Block 1 - Schedule Trigger
- Type / Role
- n8n-nodes-base.scheduleTrigger - scheduleTrigger
- Config choices
- Version 1.3
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...
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
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.
Original n8n.io sourceThis 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.
API key, Gmail account with app password
Financial fraud detection, employee misconduct investigation
Integrate case management systems, add industry-specific risk models
Reduces investigation triage time by 65%, ensures consistent risk assessment methodology
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.
Showing the first 24 of 28 workflow blocks. Download the JSON for the full node graph.
| 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 |
Use the JSON export at /data/workflows/13430/13430.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
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.
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...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
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.