Prioritize vehicle maintenance with Anthropic Claude using telemetry and history
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 16 nodes and runs on a schedule (every minute). Along the way it connects Anthropic Chat Model.
How it runs
Trigger: On a schedule (every minute).
- Workflow Configuration (Edit Fields (Set)): sets 4 fields: telemetryApiUrl, historicalApiUrl, anomalyThreshold…
- Fetch Real-Time Vehicle Telemetry (HTTP Request): calls an HTTP API
- Fetch Historical Vehicle Data (HTTP Request): calls an HTTP API
- Merge: merges the data from its input branches
- Anomaly Detection Agent (AI Agent): runs an AI agent, with model: Anthropic Model - Anomaly Detection Agent; output parser: Anomaly Detection Output Parser
- Maintenance Prioritization Agent (AI Agent): runs an AI agent, with model: Anthropic Model - Maintenance Prioritization Agent; 1 tool (RUL Calculation Tool); output parser: Maintenance Prioritization Output Parser
- Check Urgency Level (If): checks a condition and branches into true / false
- Format Urgent Alert (Edit Fields (Set)): sets 4 fields: alert_type, notification_required, escalation_level…
- Format Standard Maintenance Record (Edit Fields (Set)): sets 4 fields: alert_type, notification_required, escalation_level…
- Generate Audit Log (Code): runs custom JavaScript code
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (10)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - Merge
n8n-nodes-base.merge - Anthropic Chat Model
@n8n/n8n-nodes-langchain.lmChatAnthropic - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - AI Agent
@n8n/n8n-nodes-langchain.agent - Code Tool
@n8n/n8n-nodes-langchain.toolCode - If
n8n-nodes-base.if - Code
n8n-nodes-base.code
From the author
How It Works This workflow automates predictive maintenance for vehicle fleets by combining real-time telemetry analysis with historical pattern recognition to identify potential failures before they occur. Designed for fleet managers, maintenance…