Different AI workloads. One production standard.

Explore operational patterns for customer-facing agents, knowledge systems, internal automation, and high-volume model APIs.

Support platform engineer reviewing an AI agent run

Use case

Move from a failed customer response to the exact retrieval, tool, or model step that caused it.

Customer support agents

Machine learning engineer reviewing retrieval results

Use case

See whether an answer failed in retrieval, reranking, context assembly, or generation.

Retrieval and knowledge systems

Operations engineers collaborating at a workstation

Use case

Give every automated action a trace, an owner, and a release version.

Internal operations agents

Backend engineer monitoring a model-powered API

Use case

Treat model latency, token cost, and output failures as production service signals.

Model-powered APIs