The proliferation of artificial intelligence (AI) agents and the vast amount of observability data they generate poses significant challenges for companies seeking to refine these agents and ensure their effective operation. Observability data encompasses various aspects, including agent tools used, system prompts, user interactions, data source queries, and large language model responses over time. This data is crucial for understanding AI agent performance, user engagement levels, and areas where improvements are needed. However, managing this vast amount of complex data requires a robust solution to store, process, and analyze it effectively. A scalable, performant, and flexible database is essential for handling diverse data types, providing real-time monitoring needs, and ensuring reliability and integrity in the information being accessed and processed. By choosing the right database, companies can unlock the full potential of their AI agents, ensure they remain robust and efficient, and gain a competitive edge in delivering superior customer experiences.