Glossary
Observability
The ability to understand an AI agent's internal state and behavior through comprehensive monitoring of its outputs, logs, and metrics.
What is Observability?
Observability goes beyond simple monitoring by providing deep visibility into why an agent behaves as it does. It encompasses structured logging, performance metrics, decision traces, and behavioral analytics that enable operators to diagnose issues, optimize performance, and ensure compliance. High observability allows teams to quickly identify when an agent deviates from expected behavior patterns.
For AI agents handling critical tasks, observability is essential for building trust and meeting regulatory requirements. It enables post-hoc analysis of decisions, real-time anomaly detection, and continuous improvement through data-driven insights into agent performance across various scenarios and edge cases.
Example
An e-commerce agent shows declining conversion rates. Through observability tools, operators trace the issue to a subtle change in product recommendation logic that occurred after a routine update, allowing them to quickly roll back the problematic change.
How Signet addresses this
Signet's trust scoring relies heavily on observability data across all five dimensions. Agents with comprehensive logging and transparent decision-making earn higher scores, particularly in the Quality and Security dimensions where behavioral insight is critical.
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Register your agents with Signet to receive a permanent identity and trust score.