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Software engineering

Software engineered
around the business

New applications, platforms and internal software — or an engineered layer around the systems a company already runs. Usually both.

BUILT NEWBUILT AROUNDENGINEEREDsoftware that runs

What gets built

Software, not deliverables.

A working application with the services, data model and permissions behind it — and a way to deploy and run it. Not a prototype, and not a team rented by the month.

  1. New software

    Built from the ground up.

    • Custom applications
    • Business applications
    • Web applications
    • SaaS platforms
    • Internal operational tools
  2. System evolution

    Extended, not replaced.

    • Legacy modernisation
    • New interfaces over existing software
    • Service layers around what runs
    • Added capability without a rebuild
  3. Backend & data

    Data models outlive interfaces.

    • APIs and services
    • Databases and data models
    • Business logic
    • Authentication and permissions
    • Logging and audit trails
  4. Connected software

    Interfaces are designed, not assumed.

    • ERP and CRM
    • Third-party APIs
    • Cloud services
    • File and data exchange
    • Integration layers

Working with what exists

Most companies do not need everything replaced.

There is usually a database that is fine, an ERP nobody is going to change, and a process that works until it reaches software written for a different decade. The useful engineering question is which part of that actually has to be rebuilt — which is often none of it.

  1. What already runs

    ERP · databases · legacy applications · files · third-party APIs

  2. The engineered layer

    services · APIs · validation · business logic · access control · audit

  3. What people actually use

    web application · internal tool · platform · workflow

The same shape covers a new product built on an existing operational database, an internal tool that has to write back into an ERP, and a legacy application given a modern interface without touching what sits behind it. These are engineering patterns, not client case studies.

Where intelligence fits

A component, not the premise.

Automation, retrieval, computer vision, language models — engineered into an application at the point where they do something a rule cannot, with their output validated like any other input. A model added to software that was not going to work anyway does not make it work.

AI systems & engineering →Automation →

How the work starts

Scoped from the process, not from a wishlist.

  1. 01

    One process, one system

    Examined as performed rather than as documented, with the systems it touches named.

  2. 02

    What should exist

    Architecture, data model, and what to leave alone. Sometimes the answer is that less should be built.

  3. 03

    Engineered

    Built, reviewed and tested against something other than production.

  4. 04

    Run

    Deployment, access, logging and a route for changes after handover.

The languages, databases and platforms behind this, and the practices that keep it running after handover, are set out under technology & engineering.

A process, a system,
a problem or a product idea.

Bring one of them. We work out what should be built — and what should not — with the engineers who would do the work.