A three-person staffing firm was losing 150+ hours a month to manual re-keying of scanned resumes. This case study walks through the exact OCR pre-processing architecture, document quality audit, and ATS write-back pipeline that eliminated the queue in five weeks.

Implementing AI resume parsing is a six-step process: audit your current pipeline, define extraction requirements, select a vendor, integrate with your ATS or HRIS, run a calibration sprint, then measure and iterate. Teams that follow this sequence cut time-to-hire by up to 60% and eliminate the manual bottlenecks that cost recruiting teams 15+ hours per week.