Shakti AI Workspace is a powerful platform that enables seamless management of AI/ML workloads, allowing users to access GPU resources, run jobs, and monitor experiments through an intuitive GUI or CLI.

Shakti AI Workspace offers real-time monitoring and the ability to run AI/ML models on high-performance GPUs like H100 and L40s, all within an NGC supported Jupyter based environments.

Yes, Shakti AI Workspace supports popular frameworks like Tensorboard, ML Comet, WanDB, ML Flow, any libraries, IDEs, and tools, ensuring you can work with your preferred solutions without disruption.

Absolutely! Shakti AI Workspace offers both a user-friendly GUI and a command-line interface, giving users the flexibility to work the way they prefer.

Real-time monitoring of the workload is available in the platform that provides instant insights into job performance, resource utilization, and experiment status, with alerts and dashboards to help you stay in control from anywhere.

Yes, with browser-based access and a robust CLI, you can manage, monitor, and collaborate on your AI projects from anywhere in the world.

Yes, Shakti AI Workspace enables seamless collaboration, allowing teams to share data, experiments, and resources efficiently.

Shakti AI Workspace ensures enterprise-grade security with encrypted access, role-based permissions, and secure data storage.

Yes, the platform supports ML Ops workflows, making it easy to manage the entire lifecycle of your models, from training to deployment.

Yes, the user can bring his own docker image in Shakti AI Workspace.