Gmail Resume Parsing to Parseur + Groq Fit Score (n8n)

Automatically parse resumes from Gmail, score candidate fit with Groq, and track everything in Google Sheets

This n8n workflow monitors your Gmail inbox for resume attachments, extracts candidate data using Parseur, generates a 1–10 AI fit score with Groq, then archives the original resume in Google Drive and records results in a Google Sheets tracker.

What this workflow does

• Polls Gmail every minute for new emails that include resume attachments in PDF/DOC/DOCX formats.
• Downloads the email and attachments, then submits the resume file to Parseur for parsing.
• Waits briefly, calls the Parseur API, and retrieves the latest parsed metadata and extracted candidate fields as JSON.
• Skips processing when the extracted “Candidate Name” field is empty.
• Builds a standardized base filename and document ID from the extracted candidate fields.
• Uses Groq (LLM) to generate a fit score from 1 to 10 for the role.
• Downloads the original resume from Parseur, uploads it to Google Drive, and then appends or updates the candidate record in Google Sheets with candidate details, fit score, and the Drive link (by email).

Use cases

• Centralize inbound applications by inbox label and keep a live candidate CRM in Google Sheets.
• Automatically extract resume fields for faster review and reduce manual copy/paste.
• Use a consistent Groq-driven scoring output to triage resumes at scale.
• Archive every resume in Google Drive with direct links stored in your tracker.

Technical details

• n8n nodes/workflow components: gmail, if, code, no op, wait, and sticky note.
• Integrations: Gmail OAuth + configurable Gmail search query; Parseur parserId and API authentication headers; Groq via LangChain Groq chat model; Google Drive folder upload; Google Sheets append/update tracker.
• Designed for n8n users, automation engineers, and SaaS operators building resume parsing and candidate tracking pipelines.