Opik provides a structured way to evaluate, monitor, and debug LLM-powered applications by logging traces, running experiments, and visualizing performance metrics. On its own, teams often face challenges integrating Opik into production environments because infrastructure setup, access management, and scaling require significant engineering cycles.

Running Opik on Shakudo eliminates these hurdles. Instead of dedicating time to custom deployments or building connectors, Opik immediately plugs into the existing AI ecosystem Shakudo orchestrates. Data pipelines, authentication, and observability tools are unified, letting Opik focus solely on evaluation while the operating system handles environment consistency and interoperability with other AI components.

The result is that organizations can iterate faster. Evaluations that previously took weeks to configure safely in a production-like environment are now launched in days, with experiments feeding seamlessly into the rest of the AI stack. Instead of maintaining infrastructure, teams spend effort refining model behavior and driving business outcomes.