Applied AI
Anonymised AI-assisted candidate assessment
A web application for online tests with AI-assisted scoring, designed so that the model never knows who the candidate is.
Tools
- In-house web app
- LLM APIs
- PDF reports
- GDPR
- EU AI Act
Illustrated with fictitious data. Real project. Screenshots and examples use fictitious data: no client data or business figures are shown.
Situation
Recruitment relied on paper-based tests and subjective judgement, with no consistent criteria across candidates and no structured record of the results.
Solution
I developed an in-house web application with online tests, automatically generated PDF reports and AI-assisted scoring against model answers defined in advance. The architecture keeps the candidate anonymous to the model: it only receives the answer it has to assess, in line with the GDPR and the EU AI Act.
Result
Consistent, traceable assessment criteria for every candidate, with comparable reports and no personal data exposed to third parties.
How it works
Online test
The candidate answers in the browser.
Anonymisation
The answer is separated from any data that identifies the candidate.
AI-assisted scoring
The model only receives the answer and the reference model answer.
Result linked back
The score is matched to the candidate inside the application, never outside it.
PDF report
Comparable across candidates, for the hiring team to decide.