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,
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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 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.
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