Block 1 - Schedule Trigger
- Type / Role
- n8n-nodes-base.scheduleTrigger - scheduleTrigger
- Config choices
- Version 1.3
How It Works This workflow automates engineering governance by deploying a multi agent AI system that validates designs, checks compliance, optimises safety, and predicts maintenance needs. Designe...
n8n-nodes-base.scheduletrigger, n8n-nodes-base.set, n8n-nodes-base.httprequest, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.agenttool, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.lmchatanthropic, n8n-nodes-base.merge
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 engineering governance by deploying a multi-agent AI system that validates designs, checks compliance, optimises safety, and predicts maintenance needs. Designed for engineering teams, quality assurance officers, and operations managers in regulated industries, it eliminates manual review bottlenecks and ensures systemic risk issues are escalated promptly. A schedule trigger fetches design specifications and operational data, merges them, then routes to three parallel agent tracks: Design Validation (with Compliance Verification, Resource Coordination, and Testing Validation sub-agents), Safety Optimisation, and Predictive Maintenance. All outputs consolidate into a risk score calculator, which routes by risk level—critical and high issues trigger Slack alerts immediately, while medium and low issues are logged for review.
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 37 workflow blocks. Download the JSON for the full node graph.
| Workflow | Route engineering risks with Anthropic multi-agents and Slack alerts |
|---|---|
| Complexity | advanced |
| Nodes | 37 |
| Categories | Engineering, AI Chatbot |
| Author | Cheng Siong Chin |
| Published | 25 Feb 2026 |
Use the JSON export at /data/workflows/13698/13698.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 engineering governance by deploying a multi agent AI system that validates designs, checks compliance, optimises safety, and predicts maintenance needs. Designe...
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 Engineering, AI Chatbot use case.