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Resume intelligence and data mining using Decodo with GPT-4o-mini

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Resume intelligence and data mining using Decodo with GPT-4o-mini preview
Open on n8n.io

Important notice

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

1. Workflow Overview

1. Who this is for This workflow is specifically designed for Recruiters, HR analytics teams, and data driven talent acquisition professionals seeking deeper insights from candidate resume. Valuabl...

Best for

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

Tools used

n8n-nodes-base.manualtrigger, n8n-nodes-base.stickynote, @decodo/n8n-nodes-decodo.decodo, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.merge, n8n-nodes-base.googlesheets, @n8n/n8n-nodes-langchain.lmchatopenai

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Resume intelligence and data mining using Decodo with GPT-4o-mini
Workflow name
Resume intelligence and data mining using Decodo with GPT-4o-mini

1. Who this is for

This workflow is specifically designed for

  • Recruiters, HR analytics teams, and data-driven talent acquisition professionals seeking deeper insights from candidate resume.
  • Valuable for HR tech developers, ATS/CRM engineers, and AI-driven recruitment platforms aiming to automate candidate research.
  • Helps organizations build predictive hiring models and gain actionable talent intelligence.

2. What problem this workflow solves

Recruiters often face information overload when analyzing candidate resume manually reviewing experiences, skills, and cultural fit is slow and inconsistent.

Traditional scraping tools extract raw data but fail to produce actionable intelligence like career trajectory, skills alignment, and fit for a role.

This workflow solves that by:

  • Automating candidate resume data extraction through Decodo
  • Structuring it into JSON Resume Schema
  • Running deep AI-driven analytics using OpenAI GPT-4o-mini
  • Delivering comprehensive candidate intelligence ready for ATS/CRM integration or HR dashboards

3. What this workflow does

This n8n workflow combines Decodo’s web scraping with OpenAI GPT-4o-mini to produce advanced recruitment intelligence.

Flow Breakdown:

  1. Manual Trigger – Start the workflow manually or schedule it in n8n.
  2. Set Input Fields – Define resume URL, location, and job description.
  3. Decodo Node – Scrapes the candidate’s profile (experience, skills, education, achievements, etc.).
  4. Structured Data Extractor (GPT-4o-mini) – Converts the scraped data into a structured JSON Resume Schema.
  5. Advanced Data Mining Engine (GPT-4o-mini)

– Performs:

  • Skills Analysis (strengths, gaps, transferable skills)
  • Experience Intelligence (career trajectory, leadership, project complexity)
  • Cultural Fit Insights (work style, communication style, agility indicators)
  • Career Trajectory Forecasting (promotion trends, growth velocity)
  • Competitive Advantage Analysis (market positioning, salary expectations)
  1. Summarizer Node – Produces an abstractive and comprehensive AI summary of the candidate profile.
  2. Google Sheets Node – Saves the structured insights automatically into your recruitment intelligence sheet.
  3. File Writer Node (Optional) – Writes the JSON report locally for offline storage or integration.

The result is a data-enriched candidate intelligence report far beyond what traditional resume parsing provides.

4. Setup

Prerequisites

If you are new to Decode, please signup on this link visit.decodo.com

  • n8n account with workflow editor access
  • Decodo API credentials
  • OpenAI API key
  • Google Sheets account connected via OAuth2

Make sure to install the Decodo Community node.

Setup Steps

  1. Import the workflow JSON into your n8n workspace.

  2. Set credentials for:

    • Decodo Credentials account
    • OpenAI API (GPT-4o-mini)
    • Google Sheets OAuth2
  3. In the “Set the Input Fields” node, update:

    • url → Resume link
    • geo → Candidate region or country
    • jobDescription → Target job description for matching
  4. Ensure the Google Sheet ID and tab name are correct in the “Append or update row in sheet” node.

  5. Click Execute Workflow to start.

5. How to customize this workflow

You can adapt this workflow for different recruitment or analytics scenarios:

Add Sentiment Analysis

Add another LLM node to perform sentiment analysis on candidate recommendations or feedback notes.

Enrich with Job Board Data

Use additional Decodo nodes or APIs (Indeed, Glassdoor, etc.) to compare candidate profiles to live job postings.

Add Predictive Fit Scoring

Insert a Function Node to compute a numerical "fit score" by comparing skill vectors and job requirements.

Automate Candidate Reporting

Connect to Gmail, Slack, or Notion nodes to automatically send summaries or reports to hiring managers.

6. Summary

The Advanced Resume Intelligence & Data Mining via Decodo + OpenAI GPT-4o-mini workflow transforms traditional candidate sourcing into AI-driven intelligence gathering.

It integrates:

  • Decodo → To perform webscraping of data
  • GPT-4o-mini → to interpret, analyze, and summarize with context
  • Google Sheets → to store structured results for real-time analysis

With this system, recruiters and HR analysts can move from data collection to decision intelligence, unlocking faster and smarter talent insights.

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 - When clicking ‘Execute workflow’

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

Block 2 - Sticky Note

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

Block 3 - Decodo

Type / Role
@decodo/n8n-nodes-decodo.decodo - decodo
Config choices
Version 1

Block 4 - Set the Input Fields

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 5 - Structured Data Extractor

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.7

Block 6 - Advanced Data Mining & Profile-Job Analysis

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.7

Block 7 - Sticky Note1

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

Block 8 - Sticky Note2

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

Block 9 - Merge

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 10 - Append or update row in sheet

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 11 - OpenAI Chat Model

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

Block 12 - OpenAI Chat Model for Structured Data Extract

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

Block 13 - Summarizer

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.7

Block 14 - OpenAI Chat Model for Summarizer

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

Block 15 - Structured Output Parser

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

Block 16 - Read/Write Files from Disk

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

Block 17 - Make Binary

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

Block 18 - Extract Structured JSON

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

Block 19 - Extract formatted JSON

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

3. Summary Table

Workflow Resume intelligence and data mining using Decodo with GPT-4o-mini
Complexity advanced
Nodes 19
Categories HR, AI RAG
Author Ranjan Dailata
Published 19 Oct 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/9878/9878.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 Resume intelligence and data mining using Decodo with GPT-4o-mini do?

1. Who this is for This workflow is specifically designed for Recruiters, HR analytics teams, and data driven talent acquisition professionals seeking deeper insights from candidate resume. Valuabl...

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 RAG use case.