Building a Production-Ready Optimised Text-to-SQL AI System Using LLMs, Vector Databases, and Schema Intelligence Artificial Intelligence is changing the way users interact with databases. Instead of writing SQL manually, users now expect to ask questions like: “Show me revenue by city for the last 6 months.” or “Which candidates cleared the technical interview with scores above 80?” and instantly receive the correct SQL query and chart. This is called Text-to-SQL Generation . In this blog, we will learn how to build a production-grade Text-to-SQL AI system using: LLMs (GPT/OpenAI) PostgreSQL pgvector Ruby on Rails Schema metadata Join intelligence Vector search SQL validation Semantic layers We will also cover a real-world ATS (Applicant Tracking System) example with: Jobs Candidates Applications Interview stages Scores Recruiters This article is designed for developers building: AI dashboards AI analytics platforms AI copilots BI systems Interna...
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