Smart Industrial IoT KPI Assistant with AI Knowledge Base
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This n8n workflow creates a powerful AI assistant for Industrial IoT KPIs, leveraging a Redis vector database for specialized knowledge. It can ingest new data, answer complex queries with contextual understanding, and log all interactions to a Google Sheet, empowering smarter operational decisions.
About This Workflow
Unlock the full potential of your Industrial IoT data with this intelligent n8n workflow. Designed to act as a sophisticated AI knowledge base, it efficiently processes and stores critical KPI information within a Redis vector database. When new data arrives via a webhook, it's automatically chunked, embedded using Cohere, and ingested. Concurrently, the workflow allows for dynamic querying, utilizing an OpenAI-powered agent equipped with conversational memory and access to your specialized Redis knowledge base. This enables on-demand, insightful responses to complex queries, all while meticulously logging every interaction to a Google Sheet for auditing and further analysis. Streamline your industrial operations by transforming raw data into actionable intelligence.
Key Features
- AI-Powered Knowledge Base: Builds and queries a dedicated knowledge base for Industrial IoT KPIs using Redis and Cohere embeddings.
- Intelligent Agent Responses: Leverages OpenAI's chat models with LangChain agents to provide contextual and informed answers to complex queries.
- Conversational Memory: Incorporates buffer window memory for sustained, coherent AI interactions.
- Automated Data Ingestion: Automatically splits, embeds, and stores new IoT data into your vector database via a webhook trigger.
- Comprehensive Logging: Records all AI agent outputs and interactions directly to a Google Sheet for compliance and analysis.
How To Use
- Set up Webhook: Configure the
Webhooknode to receive incoming Industrial IoT KPI data or queries. Note the/industrial_iot_kpi_emailpath. - Configure Credentials:
- Cohere API: Connect your Cohere account credentials to the
Embeddingsnode for text vectorization. - Redis API: Provide your Redis database credentials to both
InsertandQuerynodes, ensuring access to yourindustrial_iot_kpi_emailindex. - OpenAI API: Link your OpenAI account credentials to the
Chatnode for AI model access. - Google Sheets API: Authenticate your Google Sheets account with the
Sheetnode and specify yourSHEET_IDand desiredsheetName(e.g., "Log").
- Cohere API: Connect your Cohere account credentials to the
- Define Agent Prompt: The
Agentnode'stextparameter={{ $json }}indicates it expects the input from the preceding node (likely the Webhook via Memory). Adjust this if your prompt structure differs. - Ingest Data: To populate the knowledge base, send data containing your Industrial IoT KPIs to the Webhook. This data will be split, embedded, and stored in Redis.
- Query the AI: Send queries or prompts to the same Webhook endpoint. The AI agent will use its memory, the Redis knowledge base, and OpenAI to generate a response, which will then be logged to Google Sheets.
Apps Used
Workflow JSON
{
"id": "dbee4a0c-b843-42af-af71-ebe28de42abc",
"name": "Smart Industrial IoT KPI Assistant with AI Knowledge Base",
"nodes": 20,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: dbee4a0c-b843...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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