Archi: Agentic Operations at the CMS Experiment

📰 ArXiv cs.AI

Learn how Archi, an open-source framework, enables agentic operations for scientific collaborations, and how to apply it for efficient data management and reasoning

advanced Published 4 Jun 2026
Action Steps
  1. Deploy Archi as an open-source framework for scientific collaborations
  2. Configure private and extensible agents to retrieve and reason over heterogeneous data sources
  3. Ingest and organize data from various sources using Archi's systematic approach
  4. Test and validate the performance of Archi's agents in retrieving and reasoning over data
  5. Apply Archi's framework to support technical operators in scientific collaborations
Who Needs to Know This

Data scientists, researchers, and technical operators in scientific collaborations, such as the CMS experiment at CERN, can benefit from Archi's automated data ingestion and agent-based reasoning

Key Insight

💡 Archi enables efficient data management and reasoning through automated ingestion and agent-based reasoning, supporting technical operators in scientific collaborations

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🚀 Introducing Archi: an open-source framework for agentic operations in scientific collaborations! 🤖💡

Key Takeaways

Learn how Archi, an open-source framework, enables agentic operations for scientific collaborations, and how to apply it for efficient data management and reasoning

Full Article

Title: Archi: Agentic Operations at the CMS Experiment

Abstract:
arXiv:2606.04755v1 Announce Type: cross Abstract: We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of heterogeneous data sources with the deployment of configurable, private, and extensible agents that retrieve and reason over them. An instance of Archi has been deployed for the Computing Operations team of the CMS experiment at CERN's LHC since February 2026 as a support agent for technical operators, of
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