Our services - What we do

Software that works is not the same as software you can trust. Systems reach this point for familiar reasons: the original team has moved on, the build happened at speed, or it was never designed for the load it now carries.

The research is consistent. A scan of over 1,400 AI-assisted production applications found 65% carried security issues, and 58% had at least one critical vulnerability. Maintenance costs on codebases like these have been observed to rise around 300% within eighteen months.

We spend two weeks inside the code and infrastructure, then report in commercial terms. Not “the architecture is inconsistent” — how many engineer-months to support three times the current load, which services have no tests, where the single points of failure sit.

Between 2024 and 2026, roughly ten thousand startups shipped production applications built with AI coding tools. By mid-2026, more than eight thousand needed partial rebuilds or rescue engineering to keep running.

If that describes you — real users, real revenue, a foundation you no longer trust — this is the engagement. We take a system that behaves unpredictably and make it something you can build on: secured, tested, documented, structured so the next feature doesn’t break the last one.

Work is phased. The first phase covers the highest-severity findings in risk order: security, then testing, dependencies, structural debt. Later phases are scoped from what that establishes, so you’re never asked to commit to a number nobody can responsibly estimate yet.

We don’t default to rebuilding. It’s occasionally right and usually expensive, and we’ll tell you plainly which situation you’re in.

We build new products for startups, and for teams inside larger organisations launching outside the remit of the in-house department.

A short discovery phase defines exactly what gets built, and everything after that is agreed in advance. What you receive is not a prototype — a deployed, monitored, documented product running on your own cloud accounts, in a codebase any competent engineer can pick up.

Frontend, backend and cloud deployment come as standard. Native iOS where the product genuinely needs it, and an honest conversation about whether it does. Adding platforms is the quickest way to double a build, and most products shouldn’t.

One product build runs at a time, so the work has full attention throughout.

Most AI projects die somewhere between the demo and production. A model in a notebook and a system serving real users under load are different disciplines, and the gap is where budgets disappear.

We build the second kind. Retrieval over your own documents, agent workflows touching live business systems, extraction and classification pipelines — specified, evaluated against real data, deployed with monitoring, and modelled so you know the monthly spend before it goes live.

We also deploy on infrastructure you own. For regulated sectors, or any organisation that cannot send data to a third-party API, we design and run self-hosted systems inside your own environment. Practical experience here is thin across the market. Ours is deliberate.

For investors and acquirers who need to know what they’re actually buying.

We review the target’s codebase, architecture, infrastructure, security posture and engineering practice, and report in terms a deal team can use: engineer-months required to support the growth in the thesis, dependencies carrying licence risk, where key-person exposure sits, and what the first two years of technical spend realistically looks like.

Available as a full review for platform acquisitions, or a lighter scalability-and-security review for growth-stage investment.

A full-time CTO in London costs between £173,000 and £253,000 in the first year, once National Insurance, pension, benefits and recruitment fees are counted. Most companies at this stage don’t need one full time. They need senior judgement available consistently, from someone who already knows the system.

Every retained engagement opens with a Production Readiness Assessment. From month one you have an engineer who knows the platform, rather than one learning it on your time.