How we build and hand over
A 5-stage process for shipping production systems: discovery, architecture, security review, build, support. We stay on-call until it runs under load.
Our process
What each stage produces, and what has to be true before the next one starts.
Requirements & architecture review
Discovery starts with your objectives, your systems and the constraints they impose. It ends with a written architecture and the risks we found.
Working pilot
We build a working slice of the real system on your own data. What it has to prove is agreed before we start.
Security & compliance validation
Before anything reaches production we run penetration tests and vulnerability assessments, and check the system against the regulations that apply to you.
Production deployment
The system goes live without taking the old one down. Monitoring, alerts and the runbook your team will use are in place first.
Monitoring and updates
We watch how the system performs, retrain models when the data moves, and review the roadmap with you.
How an engagement runs
Discovery & strategy
Workshops with your team show how the work is done today. We then write down the scope, the requirements and the order of work.
Design & architecture
Our designers work on the screens people will use. Our architects decide how the system is put together and where it runs.
Agile development
We build in short cycles and show working software at the end of each one. Every change runs through the test and build pipeline.
Launch & scale
We launch with tests, monitoring and support in place. Afterwards we stay on to help you scale and to change what real load exposes.
The two pathways, in detail
The internal pathway first, then the external product build.
Education
Workshops, trainings and async courses that make teams confident with AI tools. For example: on-site workshops, and Claude Code sessions for non-technical users.
Enablement
Workflow automations and build-versus-buy guidance, scoped to the smallest useful system. For example: automation builds, platform selection, vertical SaaS versus custom tool analysis.
Engineering
Custom AI products built by a dedicated team embedded in your environment. For example: dedicated PMs, designers and engineers working inside your stack.
Product and UX design
Scope, user experience and system behaviour defined before the build, so the AI features fit the work people actually do.
Engineering and AI integration
Custom software with AI integrated into the core of the product, not bolted on.
Post-launch support
After launch we stay on the work. Your team has us for changes, re-versions and scaling.
Questions owners ask
Can we stop after the pilot?
Yes. The pilot is scoped and priced on its own. If it shows the system is not worth building, that is a useful answer and the engagement ends there.
Who owns what you build?
You do: the code, the data and the documentation, with the ability to change it without us. Handover is priced into the work.
What happens after launch?
We stay on while it meets real load, fix what breaks and re-version what does not fit, against the targets signed for your engagement and measured on your data.
Start with a discovery call.
We will go through your systems and what the first stage would cover.
Schedule a call