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AI-Ready Azure Platform

A governed Azure foundation, with your first AI use case live on it.

We build or remediate the Azure landing zone, put the data, security, and governance controls in place, then design and deploy your first AI use case on it. The system is classified for the EU AI Act and handed over with the monitoring that keeps it accurate.

Investment
From €35,000
Duration
8–12 weeks
Format
Remote-first, on-site for design

At a glance

Investment
From €35,000
Duration
8–12 weeks
Format
Remote-first, on-site for design
Markets served
DACH and Benelux

Who it's for

  • An assessment has told you the foundation is not AI-ready, and you want it fixed and the first use case built in one engagement.
  • You have an AI use case that proved out in a demo and now has to run in production, governed and monitored.
  • You operate under the EU AI Act and need the classification and documentation built into the system, not bolted on after launch.
  • Your first AI pilot is stuck because no one owns the platform it would need to run on. Azure, data, and AI governance sit with three different teams.
  • You are choosing between hiring the platform team internally and buying the outcome, and want the cost and timeline for the second option before deciding.

Scope and format

Eight to twelve weeks, remote-first, with on-site sessions for the design phase. The team builds or remediates your Azure landing zone, implements the data, identity, and security controls the use case depends on, and stands up the governance the EU AI Act requires. Then we design, build, and deploy the first AI use case, whether that is retrieval over your document estate, intelligent document processing into a downstream system, or an agentic workflow. Where the use case is document processing, the pattern is the one already running in production: PDFs parsed and validated before they post into a downstream system such as SAP. The same senior architects and engineers do the work throughout.

What you get

Governed Azure foundation

A landing zone built or remediated to your compliance baseline, with identity, security, and cost controls enforced in code.

First AI use case in production

One use case designed, built, and deployed on the foundation, running against your real data with the retrieval or processing evaluated, not assumed.

EU AI Act classification and Annex IV documentation

The system mapped to its risk category and documented as an engineering deliverable, with post-market monitoring designed in.

MLOps and monitoring

The pipeline, monitoring, and retraining or rollback path the system needs to stay accurate after go-live.

RACI and operating model

Who in your organisation owns the platform, the model, and the data pipeline after handover, agreed and documented before go-live, not worked out afterward.

Cost model for scale

What running the platform and the use case costs at current volume and at ten times the volume, so the business case survives success as well as the pilot.

Handover and runbook

Documentation and a working session so your team can run and extend the platform without us.

Pricing

Value-based and scoped per engagement, from €35,000. We price against the state of your foundation and the use case you choose, and fix the figure before we start.

If you ran a Microsoft Landscape Assessment or an AI Discovery Sprint with us in the last eight weeks, that fee comes off this engagement.

Where your data sits

The build runs in your tenant, in the Azure region you are bound to. Access is least-privilege and scoped to the engagement. Where data residency matters, the foundation is configured in the Germany West Central Azure region, and we sign your data processing agreement before we start.

Governance & compliance

  • The first AI use case classified to its EU AI Act risk category before design.
  • Annex IV technical documentation produced as an engineering deliverable.
  • The platform built in your tenant and your region, with data residency enforced in the landing zone.
  • Post-market monitoring designed in, not promised for later.

Includes EU AI Act positioning and how we classify AI systems.

Read our governance approach

Common questions

How long does it take?

Eight to twelve weeks, depending on the state of the foundation and the use case you choose.

How is the price set?

Value-based, from €35,000. We scope the foundation work and the use case with you, fix the figure before kickoff, and credit any assessment fee from the last eight weeks against it.

What if our Azure foundation is already in good shape?

Then the engagement weights toward the use case, and the price reflects the smaller foundation effort. The Microsoft Landscape Assessment is how we tell the two apart before quoting.

Which AI use case do you build?

The one with the clearest payback for your data and systems. If you have not picked one yet, the AI Discovery Sprint ranks the candidates first.

Who actually does the work?

The same senior architects and engineers who design the Azure landing zone build and deploy the AI use case on it. Nothing is handed off to a separate delivery team partway through.

How is this different from hiring a systems integrator?

A systems integrator typically scopes the foundation and the AI use case as separate statements of work, often staffed by different teams. Here one senior team carries both, so the handoff risk between infrastructure and use case doesn't happen.

Can more AI use cases be added later?

Yes. The landing zone and governance controls built for the first use case carry over, so a second or third use case reuses the foundation instead of repeating it.

Do we need to have chosen a specific AI model or vendor before starting?

No. Model and vendor selection is part of the design phase, made against the use case and your data, not fixed in advance.

What if the first use case does not work out as expected?

The evaluation step in the build is designed to surface that early, against real data, not at the readout. If a use case underperforms, we redesign it or swap in the next-ranked candidate before the engagement closes, not after.

Does the engagement cover Microsoft 365 Copilot, or only custom AI systems?

Both are in scope if the use case calls for it. Most engagements combine a custom system, retrieval or document processing, with Copilot extensions where the workflow already lives in Microsoft 365.

Request the engagement