Process, software, advice.

Every engagement is scoped to the problem in front of it, not to a package. Most start with the process underneath, because that is where the largest savings sit.

01 — Optimise

Business process optimisation.

Every company runs on processes, and the cost of a bad one is paid daily. Work is mapped as it actually moves, every stall is quantified, and the process is rebuilt with before/after numbers.

  • Process mapping and discovery

    The process is documented as it really happens, not as the org chart describes it: every step, hand-off and decision, with the people who do it. The output is a single map the whole team agrees is accurate, which is the precondition for changing anything.

  • Bottleneck and rework analysis

    With the real process on the table, the losses get measured: queue time, duplicate data entry, waiting on approvals, rework loops. Each one gets a number attached, so priorities follow cost, not opinion.

  • Redesign with automation and tooling

    Steps are removed, merged or automated, and what remains is rebuilt around the outcome the customer sees. Software and AI are added where they remove work, not to add tools for their own sake. The target is a shorter process, measured end to end.

  • Rollout with metrics

    A redesigned process only counts once the team runs it on its own. Rollout comes with a baseline, a target, and hands-on support until the new numbers hold on their own.

02 — Build

Software delivery.

Backend systems, APIs and the web applications in front of them, taken from first commit to production and handed over with tests, documentation and a codebase your team can run and extend.

  • Backend systems and APIs

    The core of most engagements: data models, background jobs, integrations and APIs on the JVM (Java, Kotlin, Spring) and Go. Built to stay correct under load, observable in operation, and predictable years after launch.

  • Web applications and websites

    Internal tools, customer-facing applications and marketing sites, built with modern tooling to be fast, accessible and maintainable. Native mobile apps are out of scope by design.

  • Architecture and technical strategy

    Before code: the domain is mapped, the technology chosen for its production track record, and the architecture laid out so it grows without a rewrite. Written down, so everyone shares one mental model.

  • Delivery pipelines and handover

    Build, test and deployment pipelines set up so releases are routine. One engagement took deployments from a few a day in hours to more than 500 a day in minutes. Every system is handed over with the documentation to run it.

03 — Advise

Technical advisory.

A second opinion from people who have built and operated the systems in question: due diligence, build-vs-buy calls and architecture reviews, delivered as a decision with the reasoning attached.

See the AI offering
  • Technical due diligence

    A direct read of the codebase, architecture, team and vendor claims for founders, investors and leadership. The report names what is actually broken, what is a real constraint versus an assumed one, and which fix is proportionate.

  • Build-vs-buy and architecture decisions

    When the options are a hire, a rewrite or a purchase, the cost and the risk of each are laid out in plain language, with one recommended. The output is a decision that can be acted on this quarter, not a slide deck.

  • AI implementation strategy

    Where AI pays back in your operation, where it does not, and what it costs to run. Grounded in systems operated in production today, not in vendor benchmarks. The full AI offering is on its own page.

Not sure which one fits? Ask.

Send a short description of the process, system or decision. You get a written answer on the right way to approach it, and a straight no if it is not a fit.

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