Read the reasons behind a score.
Review a profile summary and the four weighted criteria. Use this starting point to prepare the conversation and form your own assessment.
30 days free, no card.
Product designer
Eight years in product design. Experience in research and design systems. Availability to discuss during the interview.
Indicative score generated by AI — the hiring decision is yours.
What you can expect
Ranked automatically
Applications arrive sorted by score, with relevant profiles rising to the top of the pile.
Public criteria
Skills 35%, experience 35%, education 15%, motivation 15% — the weight of each criterion is shown.
Two-sentence summary
A profile summary, up to 3 strengths and 3 concerns: you understand the score at a glance.
Human oversight
The AI suggests, you decide. No automatic decisions, with documented human oversight.
A score you can explain
The global score is recomputed server-side from the contractual weights (35/35/15/15) — never simply trusted from the model. You can re-run a scoring by hand from the application page.
Criteria and their weighting are public and identical for every candidate on a given job: a recruiter, like a candidate, can understand where a score comes from.
Built to be fair
Explicit age, gender, photo and address fields are excluded from the scoring prompt. Free-form CV text can still contain proxies, so the evaluation harness checks them and regularly compares equivalent CVs.
An attempt to manipulate the CV to inflate the score (hidden text, injected instructions) is detected and flagged, never rewarded.
Robust and traceable
Temperature 0, a hard timeout per call, one immediate retry on invalid JSON before marking a scoring as failed: the score is stable from run to run.
Tokens, duration and retries are logged. An AI usage card (scorings, tokens, average duration) is available on the admin side for monitoring.
Frequently asked questions
Can the AI reject a candidate on its own?
No. The AI proposes a score and a summary; the decision always stays with the recruiter (human oversight, AI Act).
Which model powers the scoring?
A French/European model (Mistral) via Scaleway Generative APIs, hosted in France. No candidate data leaves the EU.
Is the score the same every time?
Yes, within a few points: temperature is 0 and the global score is recomputed from fixed weights, which guarantees high stability (σ ≤ 5 on our test set).
See your next hire more clearly.
Explore the workspace with sample data, or start with your own job opening.
30 days free, no card.