AI Consulting & Integration
AI that works. From hype to substance.
We separate hype from substance, prioritise use cases by value contribution and build the architecture and governance that carry AI long-term.
Book a free introductory call30 minutes. We get to know each other. You decide if it fits.
Current state
You might recognise this.
Pilots stay pilots.
No scalable model emerges from experiments. Tools are introduced in parallel, strategy and architecture are missing, every initiative starts from scratch. What convinces in the workshop rarely lands in daily work.
High AI pressure, low clarity.
The market produces new promises daily. Leadership, business unit and employees expect answers, often weekly. But no one can cleanly say what really holds up in your own context and what only gets expensive.
AI helps. But not everywhere equally well.
It's supposed to accelerate everything, somehow. Where's the real value contribution in your business, where does AI stay symbolic or simply too expensive? Whoever doesn't separate this funds experiments instead of creating value.
AI creates impact not by digitising existing routines, but by redesigning decision and work processes. That requires clarity on where the lever really sits, and a foundation that carries the solution. That's where our work starts.
Our approach
Three steps. Pragmatic. As equals.
No long ramp-up. No AI showroom. We listen first, then we sort it out together.
Current state analysis and understanding
We get to know your business. Model, IT landscape, data, team, existing AI initiatives, AI maturity of your employees. You get an honest assessment: where you really stand, not where the market wants to take you.
Day 1 to Week 3
Strategy and use case prioritisation
We compress topics, use cases and hypotheses into a workable priority list. Which use cases raise your value contribution, which cost more than their benefit, which need a data foundation first. We recommend what we recommend because it fits, not because it generates billable days.
Week 3 to 6
Execution and handover
We support execution, build knowledge into your team, secure architecture, governance and data security. When you can move on your own, we step back.
From Week 6, as long as you need
A testable question: If you had to name three AI use cases in your company today that create measurable value, and three that are only symbolic, could you?
Whoever hesitates has a substance problem, not an AI problem. Spend 30 minutes with someone who knows this from practice.
Areas of focus
Where we focus.
AI Readiness Assessment
Where does your company really stand on AI? We assess strategic maturity, data foundation, architecture, governance and the AI capability of your teams. You get a clear read, not a glossy maturity matrix.
AI Strategy and Roadmap
What creates value now, what becomes relevant later, what is deliberately left out. We deliver a prioritised roadmap that thinks architecture, data, governance and organisation together. For the overarching IT strategy, we point to our IT Strategy & Roadmap service.
Use Case Prioritisation and Value Contribution
We assess your AI use cases by impact, effort and risk. You see clearly which use cases create real value, which stay symbolic, and which need a data foundation first.
Data Foundation and Data Governance
AI is only as good as the data it works with. We assess data quality, sources, access patterns and build the governance that makes AI use cases reliable in the first place. For deep data architecture and sovereignty, we point to our Data & Analytics service.
AI Architecture and Sovereignty
Which models, which platforms, which providers? We design the architecture that carries your AI work without locking you into a vendor. Sovereignty comes from architecture: clear data flow boundaries, defined exit paths, multi-cloud as a negotiation position.
AI Governance and EU AI Act
When AI generates code or acts autonomously, quality assurance becomes a critical function. We define guardrails for models, agents and outputs: architecture, security, maintainability, compliance. Including EU AI Act conformance, where relevant.
Why DRICH.CONSULTING
Technical depth. Business understanding. Governance that holds.
AI initiatives rarely fail because of models. They fail in the gap between technical possibility, business value contribution and durable governance. I've worked as a software developer, architect, IT project lead and Chief Data Officer. From that practice comes a recommendation that brings all three sides together.
Technical depth that knows the limits
My technical background reaches from the first line of code to platform architecture. I spot early which AI promises actually hold up technically and which die in pilot. That saves you experiments that only convince in demo mode.
Business understanding that recognises value
Technical possibility doesn't equal commercial sense. I translate AI potential into concrete levers for your business model and prioritise use cases by impact, not by trend. That's the difference between activity and value contribution.
Governance and data security from CDO practice
From years of practice as Chief Data Officer, I know what a governance framework and an AI-ready infrastructure must look like so your data stays secure and AI actually becomes effective. Compliance and impact are not opposites when the architecture is right.
100 percent independent. What that means concretely.
No model commissions, no vendor partnerships with commercial strings attached, no implementation follow-on business. Concretely: We don't recommend a model we earn money on. We don't build an AI architecture that only runs with one provider. We don't start an AI use case we don't believe in ourselves.
20+
years of
IT experience
AI
live in mid-sized
and enterprise
100%
independent, no
model commissions
→
From hype
to substance
Frequently asked
What decision-makers ask us.
An AI agency earns money on delivery, a model provider on licences. We earn money by helping you make the right decisions before delivery starts. We recommend, review and steer, but we don't build ourselves and we don't sell models.
Often then most of all. First pilots show the limits of current strategy, architecture and governance. We help turn that into a scalable model, instead of starting the next pilot next door.
We assess your use cases for EU AI Act classification, advise on documentation and compliance requirements, and design governance that doesn't surprise at the next audit. Specific legal advice comes from a lawyer; the architecture comes from us.
That depends on your use case, your data and your sovereignty requirements. We are technology-neutral and work with open source models as well as closed source APIs. The recommendation follows the application, not the trend.
No, and we don't pretend otherwise. 30 minutes are enough to roughly understand your situation and to tell you honestly whether we're the right partner. If we're not, we say so. If we are, we suggest a sensible next step.
The current state assessment delivers initial clear statements on prioritisation after two to three weeks. Concrete use case pilots take longer, because data, models and governance need to be prepared. We tell you early and honestly what's realistic.
Introductory call
Free introductory call
Tell us your situation. We listen, ask questions and tell you honestly whether we're the right partner. If we aren't, that's fine too.
- 30 minutes. No pitch, no presentation.
- You describe the problem. We listen first.
- You get an initial read, with no sales intent.
- No commitment afterwards.
Slots are offered on weekdays between 9am and 6pm (CET).
AI on the slide, no AI in substance?
Book a free introductory call