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, offering retrieval and analysis capabilities by combining documentation, historical data, and live mon
The deployment of Archi in February 2026 at CERN's LHC signifies a maturation and practical application of AI agents in complex scientific operations, moving beyond theoretical stages.
This development indicates the increasing capability of AI agents to manage and reason over heterogeneous data in critical, real-world scientific and operational environments, enhancing efficiency and decision-making.
The previous manual or less integrated approaches to managing vast scientific data and operational support are being augmented by autonomous, extensible AI systems, improving response times and analytical depth.
- · Scientific collaborations
- · Particle physics research
- · AI agent developers
- · CERN
- · Manual data integration workflows
- · Legacy IT support systems
- · Organizations slow to adopt AI agents
Increased efficiency and accuracy in complex scientific operational support and data analysis at large-scale facilities like CERN.
Accelerated discovery and operational optimization across other high-stakes scientific and industrial sectors seeking to manage vast, diverse data.
The establishment of new industry best practices for agentic AI deployment in critical infrastructure, driving broader adoption and standardization.
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Read at arXiv cs.AI