The Trace Lake

A Trace Lake is proposed as an observability and analysis platform designed for AI agents, whose long-running, probabilistic behavior produces much larger and more complex traces than conventional software systems. Unlike traditional tracing tools that sample data, prioritize real-time inspection, and discard records quickly, it would retain searchable execution histories containing prompts, outputs, reasoning steps, tool calls, and application context so teams can investigate failures, identify recurring patterns, reproduce user issues, and convert production examples into evaluations. The approach requires rapid ingestion and SQL and full-text querying, affordable scalable storage that can remain in customers’ cloud environments, and continuous analysis tools for detecting and testing recurring behaviors. Braintrust positions its Brainstore database as infrastructure built for these requirements, offering trace-oriented query features, nested and unstructured data support, and asynchronous execution through its Nitro engine; it reports faster searches and queries in production testing. The company also describes features such as Topics, Patterns, and Loop automations, and plans to extend the Trace Lake foundation beyond agent traces to include logs, metrics, and conventional system traces.

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