Building AI Agent Systems with LlamaIndex and SkySQL: A No-Code Approach to Reliable Text-to-SQL

AI agents simplify interaction with complex systems by turning natural language requests into actions—retrieving data, processing information, and automating workflows. One critical task these agents perform is querying operational databases, which store essential business data like customers, transactions, and inventory. However, traditional text-to-SQL approaches often fail due to the complexity of real-world databases, leading to inaccurate results.

In this webinar, we’ll explore how LlamaIndex simplifies AI application development by orchestrating workflows, agentic retrieval-augmented generation (RAG), and vector database integration. We’ll also show how SkySQL, a cloud DBaaS platform, leverages LlamaIndex to automatically interpret database data and metadata—while empowering domain experts to incorporate missing relationships and semantics—to significantly improve SQL generation accuracy. Join us to explore the underlying architecture, see LlamaIndex and SkySQL in action, and share the key lessons gained from our no-code agent builder implementation.

Key Takeaways:

• AI agents can reason through ambiguous natural language queries, plan multi-step actions, and execute them using various tools.
• LlamaIndex streamlines AI app development, enabling efficient agent workflows, RAG, and database integration.
• SkySQL enables developers to create AI database agents that offer reliable text-to-SQL responses. These agents seamlessly integrate into applications or are leveraged by other agents through APIs.

Learn how LlamaIndex and SkySQL make building AI agent systems faster, easier, and more reliable.