Verified European & French domain expertise for AI.
Vimen builds test sets and alignment datasets produced by verified practitioners in regulated domains.
Evaluation and alignment formats tailored to your pipeline.
SFT Pairs (Supervised Fine-Tuning)
Preference Pairs (RLHF / DPO)
Evaluation Benchmarks
What you buy is not a pool. It is a protocol.
Every data point is created by an identified practitioner. None is synthetic, none is anonymous.
An expert pool is replaceable. A verifiable production methodology is not.
Sourcing & Verification
Identity, degree, bar/professional registry verification, company ID. Calibrated knowledge assessment before onboarding. Zero unverified contributors.


Sourcing & Verification
Identity, degree, bar/professional registry verification, company ID. Calibrated knowledge assessment before onboarding. Zero unverified contributors.
The protocol remains identical regardless of the domain. Only the expert changes.
Domain Verticals
Vimen builds verified expert pools per domain, on demand. Sourcing and calibration timeline: two to four weeks depending on profile rarity.

Tax & Corporate Law

Insurance & Banking

Medicine & Healthcare

Engineering

Other Domains
Data you can defend.
Encryption, systematic NDA, signed IP transfer, public datacard.
Annotation performed by verified experts residing in the EU. Zero non-EU outsourcing.
Infrastructure hosted in the European Union. GDPR compliant by design.
Inter-annotator agreement measured and published on comparative sets.
Rights assignment signed by every contributor. Enforceable license.
Anticipating Article 10
The EU AI Act mandates documented data governance for high-risk AI training datasets. Corresponding obligations take effect in December 2027.
The traceability Vimen documents today is what these regulations will require tomorrow. Provenance, protocol, contributor qualification, IP chain.
European AI deserves the finest data.
If you deploy a generative system in European regulated domains, you know general models struggle with expert reasoning. Whether training your model or building RAG pipelines, the question remains: where does it fail, and why.
Vimen measures this gap, then produces the data to bridge it.
20 minutes to explore what this means for your use case.