We start on the floor, not in a slide deck

Industrial software fails when it's designed far from the work. Our process keeps it close to the people and the conditions it has to survive.

  1. Walk the floor

    We start where the work happens: the scale house, the line, the dispatch desk, the back office. We watch a full cycle of the process and collect the real paperwork, the exceptions and the workarounds nobody wrote down.

    You getA map of people, systems, data and handoffs, in your vocabulary.

  2. Find the expensive problem

    Most operations have dozens of annoyances and two or three problems that cost real money. We size each one by time, errors and risk, then rank them against how hard they are to fix.

    You getA written findings report and a prioritized roadmap.

  3. Build the smallest valuable slice

    We pick one slice that pays for itself and build it with the people who will use it. Working software is shown every week, on the devices and in the conditions it will actually run in.

    You getSoftware in production, not a prototype in a demo.

  4. Run old and new side by side

    The new system shadows the old one until the numbers match: tickets, weights, invoices, counts. Nobody is asked to trust it on faith, and there is always a way back.

    You getA reconciled cutover with a documented rollback.

  5. Hand over or keep running it

    You choose whether your team takes it over or we keep supporting it. Either way you get the code, the infrastructure, the runbooks and the training to own it.

    You getDocumentation, access and a system your team understands.

Principles we hold ourselves to

Specific beats general
We would rather solve one problem completely than ten partially. Narrow scope is how projects finish.
The operator is the user
The person using a tablet in gloves at 5 a.m. decides whether the software works, not the person who signed the contract.
Reversible by default
Changes ship behind a switch, with the old path still available, until they have proven themselves.
AI where it earns it
We use models where they beat rules and people on cost and accuracy, and we measure that before anything goes live.
Write it down
Decisions, data mappings and runbooks live in your repository, so knowledge does not walk out the door with anyone, including us.
Say no early
If something is a bad idea, too expensive or better bought off the shelf, we tell you in week one.