AI Hiring Assistant Case Study

Client Context

A rapidly growing enterprise tech company with weekly hiring spikes across engineering and product divisions.

The Challenge

The client's technical recruiting team was overwhelmed by over 400 applications per job opening. Manual screening created candidate response backlogs and delayed standard hiring metrics.

System Architecture

• 1PDF text extraction parser sanitizing raw resume files
• 2Pinecone vector database holding semantic embeddings of candidates' experience
• 3Claude AI reasoning pipeline matching candidate profiles against technical job specs
• 4Validation boundaries preventing bias markers (names, gender) from processing

The Engineering Solution

We engineered an automated evaluation assistant. Resumes are processed, embedded, and scored against criteria. Recruiters filter matching candidates, review structured qualification summaries, and launch auto-scheduled interviews.

Results & Commercial Impact

Initial resume screening duration was reduced by 75%. Objective criteria evaluation improved screening match quality, resulting in a 35% higher second-stage pass rate.