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Analytic Agent system translates natural language to enterprise API queries

By PulseAugur Editorial · [2 sources] ·

Researchers have developed an agentic LLM system called Analytic Agent designed to bridge the gap between natural language queries and enterprise analytics APIs. This system aims to overcome the limitations of traditional Text-to-SQL methods by securely interacting with APIs that contain complex business logic, ensuring consistency and compliance. Analytic Agent has been evaluated on 90 real-world enterprise use cases, demonstrating its ability to interpret user goals, validate permissions, and generate compliant visualizations through multi-step reasoning. AI

IMPACT Enables non-technical users to securely query enterprise data via APIs, improving accessibility and compliance for business intelligence.

RANK_REASON The cluster contains an academic paper detailing a new system for enterprise analytics.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Analytic Agent system translates natural language to enterprise API queries

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Research
The cluster contains an academic paper detailing a new system for enterprise analytics.
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2 independent sources
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paper, product
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High
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156 days old
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Gundeep Singh, Parsa Kavehzadeh, Jing Xia, Xue-Yong Fu, Julien Bouvier Tremblay, Md Tahmid Rahman Laskar, Vincent Lum, Shashi Bhushan TN ·

    Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs

    arXiv:2605.21027v1 Announce Type: cross Abstract: Enterprise analytics aims to make organizational data accessible for decision-making, yet non-technical users still face barriers when using traditional business intelligence tools or Text-to-SQL systems. While recent Text-to-SQL …

  2. arXiv cs.AI TIER_1 English(EN) · Shashi Bhushan TN ·

    Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs

    Enterprise analytics aims to make organizational data accessible for decision-making, yet non-technical users still face barriers when using traditional business intelligence tools or Text-to-SQL systems. While recent Text-to-SQL approaches based on Large Language Models (LLMs) p…

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