Feasibility checks

Does it work,
and does it hold up in your architecture?

Many AI projects do not fail because of the model but because of data, permissions and infrastructure. The Lab clarifies these questions before budget is committed and hands the result over to SIMO GmbH’s consultants.

What we check and why

A feasibility check answers two questions separately: does the approach work technically (feasibility)? And is it usable in your business architecture, with your data, roles and rules (usability)?

The second question usually decides. A model that impresses in a trial is of little help if the data is out of reach or nobody is allowed to approve what it should see.

  • Data access and quality: where is the data, who owns it, and what is missing?
  • Permissions and approvals: who may know what, and can that be enforced technically?
  • Infrastructure: what runs on your own hardware, and what needs a hybrid architecture?
  • Value in the process: which task really gets easier, and how do we measure it?
  • Limits: whatever does not hold up, we name explicitly.

How it works

Five steps to a decision

  1. Sharpen the question

    In the initial call (45 minutes, free of charge) we agree which decision the check should prepare.

  2. Set up the trial

    We build the smallest experiment that answers the question, ideally on your infrastructure.

  3. Measure

    We measure against the actual data source, not against assumptions or documentation.

  4. Assess

    We put the result into context for data, processes, roles and governance.

  5. Hand over

    You receive a basis for your decision. Whatever holds up, SIMO GmbH puts into practice with you.

Outcome

What you have in hand at the end

  • A basis for your decision

    Feasible, feasible with conditions or not feasible, each with reasons and measurements.

  • Named limits

    Open issues and risks are part of the result, not swept under the carpet. That protects you from investments that do not hold up in daily use.

  • A path into implementation

    Which building blocks of the architecture are missing and in which order they should be built.

Examples from the Lab

What checks look like

Frequently asked about the check

  • Does our data stay with us?

    Yes. Wherever possible we test on your infrastructure. Where external models make sense, only after pseudonymisation and with your approval.

  • How long does a check take?

    That depends on the question and the number of data sources. We agree scope and duration together in the initial call.

  • Who carries out the check?

    The consultants of SIMO GmbH in Aschaffenburg, Germany. The Lab is their testing ground, not a separate company.

From the Lab into consulting

Does this fit your project?

SIMO GmbH puts into practice what holds up in the Lab: Business Data Strategy & Architecture for AI. The initial call takes 45 minutes and is free of charge.