Every run recorded. Best run promoted.
Log hyperparameters, metrics, datasets, and artifacts to a persistent lineage graph. Compare any two runs instantly and promote the winner directly to the model registry.
From chaos to a searchable run history
Every training run is a structured record. Parameters, metrics, data hashes, and artifact paths all linked to a single run ID.
Hyperparameter logging
Log any Python dict as parameters. Filter run history by parameter value range to find what worked without scrolling through notebooks.
Metric time-series
Step-by-step metric logging for training curves. Compare loss curves across runs in the same chart to diagnose underfitting vs. overfitting.
Dataset provenance
Hash and register the exact dataset version used in each run. Link back from any production model to the training data it was built on.
Side-by-side run comparison
Select two runs and get a diff of parameters, metrics, and artifacts. Identify the single variable that caused a 4-point AUC gain.
Stop losing experiment results
Free plan includes unlimited runs. No experiment limit.