EnviSmart: Multi-Agent LLM System for Environmental Data
EnviSmart, a newly implemented production data management system for environmental research, utilizes campus-wide storage infrastructure and LLM-driven agents to enhance data curation across diverse datasets and changing standards. This system prioritizes reliability as a fundamental architectural aspect, featuring a three-track knowledge framework that externalizes governance constraints, domain knowledge for context retrieval, and procedural skills as interconnected, enduring artifacts. Additionally, it incorporates a multi-agent design with distinct roles, where deterministic elements manage crucial tasks such as DOI minting and public dissemination, thereby reducing risks associated with probabilistic LLM outputs that might appear plausible yet be inaccurate. This development is detailed in arXiv:2604.01647v2.
Key facts
- EnviSmart is a production data management system for environmental research.
- It uses LLM-driven agents for FAIR data management.
- The system is deployed on campus-wide storage infrastructure.
- It features a three-track knowledge architecture: governance constraints, domain knowledge, and tool-using procedures.
- The design includes role-separated multi-agent architecture with deterministic components.
- It addresses failure modes from probabilistic LLM pipelines that may produce incorrect outputs.
- Critical actions like DOI minting and public release are handled by deterministic components.
- The system is described in arXiv:2604.01647v2.
Entities
Institutions
- arXiv