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To ensure the quality of AI agents, evaluation needs to happen at each step, i.e., for LLM generation, planner action, tool call, etc. With Maxim’s observability and evaluation suite, you can attach custom evaluators to each level of your logging hierarchy (trace, span, or component within the span).
Key features:
🔍 Granular monitoring: Log and evaluate each step of your agentic workflow in real time. Continuously monitor quality at each step and define alerts for proactive issue resolution.
💻 SDK support: Integrate tracing and evaluation directly from your code using programming language support offered by Maxim.
📊 Metrics: Track key metrics such as cost, latency, and evaluator scores for each node.
This ensures you gain actionable insights into every part of your AI agent's operations, helping you debug faster and maintain production-grade performance. Learn more.