Scale-ups & enterprise
Dedicated AI-Enabled Teams
An embedded senior team running our pipeline inside your organisation, on your board, in your timezone overlap.
- Embedded & senior
- Your process
- Monthly rolling
A senior team, embedded in yours. What the work actually consists of — not a menu of buzzwords.
Embedded, not a black box
Engineers who run our pipeline inside your organisation — in your stand-ups, on your board, in your timezone overlap — not a vendor you email tickets to.
Your process, our tooling
We work the way your team works and bring our AI pipeline and review discipline with us. You get the velocity without adopting a new methodology.
Senior by default
People who have shipped and owned production systems, not juniors billed at a senior rate. The volume work is generated; the people are here for the judgment.
The difference between capacity and a body on a board. Each of these is easy to miss, cheap to fix early, and expensive once it is in production. It is what the human gates in our pipeline exist to catch.
Staff-aug that just fills a seat
A body on a Jira board adds cost, not capability. An embedded team has to raise the quality of what ships, not only the quantity.
Knowledge that leaves with the team
Everything is built in your repo, to your standards, documented as it goes — so the capability stays after the engagement ends.
The “our process is special” trap
Most process friction is habit, not necessity. We fit in first, then show where the pipeline can remove work — never the other way round.
Who this is for. And, so you don't spend a call finding out, who it isn't — with a pointer to the one that fits instead.
A fit if
- You have ongoing work and want continuity, not a fixed-scope project
- You need senior capacity that integrates with your own team
- You want the option to scale up or down month to month
Probably not if
- You have a defined, one-off build with a clear end — that is Product Engineering or an MVP Sprint
- You need a fixed price against a fixed scope
How the engagement is shaped.
Monthly rolling, sized to the work, scaling up or down with notice. Your repository, your process, your board — and a named senior lead accountable for what the team ships, exactly as on every other engagement.
Whatever you sign, the delivery loop underneath is the same: 6 stages, and the same two of them are a named senior engineer saying no. Nobody gets a cheaper pipeline for buying the cheaper engagement.
See the pipeline, stage by stageOther ways to work with us. Same pipeline, different commercial shape. If none of them is obviously right, that is what the free spec is for.
- Startups
MVP Sprint
Idea to a production MVP in nine weeks, fixed scope and fixed price. The fastest way to find out whether the thing works.
Explore - Startups & scale-ups
AI Product Engineering
LLM-backed products built properly — retrieval, agents, tool use, evaluation harnesses, cost controls and the guardrails that keep them from embarrassing you.
Explore - Everyone
Product Engineering
The classic build — web, mobile and cloud on MERN, MEAN, React Native and Node — now delivered through the AI-first pipeline.
Explore - Enterprise
AI Integration & Automation
Bring AI into systems that already exist and already matter, without a rewrite: document pipelines, support deflection, internal copilots, back-office automation.
Explore - Enterprise
Modernisation & Rescue
Ageing platforms and stalled builds. AI-assisted migration makes the economics of modernisation work where they previously did not.
Explore
Tell us what you’re building.
Thirty minutes with an engineer, not a salesperson. You will leave with a scope, a timeline and a number — or an honest reason why we are not the right fit.