On-Demand AI Infrastructure

Use open-source and commercial tools to empower every team to use any programming language, tool, library, or GenAI package they need to innovate quickly. Plug into the rapidly evolving AI ecosystem and capture innovations in GenAI in real-time.

Environments streamline processes across projects and teams. Easily select your preferred Workspace environment, create your own, or edit an environment. Use your preferred IDE, such as Jupyter, Jupyterlab, VSCode, or R-studio. Easily specify on-demand memory, CPU cores, and GPUs with hardware tiers.

Domino can dynamically provision and orchestrate distributed clusters directly on your instance. This allows Domino users quick access to distributed compute without relying on their IT team. Instantly spin-up distributed compute clusters (Ray, Spark, Dask) for computationally intensive data prep and model training.

Easily access any structured and unstructured data from any source — databases, data lakes, and cloud storage. Discover and use data from any cloud or on-premises and honor data locality and sovereignty by running your workload close to the data.

Automatically version and track data for full auditability and reproducibility. Govern access to sensitive data with granular access controls and permissions.

Optimize compute spend by balancing workloads across on-premises and clouds. Auto-scale and auto-shutdown to meet dynamic team needs, paying only for what you use. Pause and resume expensive compute resources without losing data. Use raw compute resources without any markup. Track and proactively manage costs with budgets, limits, and alerts to eliminate unexpected cost overruns.

Nexus unifies silos for data science workloads across hybrid and multi-cloud environments. It centralizes data access, eliminates costly data movement, and enables seamless incremental cloud migration while avoiding vendor lock-in. Access data anywhere, in any region, and comply with data locality requirements.