Question: I'm looking for a tool that allows me to easily set up and manage AI workflows on both cloud and on-premises infrastructure.

If you need a tool to orchestrate and manage AI workflows on both cloud and on-premises infrastructure, Anyscale is a great option. It lets you build, deploy and scale AI applications on a variety of clouds and on-premises environments. Anyscale includes workload scheduling with queues, intelligent instance management, and GPU/CPU fractionalization for efficient use of resources. It also supports a variety of AI models and integrates with popular IDEs and other tools for a streamlined workflow.

Another powerful option is Clarifai, which lets companies build, manage and operationalize AI projects at scale on-premises or in the cloud. Clarifai makes it easier to move AI prototypes into production by standardizing workflows and increasing productivity. It includes automated data labeling, generative AI and content moderation, and is designed for no-code and low-code users.

dstack is another open-source engine that automates infrastructure provisioning for AI workloads running on a variety of cloud providers and data centers. It supports AWS, GCP, Azure and other cloud services, as well as on-prem servers, making it easier to set up and run AI workloads. dstack offers a variety of deployment options and detailed documentation to help you get up and running with your AI workloads.

For a more complete platform that handles data curation, model management and pipeline orchestration, Dataloop is worth a look. It speeds up AI application development by handling large amounts of unstructured data, automating preprocessing and deploying AI models. Dataloop also incorporates human feedback and has strong security controls, so it's good for improving collaboration and development speed within an organization.