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AI resume screening & evaluation for HR with GPT-4 & Google Workspace

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Try It Out, HireMind – AI Driven Resume Intelligence Pipeline! This n8n template demonstrates how to automate resume screening and evaluation using AI to improve candidate processing and reduce man...

Best for

  • HR automation workflows
  • AI Summarization automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.formtrigger, n8n-nodes-base.extractfromfile, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.googlesheets, n8n-nodes-base.googledrive, @n8n/n8n-nodes-langchain.chainllm

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Trung Tran.

Original n8n.io source

1.1 Workflow description

Title
AI resume screening & evaluation for HR with GPT-4 & Google Workspace
Workflow name
AI resume screening & evaluation for HR with GPT-4 & Google Workspace

Try It Out, HireMind – AI-Driven Resume Intelligence Pipeline!

This n8n template demonstrates how to automate resume screening and evaluation using AI to improve candidate processing and reduce manual HR effort.

A smart and reliable resume screening pipeline for modern HR teams. This workflow combines Google Drive (JD & CV storage), OpenAI (GPT-4-based evaluation), Google Sheets (position mapping + result log), and Slack/SendGrid integrations for real-time communication. Automatically extract, evaluate, and track candidate applications with clarity and consistency.


How it works

  • A candidate submits their application using a form that includes name, email, CV (PDF), and a selected job role.
  • The CV is uploaded to Google Drive for record-keeping and later reference.
  • The Profile Analyzer Agent reads the uploaded resume, extracts structured candidate information, and transforms it into a standardized JSON format using GPT-4 and a custom output parser.
  • The corresponding job description PDF file is automatically retrieved from a Google Sheet based on the selected job role.
  • The HR Expert Agent evaluates the candidate profile against the job description using another GPT-4 model, generating a structured assessment that includes strengths, gaps, and an overall recommendation.
  • The evaluation result is parsed and formatted for output.
  • The evaluation score will be used to mark candidate as qualified or unqualified, based on that an email will be sent to applicant or the message will be send to hiring team for the next process
  • The final evaluation result will be stored in a Google Sheet for long-term tracking and reporting.

Google drive structure

├── jd # Google drive folder to store your JD (pdf) │ ├── Backend_Engineer.pdf │ ├── Azure_DevOps_Lead.pdf │ └── ... │ ├── cv # Google drive folder, where workflow upload candidate resume │ ├── John_Doe_DevOps.pdf │ ├── Jane_Smith_FullStack.pdf │ └── ... │ ├── Positions (Sample: https://docs.google.com/spreadsheets/d/1pW0muHp1NXwh2GiRvGVwGGRYCkcMR7z8NyS9wvSPYjs/edit?usp=sharing) # 📋 Mapping Table: Job Role ↔ Job Description (Link) │ └── Columns: │ - Job Role │ - Job Description File URL (PDF in jd/) │ └── Evaluation form (Google Sheet) # ✅ Final AI Evaluation Results

How to use

  1. Set up credentials and integrations:

    • Connect your OpenAI account (GPT-4 API).
    • Enable Google Cloud APIs:
      • Google Sheets API (for reading job roles and saving evaluation results)
      • Google Drive API (for storing CVs and job descriptions)
    • Set up SendGrid (to send email responses to candidates)
    • Connect Slack (to send messages to the hiring team)
  2. Prepare your Google Drive structure:

    • Create a root folder, then inside it create:
      • /jd → Store all job descriptions in PDF format
      • /cv → This is where candidate CVs will be uploaded automatically
    • Create a Google Sheet named Positions with the following structure:
      | Job Role                     | Job Description Link                   |
      |------------------------------|----------------------------------------|
      | Azure DevOps Engineer        | https://drive.google.com/xxx/jd1.pdf   |
      | Full-Stack Developer (.NET)  | https://drive.google.com/xxx/jd2.pdf   |
      
  3. Update your application form:

    • Use the built-in form, or connect your own (e.g., Typeform, Tally, Webflow, etc.)
    • Ensure the Job Role dropdown matches exactly the roles in the Positions sheet
  4. Run the AI workflow:

    • When a candidate submits the form:
      • Their CV is uploaded to the /cv folder
      • The job role is used to match the JD from /jd
      • The Profile Analyzer Agent extracts candidate info from the CV
      • The HR Expert Agent evaluates the candidate against the matched JD using GPT-4
  5. Distribute and store results:

    • Store the evaluation results in the Evaluation form Google Sheet
    • Optionally notify your team:
      • ✉️ Send an email to the candidate using SendGrid
      • 💬 Send a Slack message to the hiring team with a summary and next steps

Requirements

  • OpenAI GPT-4 account for both Profile Analyzer and HR Expert Agents
  • Google Drive account (for storing CVs and evaluation sheet)
  • Google Sheets API credentials (for JD source and evaluation results)

Need Help?

Join the n8n Discord or ask in the n8n Forum!

Happy Hiring! 🚀

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 2 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 3 - Application form

Type / Role
n8n-nodes-base.formTrigger - formTrigger
Config choices
Version 2.2

Block 4 - Extract profile

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 5 - json parser

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 6 - gpt4-1 model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 7 - Get position JD

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.6

Block 8 - Download file

Type / Role
n8n-nodes-base.googleDrive - googleDrive
Config choices
Version 3

Block 9 - Extract Job Description

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 10 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 11 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 12 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 13 - HR Expert Agent

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.5

Block 14 - Profile Analyzer Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.1

Block 15 - Update evaluation sheet

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.6

Block 16 - Map Columns

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 17 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 18 - Upload to Google Drive

Type / Role
n8n-nodes-base.googleDrive - googleDrive
Config choices
Version 3

Block 19 - gpt-4-1 model 2

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 20 - json parser 2

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 21 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 22 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 23 - Sticky Note8

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 24 - Send email to candidate about the result

Type / Role
n8n-nodes-base.sendGrid - sendGrid
Config choices
Version 1

Showing the first 24 of 26 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow AI resume screening & evaluation for HR with GPT-4 & Google Workspace
Complexity advanced
Nodes 26
Categories HR, AI Summarization
Author Trung Tran
Published 29 Jul 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/6612/6612.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does AI resume screening & evaluation for HR with GPT-4 & Google Workspace do?

Try It Out, HireMind – AI Driven Resume Intelligence Pipeline! This n8n template demonstrates how to automate resume screening and evaluation using AI to improve candidate processing and reduce man...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your HR, AI Summarization use case.