NL2SQL via iterative self-refinement with specialized agents
In brief
- Multi-agent NL2SQL framework with relevance detection and schema-grounded knowledge construction.
- Syntax self-repair via SQLite execution feedback and semantic consistency checks via SQL-to-NL reverse engineering.
- Achieves 90% accuracy on 60 test queries, outperforming direct LLM prompting.
A new NL2SQL framework leverages multiple agents and a persona-driven approach to minimize hallucinations and enhance the accuracy of generated SQL queries. The system integrates relevance detection, schema-grounded knowledge construction, KPI-aware SQL synthesis, and self-repair mechanisms for syntax and semantics.
What it changes for you
- Finance & BankingReduces critical SQL query errors for KPIs and regulatory compliance in insurance.
- Public SectorImproves reliability of SQL queries for legacy relational systems in public administrations.
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