DataRobot vs Paperspace Gradient

DataRobot is a platform for developing, delivering, and governing agentic, generative, and predictive AI solutions. Its Agent Workforce Platform supports building production agents, deploying them across infrastructure, and governing them organization-wide. Development tools include data and tool registries, a vector store, code-first workflows, and workflow evaluation and comparison. Integrations cover business applications, LLMs, APIs and frameworks, data platforms, and AI infrastructure, with documented connections to AWS, Azure, Google Cloud, and Snowflake. The platform can run on-premise, in a virtual private cloud, or as software as a service. DataRobot says it encrypts data in transit and at rest and supports SAML single sign-on, multifactor authentication, and LDAP for self-managed customers. It lists ISO 27001 and SOC 2 Type II certifications. Pricing is on request, with a 30-day trial. The trial costs nothing, allows up to five team members, and deletes data and assets 30 days after expiration unless the user contacts Sales.

Paperspace Gradient is a machine-learning platform for developing and operating models. It combines managed compute with experiment tracking, a model registry, pipeline orchestration, model serving and data versioning. Gradient is available on Linux, macOS, Windows and the web. Free plans for individual users and teams include 5 GB of storage; no hourly or maximum monthly price is shown for those plans. Paid plans are billed hourly up to a maximum monthly price. Pro — User costs $8 a month and includes 15 GB of storage, while Growth — User costs $39 a month with 50 GB. Team plans include Pro — Team at $12 a month with 15 GB of storage and Growth — Team at $39 a month with 50 GB. Those listed paid prices are maximum monthly prices, not a statement of a fixed hourly charge. The combination of compute and tools for tracking data, organizing pipelines and serving models covers several stages of machine-learning work.