AI Resume Screening Agent: Gmail-Triggered PDF Parsing → Dual-Path Candidate Analysis → Google Sheets Database

Problem:

A hiring team was manually downloading resume attachments from Gmail, reading through each PDF, assessing candidate fit, and entering data into a tracking spreadsheet, a slow, inconsistent process that created bottlenecks during high-volume hiring periods and produced subjective, unstandardized evaluations.

Solution:

Built a Gmail-triggered n8n resume processing pipeline that automatically uploads received resume attachments to Google Drive, downloads and extracts all text content from the PDF, then runs a dual-path AI analysis, Path 1 uses an OpenAI Extract Info agent to pull structured candidate data (name, experience, skills, education); Path 2 uses an OpenAI Message Model to perform fit assessment and scoring against role requirements, both outputs are merged, field-mapped through a code block, and appended as a new row directly into a Google Sheets candidate tracking database.

Result:

Eliminated all manual resume processing, every inbound resume is automatically downloaded, parsed, evaluated across two AI dimensions, and logged in the tracking sheet within seconds of arrival, enabling the hiring team to review pre-analyzed candidates rather than raw documents.