Applied AI in production
We move generative AI past the demonstration stage through retrieval, evaluation, guardrails, and cost control. We also do the integration work that determines whether it survives contact with real users and imperfect data.
AI-first engineering, built to last
Software and applied AI that hold up in production.
We help organisations make difficult technical decisions, modernise systems that cannot simply stop, and put generative AI to work beyond the demonstration stage.
Capabilities
Engineering for the parts that carry risk
We work where architecture, delivery, and operational reality meet. The aim is not a polished demonstration. It is a system your organisation can run, change, and support.
Systems architecture
We design API platforms, consolidate services, and plan migrations for organisations where downtime becomes customer phone calls. We work across hybrid cloud and on-premise environments, starting from the constraints that actually exist.
Engineering practice
We improve test strategy, delivery process, and technical standards so teams can change software with confidence. The work is designed to leave the codebase more maintainable after we have gone.
How we engage
Make the decision before making the investment
We separate deciding what is worth doing from committing to a larger delivery. Each stage has a clear outcome and a clear end.
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Assess the situation
We examine the system, the data, and the way the team works in a short, fixed-scope engagement. The price and questions to answer are agreed before we begin.
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Set out the decision
We deliver a written recommendation and a costed, sequenced plan. You keep it whether or not we work together again. If the work is not worth doing, the assessment says so.
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Build when the plan justifies it
We can deliver the plan as the delivery team or work alongside your engineers. The engagement ends with working software, documented decisions, and a team able to maintain what was built.
Selected experience
Work shaped by operational reality
Our experience spans customer-facing platforms, self-service systems, and engineering tools built around how people actually operate them.
One customer API across every channel
A unified customer API serving web, app, retail, and call-centre journeys for a North American broadband operator, with shared behaviour across channels that had evolved separately.
Self-service for routine enquiries
Appointment and outage journeys that moved routine questions out of the call queue while preserving a clear route to support when self-service was not enough.
Test generation guided by risk
Agent-driven test generation that finds coverage gaps and closes them at the right level of the test pyramid, rather than adding tests wherever they are easiest to produce.
Start with a conversation
Tell us what you are trying to build or fix. If we are not the right people for it, we will say so.