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Employee attrition risk detection & HR alerts using Azure OpenAI GPT-4o-mini & Gmail

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Employee attrition risk detection & HR alerts using Azure OpenAI GPT-4o-mini & Gmail preview
Open on n8n.io

Important notice

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

1. Workflow Overview

Description Automatically ingests new employee data, extracts relevant signals, scores attrition risk, and notifies HR/managers with structured insights and recommended actions. Built on Azure Open...

Best for

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

Tools used

@n8n/n8n-nodes-langchain.lmchatazureopenai, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.googledrivetrigger, n8n-nodes-base.googledrive, n8n-nodes-base.extractfromfile, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.if, n8n-nodes-base.code

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Employee attrition risk detection & HR alerts using Azure OpenAI GPT-4o-mini & Gmail
Workflow name
Employee attrition risk detection & HR alerts using Azure OpenAI GPT-4o-mini & Gmail

Description

Automatically ingests new employee data, extracts relevant signals, scores attrition risk, and notifies HR/managers with structured insights and recommended actions. Built on Azure OpenAI Chat with Structured Output Parser and true/false routing for escalation.

What This Template Does

  • Trigger for new data: Starts when a new profile, survey, or report file is added.
  • Download & extract: Retrieves the file and converts PDFs/text into analyzable content.
  • Analyze signals: Uses Azure OpenAI Chat to interpret sentiment, workload, performance notes, feedback, and changes (role, compensation, manager, location).
  • Structured parsing: Maps to fields like risk_score, risk_level, key_drivers, recommended_interventions, escalation_required.
  • Logic routing: Applies thresholds (e.g., risk_score ≥ 0.7) and flags for urgent follow-up.
  • Email alerts: Drafts and sends tailored notifications to HR/manager with action steps.

Key Signals Considered

  • Sentiment & language: Negative tone, burnout cues, disengagement in feedback.
  • Activity trends: Drop in participation, delayed responses, meeting absenteeism.
  • Performance & goals: Recent rating changes, missed OKRs, quality issues.
  • Role & compensation: Lateral moves, pay gaps vs. market, stalled progression.
  • Managerial context: Team churn, conflict mentions, low recognition frequency.

Features

  • Azure OpenAI Chat: Interprets unstructured text into consistent risk fields.
  • Structured Output Parser: Guarantees schema for downstream decisions.
  • Conditional Logic (true/false): Threshold checks for escalation.
  • Memory: Maintains context across multiple files per employee for trend-aware scoring.
  • Calculate avg span: Computes tenure or recency metrics used in risk scoring.
  • Email Composer & Sender: Generates and dispatches HR-ready alerts.

Requirements

  • n8n instance with access to employee data sources (Drive, Inbox, HR folder).
  • Extract From PDF configured for clean text output.
  • Azure OpenAI credentials (e.g., GPT‑4o‑mini) connected to Chat Model.
  • Email service (Gmail/SMTP) set in n8n Credentials.
  • Parser schema aligned to your People Analytics fields (risk_score, drivers, actions).

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 - Azure OpenAI Chat Model

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

Block 2 - Structured Output Parser

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

Block 3 - Trigger for new resume

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

Block 4 - Download resume

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

Block 5 - Extract text

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

Block 6 - Calculate avg span

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.2

Block 7 - Logic

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

Block 8 - Create email

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

Block 9 - Send email to hr

Type / Role
n8n-nodes-base.gmail - gmail
Config choices
Version 2.1

Block 10 - Sticky Note

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

Block 11 - Sticky Note1

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

Block 12 - Sticky Note2

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

Block 13 - Sticky Note3

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

Block 14 - Sticky Note4

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

Block 15 - Sticky Note5

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

Block 16 - Sticky Note6

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

3. Summary Table

Workflow Employee attrition risk detection & HR alerts using Azure OpenAI GPT-4o-mini & Gmail
Complexity advanced
Nodes 16
Categories HR, AI Summarization
Author Rahul Joshi
Published 06 Oct 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/9309/9309.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 Employee attrition risk detection & HR alerts using Azure OpenAI GPT-4o-mini & Gmail do?

Description Automatically ingests new employee data, extracts relevant signals, scores attrition risk, and notifies HR/managers with structured insights and recommended actions. Built on Azure Open...

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.