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dotscience logo


By Subtree, Inc

Certified enterprise ready

End-to-end MLOps platform which achieves reproducibility, accountability, collaboration, continuous delivery and monitoring across the whole ML (Machine Learning) lifecycle. DevOps workflows for versioning, model training, deployment, and monitoring,

*Requires OpenShift to install

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End-to-end AI Platform for MLOps solving the biggest problems in operationalizing AI: collaboration and deployment. Dotscience connects to data sources and provides the ability to reproducibly do collaborative data engineering, model training, model versioning, model deployment, and model monitoring. Native multi-cloud capability includes on-prem/hybrid/public. Dotscience also provides for management & deployment across remote and local infrastructure, which can be changed dynamically.

Track Runs

Track data and model runs with perfect accuracy, free from manual tracking.


Deploy your best model into production with a click or an API call.


Attach any compute: laptop, GPU rig, enterprise data center or cloud instances, and auto-scale on-demand.


Trace from a model to its training data and back from that to the raw data.


Share knowledge in the team. Fork and merge projects with notebooks using Git-style collaboration.


Statistically monitor models to get an early warning when models behave unexpectedly.


Attach any external datasets while still tracking reproducibility & provenance.


Explore historic runs, see relationships between parameters & metrics.

Additional resources

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