AI ATS System
An AI-assisted applicant screening system that compares CVs with a job description to help identify stronger matches for review.
Problem and purpose
Reviewing applicant CVs against a job description takes time, especially when each application uses a different structure and vocabulary. The AI ATS System provides an assisted comparison workflow that organizes relevant information for a reviewer. It is designed to support screening work while leaving the hiring decision with a person.
How the screening workflow works
The system takes the applicant’s CV and the role’s job description as the two sources being compared. It uses natural language processing to examine their content and presents candidate matching information in a form that can be reviewed more consistently.
- Reads CV content alongside the supplied job description.
- Compares the candidate profile with the requirements described for the role.
- Presents matching information to support candidate screening.
- Uses NLP and large language models to interpret candidate and role content.
- Uses Python and Firebase within the deployed product.
Intelligent candidate matching
The system combines natural language processing with large language models to interpret CV content in relation to a job description. It helps teams move from manual document comparison to a clearer, faster view of candidate relevance.
My role and implementation
Yahya Mahroof built and deployed the AI ATS System as a complete web product. The implementation brings together the matching workflow, NLP and large language model capabilities, the Python application layer, Firebase, and the user interface used to review candidates.
Project status and links
The project is available as a live web system. Visitors can open it from this case study, while the portfolio remains the canonical source connecting the project to Yahya Mahroof.