Automatic Experiment Logging With Sdk Instrumentation

Open-source MLOps — experiment tracking, pipelines, data management, auto-logging, self-hosted.

Unique: Uses framework-level monkey-patching to intercept training operations across PyTorch, TensorFlow, and scikit-learn without requiring code changes, combined with a centralized Task context object that manages metric buffering and async streaming to the server

vs others: Requires zero code changes to existing training scripts unlike Weights & Biases or Neptune, which require explicit logging calls, though this comes at the cost of potential instrumentation conflicts