We check which use cases are worth building, take them into production within 90 days and measure them against business results - from vision models on a steel finishing line to fraud review across 12 markets. One senior team from first workshop to live system, no hand-offs.
Every euro itemised from a named production system - eight of them, listed on the impact page. Delivered by our founding team in senior roles at a global technology leader, a European electronics group and a leading consultancy, and in ProDataAI engagements.
From vision models on the production line to the people who run them - practical, measurable, and built to last.
Models that run on the line, not in a notebook. Computer vision on steel lines, at customs and in police investigations, on an MLOps foundation that keeps them accurate.
Multi-agent systems with human-in-the-loop controls where agents earn their place - and simpler automation where they do not.
Credit decisions per customer, fraud detection, claims liability and pricing from measured elasticity. Models that move a number on the P&L.
Attribution across all journeys, including TV and offline, plus CLV, churn and segmentation - so you know which customers to keep and what it costs.
Semantic search and behavioural ranking that find what the buyer meant, and next-best-offer engines for millions of customers.
Senior AI leadership, from strategy through delivery, for as long as you need it. Scales from a few advisory days a month, so you can start small.
AI Champions programs, role-based training and the Article 4 AI literacy the EU AI Act requires, run as one program. From experience training 1,000+ employees across 12 markets.
For problems we have solved many times: a proven approach, a fixed scope and a clear path from pilot to production, running in your environment and owned by you. The first one measures what every marketing channel is worth, online and offline, and sets the budget on it.
Three honest steps. No buzzwords, no process theatre.
We start by asking whether AI is actually the right answer here. We have talked clients out of AI projects that were not ready. The ones we take on are better for it.
We build systems that hold up at 7am on a Monday, not just in a demo. Real infrastructure, real edge cases, and the unglamorous work of making AI reliable enough that your team actually trusts it.
We measure against business outcomes, not model accuracy scores. If the needle is not moving, we go back and fix it. AI that is not improving is not working.
100+ AI projects delivered across manufacturing, retail, financial services, healthcare, and telecoms. €68M+ in measurable client impact. We know what agentic AI looks like in production - what holds up and what quietly fails after six months.
Vendor-agnostic and hands-on. Senior expertise from strategy to deployment - no junior teams on client work, no hand-offs between what we recommend and what we build.
"We have talked clients out of AI projects that were not ready. We have pushed back on architectures that would have failed in production. Honest AI - built, deployed, and measured. That is what we do."
Real deployments, not demos - from DAX corporates and high-growth Mittelstand to VC-backed scaleups.
Trusted by enterprises across Europe
Prompt chains, routing, parallelisation, orchestrator-subagent and evaluator loops. The gap between one LLM call and a full agent is where 95% of production value lives.
The workflow-vs-agent choice drives cost, reliability, and EU AI Act exposure. A practical CLEAR framework for making this decision deliberately.
What high-risk AI classification means for your systems, what you need in place by December 2027, and how to get there without a compliance theatre project.
Tell us what you're trying to solve. We'll tell you honestly whether the timing is right, what would need to be in place, and what we'd actually do. If we're not the right fit, we'll say so.