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🧠 AI NeutralImportance 6/10

PMAx: An Agentic Framework for AI-Driven Process Mining

arXiv – CS AI|Anton Antonov, Humam Kourani, Alessandro Berti, Gyunam Park, Wil M. P. van der Aalst|
🤖AI Summary

Researchers have developed PMAx, an autonomous AI framework that democratizes process mining by allowing business users to analyze organizational workflows through natural language queries. The system uses a multi-agent architecture with local execution to ensure data privacy and mathematical accuracy while eliminating the need for specialized technical expertise.

Key Takeaways
  • PMAx enables non-technical users to perform complex process mining analysis through natural language interactions.
  • The framework uses a privacy-preserving multi-agent architecture that processes data locally rather than sending sensitive information to external AI services.
  • An Engineer agent generates local scripts to run established algorithms while an Analyst agent interprets results and compiles reports.
  • The system addresses key limitations of using LLMs directly for analytics, including hallucination risks and deterministic reasoning challenges.
  • PMAx separates computational tasks from interpretation to ensure mathematical accuracy in process mining results.
Read Original →via arXiv – CS AI
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