AI · 2024
CVScrap
Research project that turns CVs into queryable hiring data
- Year
- 2024
- Status
- shipped
- Discipline
- AI
- My role
- UI/UX & Web Development
The brief
Academic research project analysing CVs to take developer hiring out of the manual screening loop. Upload a document, get a normalised, queryable profile, and let a hiring team search, shortlist and compare candidates instead of skimming PDFs.
How it was built
Screening is the slowest part of technical hiring, and most of that time goes to reading documents that say the same thing in different ways. CVScrap parses a CV into a stable schema, so a recruiter filters by skills, years and projects instead of reading every line. I owned the UI/UX and the web build: the upload and review flow, the search and shortlist screens, and the design system that kept the research prototype consistent. The write-up documents the parsing model, the edge cases we found in real CVs, and where the approach breaks down.
What it had to do
- Parses CV documents into a normalised, queryable schema
- Search and shortlist flow designed for hiring teams
- Research write-up on parsing accuracy and edge cases
Stack
- React
- Next.js
- TypeScript
- NLP
- Tailwind CSS