01
The Problem
Recruiters spend hours reading resumes that don't match the role, and good candidates get missed in the pile.
Case Study 07 · Document & Data Processing
Resume Screening Agent
Hundreds of CVs scored and shortlisted before the first coffee.
- Python
- LLM Extraction
- Streamlit
- Recruitment
02
The Solution
An agent that parses PDF resumes, scores each candidate against weighted job criteria and produces a ranked shortlist with the reasoning behind every score, all in a simple web app.
- Parses PDF resumes in bulk
- Extracts skills, experience and education
- Scores candidates against weighted job criteria
- Outputs a ranked shortlist with explanations
03
The Result
Recruiters start from a shortlist instead of a pile, and every score is explainable.
Want something like this for your business?
Tell me which workflow is eating your team's time and I'll show you how an agent can take it over.