Run:ai serves each of the AI/ML team members
Data Scientists
Intergrations
Connect to the Experiment Tracking or ML tool of your choice
Friendly UI
Spin up a new environment without the pain of secure remote connection or cumbersome CLIs
Templates
Use pre-defined environments with your compute and data pipeline already provisioned
GPU Scheduler
Gain on-demand access GPUs so you won't need to worry about securing GPU slots
MLOps Engineers
Quota Management
Make sure each of your Data Scientists get their fair-share of compute access
Bin Packing
Combine compute resources for memory-intense Jobs like HPO and Batch Training
Node Pools
Configure predefined collections of compute types and data sources for your teams to use
GPU Fractioning
Run multiple Jupyter Notebooks and Inference workloads on the same GPU
DevOps and IT
Access control and IAM
Sync your AI/ML environments with your organization's LDAP directory and SSO platform
Multi-Cluster Support
Scale and manage your infrastructure on multi/hybrid clusters from one place
Policies
Configure which teams and roles have access to which projects and nodes using only a few clicks
Audit Log
Historical workloads and usage logs designed to meet compliance and audit requirements
