architecture
Reference patterns for retrieval and grounding
Security, access and traceability controls
Modernisation roadmap with sequencing

When to engage us

AI pilots are not progressing to production
Data foundations need strengthening before AI investment
An AI capability must be integrated into core business systems
Independent advice is needed on AI architecture options

05 — Service

Cloud & Integration Architecture

Designing how systems, services and data connect reliably at enterprise scale.

The challenge

Point-to-point interfaces have accumulated over years. Change is slow and risky, failures are hard to diagnose, and cloud migration exposes assumptions that were never documented.

What we do

Cloud architecture across Azure and AWS
Integration architecture and interface standards
API architecture, versioning and lifecycle
Event-driven and messaging architecture
Hybrid connectivity, identity and network design input
Cloud cost, resilience and operability design

What clients get

Cloud and integration target architecture
API and event standards with example patterns
Interface inventory and rationalisation plan
Resilience, observability and operability requirements
Migration sequencing and risk assessment

When to engage us

Integration is the constraint on delivery speed
Cloud migration needs an architecture position before it starts
APIs are proliferating without standards or ownership
Event-driven architecture is being introduced

Engagement model

How we can help.

Engagements are shaped around the decision you need to make and the capacity your teams already have.

Architecture Leadership

Senior architecture leadership embedded in a transformation programme, accountable for architectural direction and decisions.

Architecture Discovery

A time-boxed assessment of the current environment, the constraints and the realistic options available.

Target Architecture

Definition of a target-state architecture, supporting principles and a sequenced roadmap to reach it.

Solution Design

Design of a specific solution, platform or integration, taken to the level of detail delivery teams need.

Architecture Advisory

Independent advice and decision support for leadership teams, design authorities and supplier selection.

Delivery Enablement

Working alongside engineering and delivery teams so the architecture is implemented rather than shelved.

Discuss an Architecture Challenge