Databricks Mosaic AI

Databricks Mosaic AI is an enterprise-grade platform designed to help organizations build, deploy, and govern generative AI applications using their own data. As companies race to implement large language models, they face critical challenges around data security, model accuracy, and production deployment. Mosaic AI addresses these by providing a unified platform where teams can prepare data, fine-tune foundation models, build retrieval-augmented generation (RAG) systems, and deploy AI applications while maintaining enterprise security and governance standards. The platform is built on Databricks' lakehouse architecture, allowing organizations to leverage their existing data infrastructure and ensure AI models are trained on accurate, up-to-date information.

How It Works

Teams start by connecting their data sources to the Databricks lakehouse, where data engineering and ML teams can collaborate on preparing high-quality training data. For building LLM applications, Mosaic AI provides tools to experiment with different foundation models, fine-tune them on your specific domain data, and create RAG systems that combine model capabilities with real-time data retrieval. The platform includes managed MLflow for experiment tracking, model versioning, and deployment orchestration. When ready for production, deploy models to auto-scaling endpoints with built-in monitoring for quality, latency, and cost. Mosaic AI also provides governance features for tracking data lineage, managing access controls, and ensuring compliance with regulatory requirements.

Core Features

• •Model Training and Fine-Tuning - Access to state-of-the-art foundation models with tools for efficient fine-tuning using your proprietary data to improve accuracy for domain-specific tasks
• •Vector Database - Managed vector search capabilities for building RAG applications that combine LLM reasoning with real-time information retrieval from your data
• •AI Playground - Interactive environment for comparing different models, testing prompts, and evaluating outputs before committing to a specific approach
• •Production Deployment - Deploy models to auto-scaling endpoints with built-in monitoring, A/B testing, and cost optimization features for reliable production AI
• •MLOps Integration - Unified MLflow platform for tracking experiments, managing model versions, and orchestrating complex ML workflows with data and AI pipelines
• •Governance and Security - Enterprise-grade access controls, data lineage tracking, and audit logs ensuring AI applications meet compliance and security requirements

Who This Is For

Perfect for enterprise data teams building custom LLM applications who need to leverage proprietary data while maintaining security and governance, ML engineers deploying generative AI to production who need reliable infrastructure and monitoring, and organizations implementing RAG systems to reduce hallucinations and improve accuracy. Mosaic AI is also valuable for financial services and healthcare organizations with strict compliance requirements, data science teams migrating from experimental to production AI deployments, and companies consolidating their data and AI infrastructure on a single unified platform.