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New AgentOnto LLM agent uses ontology for enterprise data analytics

Researchers have developed AgentOnto, an LLM agent designed for enterprise data analytics that utilizes an ontology to guide its analysis and incorporate feedback. This approach organizes heterogeneous enterprise knowledge, enabling the agent to connect analytical requests with data distributed across various sources. AgentOnto has demonstrated superior performance compared to existing methods in evaluations on public datasets, with specific module-level assessments confirming the efficacy of its ontology construction, analysis, and updating capabilities. A real-world deployment further validated its practical utility in enterprise settings. AI

IMPACT Enhances enterprise data analysis by providing a structured, ontology-guided approach for LLM agents, improving accuracy and adaptability.

RANK_REASON The cluster describes a new research paper detailing an ontology-guided LLM agent for data analytics. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New AgentOnto LLM agent uses ontology for enterprise data analytics

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The cluster describes a new research paper detailing an ontology-guided LLM agent for data analytics. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dayan Pan, Bincheng Zuo, Xiaojian Wang, Daogang Zhang, Jingyuan Wang ·

    AgentOnto: Ontology-Guided LLM Agents for Enterprise Data Analytics

    arXiv:2610.23317v1 Announce Type: new Abstract: Enterprise data analysis requires agents to connect analytical requests with knowledge distributed across databases, business documents, and existing example tasks. Without an explicit representation of this knowledge, an agent may …