OpenLLMetry extends OpenTelemetry with AI-specific instrumentation, giving teams deeper visibility into LLM applications by tracking latency, token usage, and error rates. Deploying it on Shakudo means those insights integrate directly with all other tools in your data and AI ecosystem without requiring extra engineering for pipelines, security, or compatibility.

Without Shakudo, organizations often spend weeks wiring up OpenLLMetry to different observability platforms, maintaining authentication layers, and configuring infrastructure dependencies. On Shakudo, OpenLLMetry runs as part of the AI operating system, so it automatically benefits from unified access controls, resource scaling, and data-sharing across tools already in the environment.

This accelerates operational maturity: troubleshooting can start within hours of deployment instead of requiring long integration cycles, and model performance data becomes immediately available to teams across analytics, product, and ML engineering. The result is measurable business value with less overhead and faster iteration loops.