Build · AI and agentic software engineering
The business wants features faster. Unmanaged AI coding produces inconsistent code, hidden technical debt and changes nobody can explain — and in a regulated business that is a risk the CIO cannot sign off.
We are an AI-native engineering company, and that means more than faster coding. You get an agentic software delivery lifecycle where specs, decisions and evidence are all defensible: deterministic quality gates, evaluations before and after release, rigorous spend controls and a full audit trail. Speed your risk function can stand behind.
THE PROBLEM
Most engineering leaders we talk to have already tried AI coding tools. The problem is rarely the tools — it is that legacy processes, hand-offs and governance still constrain delivery. The next leap in productivity comes from redesigning the whole software development lifecycle, not from generating code faster.
Pull request volume is up and so is the review queue. Senior engineers spend their days checking machine-written code, and the throughput gain evaporates in the pipeline.
A regulator, an auditor or an incident review asks why a line of code exists. The answer is “the agent did it”, and that is not an answer anyone can sign.
Every engineer prompts differently, so the codebase drifts. Architecture decisions are bypassed, patterns fragment, and the debt arrives six months later as an outage.
THE PROCESS
We can deliver the work for you, work alongside your teams, or train your people to adopt the approach themselves. Whichever way, the steps are the same, and the first is a two-week baseline.
Map
A baseline of your value streams and current delivery lifecycle: repository complexity, test coverage, pipeline maturity, review cycle time and where AI tooling is already in use. We use our EPIQ framework — evaluating practices, infrastructure and quality — so the baseline is comparable and the gains are measurable later.
You hold: An honest picture of throughput, quality and risk, with the metrics you will judge us against.
Design
Spec-driven development comes first: behavioural specifications and architecture decisions are written before any agent generates code. We design the agentic quality gates — linting, static security analysis, architecture policy checks, test coverage — into the CI/CD pipeline, and define the points where a human must review.
You hold: An agentic SDLC design with deterministic gates, review points and an audit trail specified.
Build
Fleet coordinates the coding agents, tools and workflows against those gates on a real product backlog. Agentic test generation produces regression, contract and edge-case suites from specs and wireframes, while your QA engineers move to exploratory and non-functional testing. Evaluation gates confirm the output is holding, with the right models behind it.
You hold: Agentic delivery running in production on your backlog, with every change traceable to a spec, a decision and a review.
Run
Observability, synthetic monitoring and kill switches are in place. Your engineers own the harness, the prompts and the gates, with internal champions trained to keep improving them. The metrics from the Map step are re-measured and reported.
You hold: A delivery lifecycle your teams run without us, with measured throughput and quality gains.
THE OUTCOME
What good looks like at the end:
PARTNERS AND ECOSYSTEM
We hold more than 400 GitHub Copilot certifications, covering over 90% of our engineers. We are an Anthropic Preferred Services Partner, with Claude Code at the heart of how our teams build, and an OpenAI Select Partner.
We work across Claude Code, Codex, open-source harnesses and open-weight models, so you are not locked in, and across AWS, Azure and Google Cloud pipelines, so the work happens inside the enterprise environment you already run.
Preferred Services Partner.
One of six in Europe. Claude and Claude Code sit at the heart of how our teams build, which is the same harness your engineers will run.
Select Partner.
Codex alongside Claude Code, so the harness is model-neutral and the choice is made per workload rather than per vendor relationship.
400+ Copilot certifications.
Covering more than 90% of our engineers, so the tooling your teams already have in the IDE is the tooling we build the lifecycle around.
Alongside them we work with Cursor, Kiro, OpenRouter, LangChain and SonarQube.
BUILT IN-HOUSE, PROVEN ON CLIENT WORK
Coordinates the agents
An agentic software delivery harness that coordinates coding agents, tools and engineering workflows, with automated quality gates, evaluations and traceability built into production delivery.
For this work: Fleet is what makes agentic delivery auditable. It coordinates the agents against the quality gates in the Design step, so speed and traceability arrive together rather than as a trade-off.
Evaluation you can trust
Our evaluation harness tests AI systems against real-world cases before and after they go live, so quality is measured, not hoped for.
For this work: Raidar is the launch-readiness layer. It scores AI outputs for groundedness, hallucination, toxicity and accuracy before release and keeps scoring after, so “is it safe to ship?” becomes a measurement.
LIVE IN BUSINESSES LIKE YOURS
OAG
1 in 6 pull requests delivered by agents, rework down 64%, and roughly three engineers' worth of time returned every month.
Read the case study
FanDuel
A LangGraph-orchestrated AI test generation tool: regression effort down 50%, and an hour per cycle down to six minutes.
Read the case study
I've been taken aback by what has been achieved in such a short space of time.
Mikey Smith
Chief Technology Officer, MoneySuperMarket
THE FIRST STEP
Two weeks gives you a baseline of your value streams and your delivery lifecycle, and a clear view of where AI is helping, where it is creating risk, and what an agentic SDLC would change. You keep the baseline whether or not we build the rest.
