A framework-neutral, full-lifecycle Agent management platform for Agent developers and teams—purpose-built to tackle the challenges AI Agents face across development, debugging, evaluation, and production operations.
Loop is a framework-neutral, full-lifecycle Agent management platform for Agent developers and teams. It focuses on solving the challenges AI Agents face throughout their entire lifecycle—from development and debugging to evaluation and production operations.
Loop covers the key stages of the Agent lifecycle: tracing runtime behavior and quantifying output quality—supporting efficient development and stable operations with a single toolset.
End-to-end visualization that completely records every stage from input to output—prompt parsing, model invocation, tool execution, and memory read/write—automatically capturing latency, token consumption, and exceptions. Quickly locate errors and performance bottlenecks, turning a "black box" into "transparent decision-making." Online traces can also be distilled into evaluation datasets and converted into regression cases.
Perform multi-dimensional automated evaluation of AI Agents (accuracy, conciseness, compliance, and more). Rapidly build evaluation datasets, complete end-to-end quality verification with preset LLM graders, and support cross-version comparison—making outputs quantifiable and comparable.
What Loop Can Do
Loop covers the key stages of the Agent lifecycle: tracing runtime behavior and quantifying output quality—supporting efficient development and stable operations with a single toolset.
Observability
End-to-end visualization that completely records every stage from input to output—prompt parsing, model invocation, tool execution, and memory read/write—automatically capturing latency, token consumption, and exceptions. Quickly locate errors and performance bottlenecks, turning a "black box" into "transparent decision-making." Online traces can also be distilled into evaluation datasets and converted into regression cases.
Evaluation
Perform multi-dimensional automated evaluation of AI Agents (accuracy, conciseness, compliance, and more). Rapidly build evaluation datasets, complete end-to-end quality verification with preset LLM graders, and support cross-version comparison—making outputs quantifiable and comparable.
Why Choose Loop
- Framework-neutral, plug-and-play: Built on the OpenTelemetry GenAI open standard—integrate any framework or runtime quickly.
- End-to-end observability: Full-chain visualization across debugging, evaluation, and production—precisely locate errors and bottlenecks.
- Out-of-the-box evaluation: Preset graders plus end-to-end, ready-to-use statistical metrics.
- Native resource-layer support: Runtime / sandbox / browser / memory / gateway available natively and dynamically orchestrated.
- Team collaboration, unified inside and out: Share experiment results—collaborate within the platform or serve external ecosystems as a neutral standalone site.