Software Development

We build custom software from a written specification. AI does the generation, our engineers review the output, and you own the source code, the infrastructure code, and the deployment pipeline at the end.

How the work runs

We write the specification with you. You bring the idea, however rough. Our product specialists run design sessions to turn it into a specification precise enough to build from — that is most of the work, and it is where your time goes.

We generate the application from it. Our engine produces the services, pages, and components, each one traceable to the requirement that produced it.

Our engineers review it. They read the output, close the gaps, and check it against your architectural and security constraints before you see it.

You review it running. Each iteration goes to a staging environment you can use. We meet on your cadence, you tell us what is wrong, we change the specification and regenerate.

What you get

  • The source code, in a private repository that is yours. No licence, no runtime fee, nothing to renew.
  • The infrastructure as code — the full Terraform to deploy it into your own cloud account.
  • A CI/CD pipeline for testing and deployment.

Working with your engineers

If you have a technical team, they are welcome in the process:

  • Code review. We expect it. Your engineers reviewing our output is a normal part of the engagement, not an escalation.
  • Changing the design late. Because the specification is the source of truth, an architectural or security-policy change means regenerating rather than refactoring. We use feature branches and flags so you can test a large change before it reaches your users.
  • Migrations. Where a change needs a data migration, our engineers write the plan and you approve it.

If you do not have a technical team, you do not need one to work with us.

How we generate code

We do not use a general-purpose code-completion model. Generation runs through our own planning and reasoning engine, which works from the specification rather than from a prompt, so the same specification produces the same application.

Two consequences worth knowing:

  • The output is consistent across a project — naming, structure, and patterns do not drift between the first module and the twentieth.
  • We are not reproducing training data from a public model, which removes a class of licensing risk that comes with assistant-generated code.

Security

  • Zero-trust architecture by default.
  • Threat modelling during design, not after.
  • Static and dynamic analysis in the pipeline.
  • Penetration testing before release.
  • We work to your security policies where you have them.
Software Development