Service 02

AI advisory & assessments

Where AI actually pays off in your stack, which model to commit to, and what to build versus buy.

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Overview

Most AI engagements should start with an assessment, not a sprint plan.

We take the workflow apart and find where a model earns its cost and where it does not. You get a written scope, an evaluation plan and a cost model — yours to keep, whether or not you hire us to build.

A good half of the AI work we are asked to quote should be a database query, a rules engine, or a better form. We say so in the assessment, at the same price. Where AI is genuinely the right answer, the assessment also settles the harder questions: which model and vendor to commit to, what happens when the model changes, and whether the workload needs to stay inside the EU.

What we build

  • Workflow-by-workflow assessment of where a model earns its cost
  • Written scope, evaluation plan and cost model you keep either way
  • Model and vendor selection, including EU-hosted and self-hosted options
  • Data boundary scoping — what leaves your systems and what stays
  • Build-versus-buy analysis against existing tools and platforms
  • Honest recommendation against AI where a deterministic system is cheaper and more reliable
  • Prioritised roadmap handed over whether or not we build it

What we commit to

Written into the engagement, not implied.

Assessment priced and delivered on its own
Separate
You keep the written plan
Yours
Model scored on your workload
Workload
Same fee if the answer is no
Same fee
How it runs

Three phases, and you can stop after the first.

The assessment is priced and delivered on its own. If the answer is that you should not build this, you have paid for one phase and saved the other two.

  1. Assess

    Workflow by workflow, we find where a model earns its cost. You get a written scope, an evaluation plan and a cost model — yours to keep either way.

  2. Decide

    A build-versus-buy recommendation against the tools and platforms you already run, plus model and vendor selection where building is the right call.

  3. Hand over or build

    You take the plan to your own team, or we build it under the AI product engineering service. Both are real options — the assessment does not assume the second one.

The uncomfortable part

If a deterministic system is cheaper and more reliable, we recommend that instead — the assessment costs the same either way.

We will say so in the assessment, at the same price. It costs us a build and saves you a system you would have had to keep feeding.

  • A chatbot over content nobody reads
  • Summarising records a person already skims in four seconds
  • Natural-language search across six well-labelled filters
  • Anything where a wrong answer is expensive and unreviewed
FAQ

About this service.

Questions about this service, kept separate from the ones answered on the home page.

No. The assessment ends in a written recommendation, and where buying or not building at all is the better answer, that is what we write down.

This is the decision before the build: where AI pays off, what to build versus buy, and which model and vendor to commit to. It is priced and delivered on its own.

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Custom software solutions, web applications, and systems integration. We use modern technologies to deliver optimal performance and results.

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IT infrastructure & cloud

Data processing infrastructure and cloud solutions management. We ensure system stability and security.

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Consulting & architecture

Strategic IT consulting. We help you choose the right technologies and optimise business processes.

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Tell us what you are trying to build.

Two sentences about the product and the constraint. We reply within one working day — with a plan, or an honest referral.

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