Automated Production KPI Dashboard with AI Integration
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Streamline your production monitoring with an automated KPI dashboard. This workflow leverages AI to ingest, process, and analyze your production data, providing actionable insights and logging crucial metrics.
About This Workflow
This n8n workflow empowers businesses to create a dynamic and intelligent Production KPI Dashboard. It begins by capturing production data via a webhook, then intelligently splits and embeds this information using AI models (Cohere for embeddings). The processed data is stored and indexed in Weaviate for efficient retrieval. An AI agent, powered by OpenAI's language models and conversational memory, then interprets queries and analyzes the indexed data. Finally, key performance indicators and insights are logged to a Google Sheet for ongoing tracking and reporting. This solution offers a robust way to gain real-time visibility into production performance and drive data-informed decisions.
Key Features
- Real-time Data Ingestion: Capture production metrics as they happen via a webhook.
- AI-Powered Data Processing: Utilize text splitting and embeddings for intelligent data analysis.
- Vector Database Integration: Store and query data efficiently with Weaviate.
- Conversational AI Agent: Interact with your data through an AI agent for deeper insights.
- Automated Logging: Seamlessly export key KPIs and logs to Google Sheets.
How To Use
- Webhook Setup: Configure the 'Webhook' node to receive your production data. Ensure the path matches your desired endpoint (e.g.,
/production_kpi_dashboard). - Data Splitting & Embedding: Adjust the
chunkSizeandchunkOverlapin the 'Splitter' node to optimize text segmentation. Configure the 'Embeddings' node with your Cohere API credentials. - Data Storage: Set up the 'Insert' node with your Weaviate API credentials and specify the
indexName('production_kpi_dashboard'). - AI Agent Configuration: Connect the 'Query' node (pointing to your Weaviate index), 'Tool', 'Memory', and 'Chat' nodes. Ensure you provide your OpenAI API credentials and select a suitable model. The 'Agent' node's
promptTypeshould be set to 'define' and itstextparameter should dynamically receive the incoming data (={{ $json }}). - Google Sheets Logging: Configure the 'Sheet' node with your Google Sheets API credentials,
SHEET_ID, andsheetName('Log') to append the processed results.
Apps Used
Workflow JSON
{
"id": "c8905e7f-2617-4612-8fa0-d406338cae8b",
"name": "Automated Production KPI Dashboard with AI Integration",
"nodes": 10,
"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: c8905e7f-2617...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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