mlsanityData to 7 Oct 2026

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

arXiv 2605.21027 ↗First posted 20 May 2026cs.CL cs.AIcited by 1

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

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) promise natural language access to structured data, they fall short in enterprise settings where analytics pipelines rely on governed APIs rather than raw databases. In practice, these APIs encapsulate complex business logic to ensure consistency, auditability, and security. However, delegating mathematical or aggregation logic to an LLM introduces reliability and compliance risks. To this end, we present Analytic Agent, an LLM-based agentic system that translates natural language intents into secure interactions with enterprise analytics APIs. Evaluated on 90 real enterprise use cases constructed by domain experts, it reliably interprets user goals, validates permissions, executes governed queries, and generates compliant visualizations through multi-step reasoning and policy-aware orchestration.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 24 of its 33 references that are in the map. First posted on arXiv 20 May 2026.

Builds on

24 of 33 references.

Closest ancestors · 1

Same direction, newest first

  1. 2025AI Knowledge Assist: An Automated Approach for the Creation of Knowledge Bases for Conversational AI Agents9 Oct

Other references · 23

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  3. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
  4. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  5. 2019Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Datasetcited by 426
  6. 2023AlignScore: Evaluating Factual Consistency with a Unified Alignment Functioncited by 284
  7. 2016Language to Logical Form with Neural Attentioncited by 158
  8. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  9. 2025Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Toolscited by 106
  10. 2020SmBoP: Semi-autoregressive Bottom-up Semantic Parsingcited by 97
  11. 2022Natural Language to Code Generation in Interactive Data Science Notebookscited by 86
  12. 2024A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendationscited by 84
11 more
  1. 2019Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsingcited by 74
  2. 2020NL4DV: A Toolkit for Generating Analytic Specifications for Data Visualization from Natural Language Queriescited by 73
  3. 2025When2Call: When (not) to Call Toolscited by 36
  4. 2023Evaluating Cross-Domain Text-to-SQL Models and Benchmarkscited by 32
  5. 2025CONFETTI: Conversational Function-Calling Evaluation Through Turn-Level Interactionscited by 16
  6. 2025Disambiguate First, Parse Later: Generating Interpretations for Ambiguity Resolution in Semantic Parsingcited by 12
  7. 2025AI Agentic workflows and Enterprise APIs: Adapting API architectures for the age of AI agentscited by 11
  8. 2023AI Coach Assist: An Automated Approach for Call Recommendation in Contact Centers for Agent Coachingcited by 8
  9. 2024DePLOI: Applying NL2SQL to Synthesize and Audit Database Access Controlcited by 6
  10. 2024Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systemscited by 6
  11. 2025InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Informationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

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