Expertise
Research-grounded method, built to be defended.
Responsible AI advice is only worth what its method can prove. Ours combines a research foundation, a reproducible test procedure we call waveTest, and the practical experience to make recommendations workable — including the realities a non-EU company faces entering the European market.
Four fields
Where regulation, data science, and business meet.
EU AI Act & governance
Risk classification, role determination, conformity, transparency, and post-market duties — read against the live timeline and your sector.
Fairness & bias science
Quantitative fairness metrics, intersectional analysis, and SHAP-based explainability — established statistical methods, not heuristics.
Data & ML engineering
Drift detection, data quality pipelines, and monitoring built on open-source tooling you own — no vendor lock-in.
Sustainability & ESG
The footprint of AI workloads, its place in CSRD/ESRS reporting, and how to integrate it before it becomes a reporting scramble.
Our method
waveTest: reproducible procedures, not opinions.
waveTest is our own test methodology. Each dimension is a defined, repeatable procedure that produces an artifact — so a finding can be re-run, challenged, and put in front of a board or an EU customer.
Fairness
Statistical parity, equal error rates, equalized odds, measured across protected attributes and their intersections — against a fairness criterion stated up front for your use case.
Explainability
SHAP-based analysis of which features drive which decisions, so a model’s behavior can be explained to the people it affects and the authorities that ask.
Data quality
Structured assessment of the inputs, because most bias originates upstream in the data — validated with reproducible pipelines.
Compliance mapping
Each finding mapped to the relevant EU AI Act obligation and, where it overlaps, to your existing GDPR documentation — so nothing is built twice.
The founder
Dr. Valentin José Mayr.
EU-native and fluent in the US business context — used to translating between the way American companies build and ship AI, and the way the European market expects it to be governed. Research where it matters, practice where it counts.
Foundation
Research, strategy, business
- DBA in Data Science
- MBA in Finance
- M.Sc. Data Science
Depth
AI governance & compliance
- Certificate “AI: Law, Policy & Governance” — London School of Economics
- Certified AI Compliance Manager (IHK)
Practice
Digital transformation
- 20+ years in digitalization projects
- SME and upper-mid-market focus
Recommendations should be research-backed — and workable on Monday morning. If they’re only one of the two, they’re not useful.
— Dr. Valentin José Mayr · Founder
Your next step