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Monitor academic integrity signals with GPT-4o, email alerts and case archiving

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Monitor academic integrity signals with GPT-4o, email alerts and case archiving preview
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1. Workflow Overview

How It Works This workflow automates integrity signal detection and investigation orchestration for compliance officers, ethics teams, and risk managers in financial services, healthcare, and regul...

Best for

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

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.switch, @n8n/n8n-nodes-langchain.agenttool, n8n-nodes-base.if

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title
Monitor academic integrity signals with GPT-4o, email alerts and case archiving
Workflow name
Monitor academic integrity signals with GPT-4o, email alerts and case archiving

How It Works

This workflow automates integrity signal detection and investigation orchestration for compliance officers, ethics teams, and risk managers in financial services, healthcare, and regulated industries. It solves the challenge of identifying potential misconduct while ensuring human judgment governs sensitive investigations. Scheduled triggers initiate assessments on synthetic integrity signals, which flow to an AI agent for severity classification based on risk indicators. High-risk signals route to parallel AI investigation agents: data correlation analysis to uncover patterns and anomaly detection to flag statistical outliers. Results converge at mandatory human review gates where compliance professionals evaluate findings before case creation. Approved investigations generate structured case records, while cleared signals archive automatically with full audit trails.

Setup Steps

  1. Configure Llama-3.1-70B-Instruct model access
  2. Set up schedule trigger for daily or continuous monitoring cycles
  3. Configure risk-based routing logic (Low/High thresholds)
  4. Connect Gmail for human review alerts to compliance officers
  5. Set up Google Sheets for case storage and automated archival

Prerequisites

API key, Gmail account with app password

Use Cases

Financial fraud detection, employee misconduct investigation

Customization

Integrate case management systems, add industry-specific risk models

Benefits

Reduces investigation triage time by 65%, ensures consistent risk assessment methodology

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 - Schedule Trigger

Type / Role
n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices
Version 1.3

Block 2 - Workflow Configuration

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

Block 3 - Simulate Assessment Data

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

Block 4 - OpenAI Model - Integrity Agent

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

Block 5 - Structured Output - Integrity Signals

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

Block 6 - Integrity Signal Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3.1

Block 7 - Route by Risk Level

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

Block 8 - OpenAI Model - Orchestration Agent

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

Block 9 - OpenAI Model - Investigation Tool

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

Block 10 - Investigation Agent Tool

Type / Role
@n8n/n8n-nodes-langchain.agentTool - agentTool
Config choices
Version 3

Block 11 - Structured Output - Investigation

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

Block 12 - Structured Output - Orchestration

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

Block 13 - Case Orchestration Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3.1

Block 14 - Check if Human Review Required

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 15 - Store Case for Human Review

Type / Role
n8n-nodes-base.dataTable - dataTable
Config choices
Version 1.1

Block 16 - Send Human Review Alert

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

Block 17 - Wait for Human Decision

Type / Role
n8n-nodes-base.wait - wait
Config choices
Version 1.1

Block 18 - Store Automated Case

Type / Role
n8n-nodes-base.dataTable - dataTable
Config choices
Version 1.1

Block 19 - Merge All Cases

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

Block 20 - Archive All Cases

Type / Role
n8n-nodes-base.dataTable - dataTable
Config choices
Version 1.1

Block 21 - Prepare Low Risk Response

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

Block 22 - Store Low Risk Case

Type / Role
n8n-nodes-base.dataTable - dataTable
Config choices
Version 1.1

Block 23 - Sticky Note

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

Block 24 - Sticky Note1

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

Showing the first 24 of 28 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Monitor academic integrity signals with GPT-4o, email alerts and case archiving
Complexity advanced
Nodes 28
Categories Document Extraction, AI Summarization
Author Cheng Siong Chin
Published 16 Feb 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/13430/13430.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 Monitor academic integrity signals with GPT-4o, email alerts and case archiving do?

How It Works This workflow automates integrity signal detection and investigation orchestration for compliance officers, ethics teams, and risk managers in financial services, healthcare, and regul...

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 Document Extraction, AI Summarization use case.