Low-risk AI prototyping service

Fast experiments to support calm decisions

AI is changing software work quickly, but many organizations feel they have no time to think clearly about it. A prototype is a way to replace assumptions with evidence — without committing to a large project too early.

Our AI prototyping service is fixed-scope and decision-oriented. The goal is not "AI everywhere". The goal is to learn what actually works in your context, what breaks, and what it would take to build something reliable.

What it is

A short, practical engagement where we take one concrete use case and turn it into a working prototype. You get something you can run and evaluate — plus a clear recommendation for what to do next.

  • Fixed scope (one use case, defined constraints)
  • Working prototype (demonstrates capability and limits)
  • Decision-ready outcome (proceed, adjust, or stop).

Packages and pricing

We offer three fixed-scope packages. Each ends with a decision-ready outcome: proceed, adjust the approach, or stop.

Starter

€1,200 + VAT • delivery within two weeks

  • one clearly defined use case and a specification or list of requirements
  • implementation as a web application only
  • focused familiarization (up to 6 hours)
  • working demonstrator or small prototype
  • short written recommendation on how to proceed with the demo/prototype.

Best for: a quick reality check before investing time and attention.

Standard

€4,800 + VAT • typically 2–3 weeks

  • one use case with clear success criteria and evaluation
  • prototype with more realistic boundaries and quality gates
  • risk notes: data, privacy, reliability, operational concerns
  • handover discussion with your team.

Best for: feasibility checks using your real data and constraints.

Detailed

€14,500 + VAT • typically 4–6 weeks

  • deeper evaluation, alternatives, and operational considerations
  • prototype closer to a production path (still not production)
  • integration sketch (auth, data flows, monitoring, cost model)
  • clear next-phase plan if you decide to proceed.

Best for: decisions that affect a core workflow or a long-lived system.

If a prototype leads directly to a consulting or development project with us, the prototype fee is credited toward that engagement.

Pricing assumes reasonable access to data and stakeholders. If your situation is unusually constrained, we'll agree the scope up front and keep it tight.

When it's a good fit

  • you need to test feasibility before committing budget or roadmaps
  • you want to evaluate AI quality on your real data, not demos
  • you need a safe way to explore risks (privacy, accuracy, trust, accountability)
  • you want to understand integration effort and operational consequences.

Example prototype themes

  • AI-assisted search or Q&A over internal documents (with grounded answers)
  • exploring if a custom application (where none currently exists) would help
  • classification, routing, or extraction from documents and messages
  • drafting support for internal workflows (with review and quality gates)
  • AI-assisted developer workflows (tests, refactoring support, analysis)
  • customer support helpers (with careful boundaries and escalation).

A prototype is not a promise of production readiness. It is a way to measure what "ready" would require.

How we approach AI

We treat AI as engineering, not magic. That means being explicit about:

  • Purpose: what problem are we solving, and for whom?
  • Boundaries: what should the system never do?
  • Quality: what does "good enough" mean, and how do we measure it?
  • Trust: how do humans review, override, and stay accountable?
  • Operations: monitoring, costs, failures, and long-term maintenance.

Sometimes the best result is a prototype that proves the idea is not worth building. That is still progress — and usually cheaper than learning the same lesson later.

What this is not

Prototyping is meant to reduce uncertainty. It is intentionally not the same as full delivery. To avoid misunderstandings, here is what these engagements are not:

  • not a fully working, tested, production-ready application
  • not a production deployment or a "ready-to-ship" feature
  • not a security certification, compliance audit, or penetration test
  • not a full data platform or enterprise integration project
  • not a replacement for product ownership, process design, or change management
  • not an open-ended research project without boundaries.

What this does not include

The packages above are fixed-scope on purpose. Unless agreed separately, they do not include:

  • production hosting, deployment pipelines, or on-call operations
  • full authentication/authorization integrations (SSO, enterprise IAM)
  • data migration or large-scale data cleanup work
  • long-term maintenance or support contracts
  • user training, organization-wide rollout, or change programs.

If you want to proceed after a prototype, we'll propose a sensible next phase based on what we learned.

How to get started

We begin by selecting one concrete use case and clarifying constraints: data sources, users, success criteria, and non-negotiables. We build the smallest prototype that can answer the real question: does this work in your world?

Send us an email: info@intertechno.org

Further contact details can be found here.