Custom Application Development
Web, mobile and enterprise applications built to carry real load — including the AI surfaces that increasingly live inside them. We ship software we then have to maintain, which changes how we build it.
- Next.js & React
- React Native
- Node & Python
- AI-native surfaces
Most software is expensive because of how it was started
The cost of an application is decided in its first month — by the data model, the boundaries between services, and whether anyone wrote a test. We build the way we build our own products, because we are the ones who carry the maintenance when it is wrong.
Capabilities in this practice
Each of these ships as a working system integrated with what you already run — not a slide deck or a proof of concept that stalls at the pilot.
Web Applications
Next.js and React front ends with server rendering where it earns its keep, on APIs designed for the access patterns the product actually has.
Mobile Applications
React Native apps sharing logic with the web where that helps and going native where it does not — offline behaviour and push handled as features, not afterthoughts.
Enterprise Platforms
Multi-tenant systems with role hierarchies, audit trails, SSO and the permission model your security review will ask about.
AI Surfaces Inside Products
Chat, search, generation and agent features built into existing applications — with the retrieval, evaluation and cost controls that keep them viable.
API & Integration Work
REST and GraphQL surfaces, webhooks, third-party integrations and the sync jobs that keep systems agreeing with each other.
Modernisation
Incremental replacement of legacy systems — strangler-fig style, so the business keeps running while the software underneath changes.
A sequence built to de-risk, not to impress
We measure before we optimise and ship in slices, so you can stop, redirect or scale at any step with evidence rather than instinct.
- 1
Shape the problem
Agree what the software must do and, more usefully, what it must never be asked to do.
- 2
Model the data
Get the schema and the boundaries right first; almost every later cost traces back here.
- 3
Thin vertical slice
Ship one complete path end to end early, so integration risk surfaces in week two, not month five.
- 4
Build in slices
Iterate in working increments you can review, redirect or stop against real usage.
- 5
Harden
Load behaviour, error paths, observability and access control before launch rather than after.
- 6
Operate
Monitoring, on-call and a maintenance path — the part that decides total cost of ownership.
Applications we build and run
We build our own products on this stack. When we recommend an approach, it is one we already run in production and pay the bills for.
The things clients ask before signing
Usually both. We start inside what exists, add tests around the parts we are about to change, and replace incrementally. A full rewrite is occasionally correct but it is rarely the cheapest path, and it puts the business on hold while it happens.
You do, from the first commit, in your repositories. We work in your organisation rather than handing over a zip file at the end.
That is the intended outcome. We use mainstream stacks rather than in-house frameworks, document decisions as we make them, and run a handover period pairing with your engineers.
We scope a first slice precisely and the rest in ranges, then re-forecast against measured velocity after a few weeks. A confident twelve-month estimate on day one is a sales artefact, not an engineering one.
Ready to put this into production?
Tell us the problem you are trying to solve. We will tell you honestly whether AI is the right tool for it, and what it would take to ship.