Six recipes for reaching near-100% accurate Text-to-SQL

In the world of agentic applications, natural language is the standard user interface. Today’s AI capabilities provide a great opportunity to enable natural language interactions with your enterprise data, but it can be hard to reach 100% accuracy.

We’ll detail six production-ready architectural patterns for getting close to 100% accuracy, or “hill-climbing" as it’s known in the AI world, using Google’s QueryData API in databases like AlloyDB, Spanner, and Cloud SQL. You’ll learn:

• The importance of near-100% accurate, explainable, and relevant results
• Techniques for building an accurate, flexible, and secure natural language interface to your agent
• How to try these techniques yourself via a self-driven codelab