Europe's finest expert minds, deployed where AI failure costs the most.
2M+ credentialed practitioners (students, researchers, young graduates) across 800+ European universities and 24 languages. Trained in your rubric, validated by senior domain experts, delivered end-to-end.
Crowd labor won’t get you to the next frontier. Neither will synthetic data.
As models approach human-level on general tasks, the bar for useful feedback rises. You need reviewers who think in your domain, not adjacent to it. Credentialed practitioners with the academic depth and lived field experience to catch what the model gets wrong where getting it wrong looks exactly like getting it right.
No one else can source European expertise at scale. We can.
24 languages. Regulatory frameworks that vary across every border. Medical, financial, and cultural contexts that don't translate. No US-based platform has the reach, the relationships, or the regional depth to source the practitioners who understand these differences from the inside.
24 languages, natively
Native speakers across every EU language. People who think in these languages, not translators working from English.
27 legal systems
27 national frameworks layered with EU regulation. A French expert and a German one flag completely different model failures.
Regional specificities
Medicine, finance, culture — they all diverge by country. No synthetic data replicates lived expertise.
This network wasn’t built for AI. It was forged over a decade of institutional trust.
JT AI Labs is built on JobTeaser, Europe’s #1 career platform; embedded inside 800+ universities since 2014. A decade of operating data on hiring, talent, and career decisions; now deployed for the labs and enterprises that need this depth most.
Our methodology, end-to-end, so you can focus on your models.
Annotation quality comes from three things: a credentialed workforce, a rigorous rubric, and expert validation. You define the failure modes you want to catch. We deliver structured data your team can act on.
Rubric design
Our Machine Learning engineers and domain leads co-design evaluation criteria
Source
Credentialed practitioners by discipline, degree, and language
Train
Project-specific onboarding on your rubric
Annotate
Trained practitioners produce the data with documented inter-annotator agreement
Validate
Senior practitioners audit every output, delivering vetted data with a comprehensive methodology note.
Deliver
Contracts, payments, data residency across 25+ jurisdictions
Your team stays focused on model development, not annotator management. From first brief to final delivery — we own it.
Not gig work. Domain practitioners working in their field, making AI better.
Our contributors are Masters students and PhD researchers who apply the expertise they’ve spent years building — on the frontier problems of AI. This is intellectually engaging work at the intersection of their field and the technology reshaping it.
Competitive compensation
Paid at the level their expertise deserves
Applied expertise
Their domain knowledge, put to meaningful use
Frontier AI exposure
A window into how the most advanced models learn
Benchmarks in development.
We're producing a first wave of benchmark datasets evaluating AI performance in high-stakes European contexts: hiring, career guidance, and financial decision-making. Each benchmark surfaces failure modes that generic capability benchmarks miss; differential treatment, reasoning errors across languages, advice quality gaps across profiles. Public leaderboards. Frontier-lab co-development welcomed. More domains coming through 2027.
EU-focused. GDPR-native.
Every annotation is produced by EU-based contributors, with full GDPR compliance, complete data provenance, and residency guarantees. For labs building European foundation models or serving EU customers, this isn’t optional — it’s a requirement we meet by design, not by workaround.
Need evaluation data for AI in European hiring, finance, or another high-stakes domain?
Tell us where your model is being deployed and what failure modes you need to catch. We'll scope a benchmark or evaluation dataset built for your context.