Six practices, one delivery team.
AI and data, cloud engineering, software development, enterprise platforms, quality automation and talent, drawn from the same teams and held to the same standard.
AI, data and cloud
We build AI-powered systems, data platforms and cloud infrastructure as production engineering work, not as experiments. That means monitoring, cost controls and governance from the start, not added when something breaks.
- LLM and AI agent development
- RAG pipelines and vector search
- Data lakehouses and real-time pipelines
- MLOps and model monitoring
- Cloud migration and infrastructure
- FinOps and cost architecture
Application engineering and modernization
Custom software from prototype to production, and modernization of systems that need to keep running while they change. Web, mobile, API and backend work, built by engineers who have done it in your sector before.
- Web and mobile application development
- API design and backend engineering
- Legacy system modernization and replatforming
- Cloud-native architecture
- Microservices and event-driven design
Quality engineering and automation
Test strategy, automation frameworks and performance engineering built into the delivery pipeline. We also do SDET work for teams that need engineers who sit at the intersection of development and testing.
- Test automation and SDET
- Playwright, Cypress and Selenium frameworks
- API and contract testing
- Performance and load testing
- CI/CD pipeline quality gates
- Shift-left testing practices
Enterprise platforms and integration
Implementation and integration of the systems a business runs on. Salesforce, ServiceNow, SAP, connected to each other rather than running in parallel with a spreadsheet in the middle.
- Salesforce — Sales Cloud, Service Cloud, Einstein AI
- ServiceNow — ITSM, CSM, ITOM and Now Assist (GenAI service management)
- SAP and ERP integration
- Middleware and data integration
- System-to-system and third-party connections
- AI extensions for enterprise platforms
Technology talent solutions
When the gap is people, we bring in screened engineers who join your team directly. Software, cloud, data, QA, mobile. Employed by us, under your direction, for as long as the engagement needs them.
- Software and cloud engineers
- Data and AI specialists
- QA and SDET professionals
- Screened for domain fit before technical depth
- Scales with the programme
Consulting and advisory
For teams that need a second opinion on a direction, a technology assessment or a roadmap before they start building. Assessments come with a plan, not just a set of findings.
- Technology strategy and roadmap
- Architecture assessment and modernization planning
- Vendor and platform selection
- Operating model design
How we run
an engagement.
A structured process, so you know exactly what happens between the first conversation and the first delivery, whatever shape the engagement takes.
Discovery and scoping
We identify the requirements, constraints and definition of success, then map that against a realistic delivery shape, so the engagement is scoped against reality rather than a job title or a feature list.
Team and approach
We assemble the right mix of consulting, engineering and specialist capability for the problem, drawing on our existing teams first and bringing in additional depth where the requirement calls for it.
Technical validation
Architecture review, technical interviews and, where relevant, a short proof of concept, all before the plan is locked in and work begins at scale.
Onboarding and ramp up
Access, context and documentation handed over so the team is productive from the first sprint, not the third.
Governance and compliance
Security review, IP terms and regulatory requirements handled up front. See Partnering with us for the detail.
Ongoing quality
Regular check ins with both the people on the ground and your team, so small issues, technical or otherwise, get resolved before they affect the outcome.
What we actually
do differently.
Assessment before architecture
Before we propose a technical direction on a build, we spend time understanding what the current system does well, what it does poorly and why it was built the way it was. That context usually changes the recommendation.
AI augmented, human verified
Our engineers use AI assisted tooling for code generation, test authoring and documentation where it genuinely speeds delivery, with every output reviewed by a senior engineer before it ships. The tooling changes; the review discipline does not.
Documentation as a deliverable
Architecture decisions, runbooks and handover documentation are produced throughout an engagement, not assembled at the end from memory. A client should be able to operate what we build without calling us first.
AI that is built to run, not to demo
When we put a language model or an agent into a system, it goes through the same engineering rigour as anything else: latency budgets, fallback behaviour, cost monitoring and human review checkpoints. We have seen enough failed AI projects to know the difference between a working demo and a production feature.
The specialists
we field most.
AI and ML engineers
Cloud and platform engineers
Data engineers
Software engineers
DevSecOps engineers
QA automation and SDET
Enterprise platform specialists
Product and delivery leads
Tell us what you are building. We will show you how we would deliver it.
One conversation is usually enough to tell whether we are the right partner. If we are, we will come back with a clear plan. If we are not, we will tell you that too.
Talk to us →