TOOL · GLOBAL
arXiv: AgentNLQ—multi-agent framework for natural-language-to-SQL conversion
Open research framework using multiple specialized LLM agents to convert natural-language queries into SQL. Achieves 78.1% semantic accuracy on the BIRD benchmark by enriching schema representation and using semantic agents.
WHY IT MATTERS
Enables non-technical staff (compliance, risk, operations) to query databases using plain English. Reduces dependency on SQL engineers; accelerates analytics velocity. Fintech and banking ops teams should trial on internal schema.
Source: arXiv · 2026-05-21