Services
Five directions, and the honest version of what each one involves.
35 capabilities across five categories. Most engagements begin in one and move into the others — a discovery becomes a build, a build becomes a managed service. We have organised these the way work actually flows rather than the way an org chart does.
Product strategy and discovery
Decide what to build, and what deliberately not to build, before spending on engineering.
User research and service design
Understand the whole service, not just the screens.
UX/UI and design systems
Interface design that specifies every state, not just the demo state.
Corporate and product websites
Marketing sites that are fast, editable and actually convert.
SaaS, portals, marketplaces and platforms
Multi-tenant, authenticated products where isolation and permissions are the hard part.
Native and cross-platform mobile apps
Apps built for real devices, real networks and real store review.
Legacy application modernisation
Replace or refactor an ageing system without stopping the business.
API and integration engineering
Make systems talk to each other reliably, including the ones you do not control.
Data and platform migrations
Move data between systems with evidence that nothing was lost or corrupted.
Application re-architecture
Change the shape of a system so it can absorb the next five years of change.
Cloud-native transformation
Move to cloud in a way that reduces cost and risk rather than adding both.
AI opportunity and readiness assessment
Find the use cases worth funding, and prove your data can support them.
Generative AI applications
Production applications with grounding, guardrails and a defined failure mode.
Enterprise search and RAG
Answers grounded in your documents, with citations and respect for permissions.
AI agents and copilots
Assistants that take real actions, within boundaries you set.
Voice and conversational AI
Conversational interfaces on the channels your users already use.
Document intelligence
Extract structured data from documents, with a confidence threshold and a review queue.
Workflow and process automation
Remove the re-keying, the chasing and the spreadsheet in the middle.
AI evaluation, observability and governance
Know whether your AI is working, and be able to prove it.
Azure, AWS and Google Cloud architecture
Architecture chosen against your constraints, not a vendor reference diagram.
Landing zones and infrastructure as code
Foundations defined as code, so environments cannot drift apart.
Containers, serverless, networking, identity and security
The runtime layer, built to a least-privilege default.
GitHub and Azure DevOps CI/CD
Pipelines that make the safe path the fast path.
Internal developer platforms
Paved paths so teams ship without re-deciding the same things.
DevSecOps, test automation, release governance and observability
Controls that run automatically instead of arriving as a spreadsheet.
Reliability, disaster recovery, FinOps and performance
Recovery objectives that have been tested, and costs that have been attributed.
Data engineering, analytics, BI and AI-ready data platforms
Trusted data, with lineage and quality tests, ready for both reporting and AI.
Managed engineering
A standing team that maintains and extends your product.
Application and cloud support
Defined severities, response targets and a route to a person.
Monitoring and incident response
Detect problems before your users report them, and learn from each one.
Security patching and dependency management
Stay current deliberately rather than in an annual panic.
Performance and cost optimisation
Keep the product fast and the bill proportionate as usage changes.
Product backlog enhancement
Reserved capacity so the product keeps moving forward.
Fractional CTO and platform leadership
Senior technical leadership at the fraction you actually need.
Quarterly health and roadmap reviews
A structured look at whether the product is actually healthy.
How the work runs
Whichever service you start with, the lifecycle is the same
- 01
Explore
Understand the idea and whether we are the right team for it.
- 02
Shape
Paid discovery that replaces assumptions with evidence.
- 03
Design
Make it real enough to test before it is expensive to change.
- 04
Build
Iterative engineering with quality automated from day one.
- 05
Validate
Prove it works — for users, under load, and against attack.
- 06
Launch
Go live deliberately, with a way back.
- 07
Grow
Use evidence from real usage to decide what happens next.
- 08
Operate
Keep it secure, available, affordable and improving.
Next step
Not sure which of these you need?
That is the normal starting position, and it is what the Project Architect is for. It asks about the problem rather than the service, and recommends a direction at the end.