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VAISense Automation AI Agent

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This tool provides the engineering referencing with GenAI AI Agents.

  • Monitor the sensors threshold value, send notification to contact points
  • Evaluate current sensors confidence based on Z-Score calculation
  • Evaluate streaming data window based on standard deviation, mean value
  • Summaries above results in GenAI LLM response
  • Dump the chat history into local file

Video AI, Sound AI and Vibration AI are customized function on demand

GenAI options; defalult LLM model is Gemini

  • "CH": Ask LLM response in Chinese
  • "RESET": Initiate a new GenAI session
  • "RAG": Ask GenAI answer the questions according to the provided information
  • "Choose a LLM": Select LLM model
  • "temperature": To make the output more deterministic, predictable, and factual.

IOT AI

  • "VIB": Vibration AI
  • "SOUND": Sound AI
  • "VID": Video AI

Predefined query example

  • Ask "How is the machine tool machining confidence according to current measurement?"
  • Ask "Continue to show the evaluation value result and tell me how to troubleshoot it according to the health confidence evaluation result?"
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VAISense Automation now support MCP

VAISense Automation offers MCP endpoints. Simply provide the schema to Edge IT. Now your project can leverage the GenAI LLM function. Besides, you can choose our Edge OT to adapt raw IOT data with AI inference capability.

The Edge OT is built with multi dockers app to process and format and analyze raw data, With InfluxDB to store the time series raw data, MTConnect to sematic accumulate the data analysis result and physical AI inference, the Edge OT is designed to be a multi MCP servers to provide LLM to get the associated information regarding to the user's prompt.

The GenAI factory trial field on the way

We like to announce that VAISense Automation GenAI Assistant is beginning to be designed in a machine tool based production factory. With the VA GenAI Assistant, the factory can understand the operation procedure efficiency and help to optimize the manufacturing process by fine tuning the program.

The core key data is extracted from "Smart Tool Holder", which can sense the torque of cutting force in three dimensions. By using the time series data, the Assistant can interpret the historical machining quality trend, current status quality and answer the question for machining operation.