Coze Loop is an open-source AI agent observability and optimisation platform from the Coze team at ByteDance. It addresses the full lifecycle of agent development, from development and debugging through evaluation to production monitoring, with prompt management, automated evaluation and end-to-end tracing of agent runs. The project has more than 5,700 stars on GitHub and saw active development through 2026.
Once agents move beyond demos, teams need to see why an agent answered the way it did and whether a prompt change actually helped. Coze Loop provides a playground for debugging prompts and agents, visualisation of complete execution traces across LLM calls and tools, evaluation datasets with experiment comparison, and monitoring for live traffic. It grows out of the same ecosystem as the Coze agent platform and the Eino framework, and is aimed at teams operating agents as real products. In practice that means treating prompts as versioned assets, scoring model and agent changes against fixed evaluation sets before release, and alerting when production quality drifts. The platform is built to be deployed inside a company’s own infrastructure, which matters for teams whose traces contain sensitive user data that cannot be sent to a third-party analytics service. Dashboards summarise quality and cost trends across releases.
Freemium. The open-source edition is free to self-host; a commercial edition with additional enterprise capabilities is offered for organisations that need it.
Engineering and platform teams shipping LLM agents to production who need observability, systematic evaluation and prompt lifecycle management rather than guesswork.