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) 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 ...
| Authors | Gundeep Singh, Parsa Kavehzadeh, Jing Xia et al. |
|---|---|
| Primary category | cs.CL |
| Published | 20 May 2026 |
| Last updated at source | 15 June 2026 |
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