Text-to-SQL solution powered by Amazon Bedrock

This article explains how to build a text-to-SQL solution using Amazon Bedrock that converts natural language business questions into database queries and returns synthesized answers.

• Transforms business questions into SQL queries executed against data warehouses in seconds
• Solves three key barriers: SQL expertise gaps, BI tool flexibility limits, and semantic understanding challenges
• Uses Amazon Bedrock AgentCore for orchestration, GraphRAG for business context, and deterministic SQL validation
• Five-stage workflow: question analysis, knowledge graph retrieval, SQL generation, parallel compute, response synthesis
• Knowledge graph on Amazon Neptune and OpenSearch encodes metric definitions and business terminology
• Deterministic SQL validators catch semantically incorrect queries before execution
• Row-Level Security automatically injected to enforce data access controls
• Parallel agent execution and token optimization reduce latency to 3-5 seconds for simple queries
• Enables non-technical users to perform complex multi-table analysis without SQL knowledge

The solution democratizes data access by combining LLMs, knowledge graphs, and validation layers to deliver accurate, fast analytics accessible to business users without technical barriers.