Notebooks, models, and MLOps — natively integrated.
A complete data science workspace that runs directly on your governed data. Jupyter and VS Code environments, model registry, experiment tracking, and one-click deploy to production endpoints — all under platform governance.
Notebook Workspaces
Auto-scaling Jupyter and VS Code environments with first-class access to warehouse tables, vector stores, and the model registry.
Experiment Tracking
Every run, parameter, metric, and artifact captured automatically — search, compare, and promote models with full reproducibility.
One-Click Deploy
Promote any model from notebook to managed serving endpoint with autoscaling, A/B testing, and integrated observability.
From hypothesis to production endpoint.
Data scientists shouldn't need to leave the platform to ship a model. Genedata Data Science integrates natively with your warehouse, governance, and CI/CD — so the path from notebook to production is days, not quarters.
Architecture for the model registry, training-to-serving pipeline, and integrated experiment tracking.
Request Documentation