About Neptune.ai
An experiment tracking and metadata platform focused on large-scale model training and deep debugging of model internals.
Key Features
- High-scale experiment tracking — log large numbers of per-layer metrics (losses, gradients, activations).
- Visualization & querying — fast rendering and querying of massive metric tables and charts.
- Run forking & lineage — fork runs, inspect lineage, and inherit training history for reproducibility.
- Flexible deployment — cloud and self-hosted (Kubernetes/Helm) deployment options.
Use Cases & Best For
Teams training very large models who need scalable metric logging and deep debugging.
ML engineers who require fast querying and visualization of high-volume training telemetry.
About MLOps & Monitoring
Model operations and lifecycle management