A comprehensive suite for securely building, training, and deploying production-quality generative AI applications and LLMs, fully integrated within the Databricks Data Intelligence Platform using your own private data.
Databricks Mosaic AI provides an integrated tooling suite for enterprises to build and manage generative AI applications on the Databricks platform. It primarily serves data scientists, ML engineers, and developers needing to create custom AI models and RAG systems using their own private data. The platform's unique value lies in unifying data management, model development, deployment, and governance under a single security model via Unity Catalog. This approach simplifies the MLOps lifecycle by avoiding disparate tools and enables organizations to maintain full control over their AI models. Mosaic AI abstracts infrastructure complexities while providing robust tools for fine-tuning, serving, and monitoring models at scale.
Data Scientists, Machine Learning Engineers, Data Engineers, and AI Developers working in enterprise environments who need to build, train, deploy, and govern custom generative AI models and applications.
Based on 0 reviews
2013
San Francisco, USA
Standard
For individuals and small teams. Includes core Databricks platform features, with usage charged per Databricks Unit (DBU) based on compute type.
Pay-as-you-go
Premium
For enterprises needing unified governance. Includes all Standard features plus Unity Catalog, role-based access control, and other collaboration tools.
Pay-as-you-go
Enterprise
For regulated industries needing maximum security. Includes all Premium features plus enhanced compliance controls, audit capabilities, and dedicated support options.
Pay-as-you-go
Choose this fully managed ML platform for its deep integration with the AWS ecosystem if your entire workload is already on AWS.
A strong choice if you are heavily invested in the Google Cloud ecosystem and want native access to Google's proprietary foundation models like Gemini.
A compelling alternative if your data already resides entirely within Snowflake and you want to keep AI compute and data in the same platform to minimize data movement.
Opt for Hugging Face if your primary need is collaborating around, hosting, and deploying open-source models, rather than needing a full data-to-AI platform.
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