French HR Expert Data for AI Labs: Payroll, Labor Law, and Recruiting

Aug 3

Your models are weakest where the ground truth is hardest to reach. French human resources is one of those places — and it is one of the few remaining domains where correctness can be checked automatically.

Talma AI is a Paris-based recruitment company building a verified network of French HR professionals for AI training work: preference data, evaluation rubrics, and RL environments in payroll, labor law, and hiring. This page explains what is Talma Labs, what we cover, how we verify expertise, and how to run a pilot.

Why French HR is a verifiable domain

Most expert-data domains are graded by opinion. A legal memo or a medical explanation can be scored well or badly, but two qualified reviewers will often disagree, and the reward signal stays noisy.

French payroll does not work that way. A payslip is the output of a deterministic computation: gross salary, contribution brackets, collective bargaining agreement rules, and statutory rates produce exactly one correct set of figures. A DSN filing either reconciles or it does not. This gives you something rare — a real professional workflow with a computable reward, in a non-English language, under a regulatory regime that no US-trained model has seen in depth.

The same holds, with more nuance, for labor law. French employment law is codified, heavily case-driven, and unforgiving: a procedural error in a dismissal invalidates it regardless of the underlying facts. Whether a given procedure is valid is a question with an answer, not a matter of taste.

For teams building agents for European enterprise use, this is also where failures are expensive. HR is one of the highest-volume enterprise agent use cases, and in the EU it operates under regulatory scrutiny — the AI Act treats employment-related systems as high risk. Evaluation data in this domain is not a nice-to-have.

What translated data does not solve

Preference data does not survive translation. Alignment researchers have documented the gap repeatedly: models trained on English preference data underperform in other languages, and translated datasets are not a substitute for native annotation. The judgment being captured is culturally and legally situated, not lexical.

French HR is an extreme case of this. Collective bargaining agreements — conventions collectives — cover most of the private workforce, and they are sector-specific, negotiated, and frequently revised. There is no equivalent structure in US employment practice to translate from. A model can only learn this from people who apply it.

The French state has begun collecting French-language preference data at scale through compar:IA, an open initiative that had gathered over 600,000 prompts by early 2026. That effort samples the general public. It does not produce specialist judgment in payroll or employment law.

Domain coverage

Our network covers the full HR function. The domains below are ordered by how well they suit training and evaluation work — the first four have the clearest ground truth.

Payroll and statutory filings — payslips, DSN, URSSAF, contribution calculation
Employment law — dismissal procedure, contract law, litigation exposure
Collective bargaining agreements — sector-specific rules, applicability, revisions
Contracts and HR administration
Recruiting and sourcing — candidate screening, interview evaluation
Candidate documents — CVs, cover letters, professional profiles
Employee relations — works councils (CSE), collective negotiation
Compensation and benefits
Training and skills development
Workforce planning
Onboarding and offboarding
HRIS tooling and process

How we verify experts

Verification is the product. Self-reported expertise is worthless to you, and a network of 6,000 unverified contacts is worth about as much as a mailing list.

Practical testing by domain. Candidates are scored on real work, not credentials: correcting a payslip seeded with errors, resolving a termination scenario against the applicable agreement, assessing a candidate file. Scores are recorded per sub-domain, so a payroll specialist is not staffed on employee relations.

Identity verification. Handled through a third-party provider, with liveness and document checks. We treat this as a hard requirement rather than a formality — infiltration of expert marketplaces by fraudulent contractors is a documented problem in this market, and a lab has no way to audit it after the fact.

Inter-annotator calibration. The same cases are scored by multiple experts to measure agreement. We report those figures to you rather than asserting quality. Where agreement is low, that itself is a finding worth having before you build a reward model on the domain.

Delivery review. A lead expert reviews sampled output before it reaches you, with double scoring on contested items.

What we deliver

Vetted experts, staffed on your platform. If you run your own annotation tooling, this is the fastest path. We source, verify, and score; your team assigns and manages the work. This is available now.

Managed data production. Preference pairs, evaluation rubrics by sub-domain, annotated case sets — produced and quality-reviewed on our side, delivered to your specification.

RL environments. Simulated French HR workflows with computable rewards: payroll processing and filing, collective agreement application, end-to-end hiring processes. This is the longest-horizon work and is scoped per engagement.

We are an independent French company. We are not owned by, nor do we hold investment from, any model developer — the neutrality question that reshaped this market after 2025 is not one you need to litigate with us.

Where we are, honestly

We think you should discount vendor claims in this market, so here is the accurate picture.

Talma AI is an established recruitment company. The expert-data vertical is new. We have roughly 6,000 identified French HR professionals — real contacts from our recruitment operation, not purchased lists — and we are running them through qualification now, starting with payroll as the first scored domain.

What we can commit to today is a scoped pilot: a defined set of experts, verified and calibrated, on a domain you choose, with agreement metrics reported. What we would not tell you is that we have thousands of experts already working. Nobody in this market who tells you that on a first call is being straight with you.

Working with us

Pilot. Pick a sub-domain and a task format. We deliver a calibrated expert cohort and a sample batch, with inter-annotator agreement reported alongside it.

Commercial model. Hourly rates for staffed experts, per-unit pricing for managed data production, scoped pricing for environments. Rates depend on domain and required seniority; the regulated domains — payroll, employment law — carry the premium.

Data handling. Work is performed under confidentiality agreements. Experts never handle data from their own employers. We are a French company operating under GDPR, which for EU-facing evaluation work is generally an advantage rather than a constraint.

FAQ

How large is the expert network? About 6,000 identified French HR professionals, with qualification underway. We report verified, scored, and available counts separately, and we will give you the real number for your domain before a pilot.

Can you support languages other than French? French is our specialty and our defensible position. We would rather do one language properly than claim coverage we cannot verify.

How quickly can a cohort be staffed? For domains already in qualification, weeks rather than months. Contacts are in hand, so we are not running acquisition — we are running verification.

Do you work through existing data vendors? Yes. If you already work with a marketplace or data partner, we can supply verified French HR experts through them.

Are you independent of model developers? Yes. No model developer holds equity in Talma.

What about the EU AI Act? Employment and worker-management systems fall in the high-risk category, which brings documentation and evaluation obligations. We are not a compliance advisor, but domain-expert evaluation data in this area is directly relevant to those requirements.