Custom software development
Internal tools, customer portals and platforms built around how your team works, not how an off-the-shelf product assumes it does.
How we build custom softwareWe design, build and run custom software, AI workflow automation, agentic systems and mobile apps for product and operations teams, then hand them over tested, documented and owned by you.
Four kinds of work, one team. Most projects mix two of them: an AI workflow with a custom dashboard, an agent with a mobile front end.
Internal tools, customer portals and platforms built around how your team works, not how an off-the-shelf product assumes it does.
How we build custom softwareDocument intake, reconciliation, reporting and the other repetitive work between your systems, handled by AI with a person approving what matters.
How we automate workflows with AIAgents that plan, call your tools and check their own results, with logs you can read and limits you set.
How we build AI agentsiOS and Android apps, native or cross-platform, connected to the same backend and agents as the rest of your stack.
How we build mobile appsAI drafts the routine parts of clinical paperwork. A doctor edits and signs every one before it’s final.
Every AI draft signed off by a doctor
A React Native app for grades, fees and messages, on an API we added to the existing platform.
81 documented API endpoints
Installer tooling, go-live controls, device telemetry and data retention for a UK maker of connected lockers.
A fifth of all commits in 8 months
Four stages. You can stop after any of them and keep everything we’ve made.
A 1–2 week paid discovery. We sit with the people doing the job and decide what should be software, what should be AI and what should stay human.
The smallest version that does real work on real data, in 4–6 weeks. You see it running in a live environment every week.
Monitoring, evaluations, access controls and runbooks go in before launch, not after the first incident.
We stay on to tune and extend it, or hand it to your team with documentation written for the next engineer.
Something else? Ask us directly.
A workflow follows steps you define and uses AI inside some of them, like reading an invoice. An agent decides its own next step toward a goal and calls tools until it’s done. Workflows are cheaper and more predictable; agents handle work that can’t be scripted. We recommend the simplest one that does the job.
It depends on scope and integrations, so we don’t publish a rate card. Every project starts with a short paid discovery, quoted at a fixed price after a first call. At the end of discovery you get a fixed quote for the build, before you commit to it.
A first production release usually takes 6–12 weeks from the end of discovery. Smaller workflow automations can ship in 2–4 weeks.
You do. Code, infrastructure, prompts and evaluation sets live in your accounts from day one.
Yes. Our engineers have connected software to card gateways and bank APIs, a government funding body, messaging and SMS services, and IoT devices over MQTT. If it has an API, a database or an export, we can work with it.
Every AI step has evaluation tests, logs and a defined fallback. Anything with financial, legal or customer impact goes to a person for approval until the error rate says it doesn’t need to.
, 3 min read
Most processes don’t need an agent. Five questions that tell you which one you need, and what goes wrong when you pick the other.
, 6 min read
When the same cancellation runs twice, money moves twice. Why checks in application code don’t stop it, and the database lock that does.
, 6 min read
Your data and your rules already live in the web app. How to give a mobile app access to them without rewriting the platform or breaking the web side.
Tell us what it is. Within 2 business days we'll reply with whether it needs custom software, an AI workflow or an agent, and roughly what it would take.