AI Recruitment & Resume Screening

Overview

A fast-growing company posting 15+ roles simultaneously was buried in applications. Recruiters were skimming resumes for 6 seconds each, making inconsistent decisions, and good candidates were slipping through the cracks. We built an AI screening system that reads every resume thoroughly, evaluates candidates against detailed role criteria, surfaces the top 10% with explanations for why they match, and generates structured interview guides so hiring managers ask the right questions.

The Challenge

Resume screening requires understanding context — a 'project manager' at a startup means something very different than at a Fortune 500. The AI needed to handle diverse resume formats, understand career trajectories, evaluate transferable skills, and avoid the biases that plague both human and algorithmic screening. It also needed to comply with EEOC guidelines and provide explainable scoring.

Our Approach

We built a multi-stage pipeline. Stage one parses any resume format into structured data. Stage two evaluates each candidate against a detailed role scorecard covering required skills, experience level, industry background, and culture indicators. Stage three generates a ranked list with narrative explanations for each score. The system learns from hiring outcomes — when a screened-in candidate succeeds or fails, it adjusts the model. All scoring criteria are transparent and auditable.

Key Features

• Universal resume parsing (PDF, DOCX, LinkedIn)
• Role-specific scoring against detailed criteria
• Narrative explanations for every candidate score
• Bias monitoring and mitigation
• Structured interview guide generation
• Hiring outcome feedback loop
• EEOC-compliant audit trail

Results

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