Automate CV screening and applicant scoring from Gmail to Airtable with AI
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 11 nodes and runs on Gmail events. Along the way it connects Google Gemini Chat Model, Gmail and Airtable.
How it runs
Trigger: On Gmail events.
- Extract Job Code (Edit Fields (Set)): sets or maps fields
- Read CV (PDF) Text (Extract from File): extracts data from a file (pdf)
- Find Job Post (Airtable): search
- AI CV Parser (Information Extractor): extracts structured fields from text with AI, with model: Google Gemini Chat Model
- Combine Job & CV Data (Merge): merges the data from its input branches
- AI Applicant Scorer (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model; output parser: Structured Output Parser
- Save Applicant (Airtable): create
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
- Still check Gmail Trigger below v1.4 runs as v1.4 (drafts skipped, max emails per poll) (Watch for New Applications).
Nodes used (9)
- Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Gmail Trigger
n8n-nodes-base.gmailTrigger - Edit Fields (Set)
n8n-nodes-base.set - Airtable
n8n-nodes-base.airtable - Extract from File
n8n-nodes-base.extractFromFile - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - Merge
n8n-nodes-base.merge - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm
From the author
Quick overview This workflow automatically processes job applications received via Gmail. It extracts the job code from the email subject and parses the attached CV using Gemini AI to retrieve applicant details.Each applicant is then scored against job…