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AI Platform

Databricks Mosaic AI

Databricks AI platform for building, fine-tuning, deploying, and governing AI agents and ML models within the data lakehouse ecosystem.

Producer:DatabricksManaged Cloud · Serverless · On-PremisesSOC 2 Type II · SOC 1 Type II · SOC 3Released:Jul 1, 2023
Data residencySovereign cloud
Databricks Mosaic AI
Supported models
3SLM/LLM
SDK / Languages
4python, scala, r
Uptime SLA
99.9%
Robotics-Ready
✓

Description

Databricks Mosaic AI is an integrated AI/ML platform that is part of the Databricks Data Intelligence Platform, built on a data lakehouse architecture. The platform covers the full model lifecycle: data preparation, training, fine-tuning, deployment, and monitoring. Mosaic AI was created following Databricks acquisition of MosaicML in June 2023 for approximately $1.3 billion, incorporating its LLM training and serving technology.

Key Components

The platform consists of: Agent Bricks for building AI agents optimized on enterprise data; Unity AI Gateway as a central governance hub for LLMs and MCPs; Vector Search, a native vector database with real-time sync; Agent Framework and Evaluation for building and assessing production agents; Model Serving for deploying GenAI and classical ML models; Mosaic AI Training for fine-tuning and pre-training LLMs; Managed MLflow as the MLOps backbone; and Databricks Notebooks for collaborative data science.

Lakehouse Integration

The key advantage of Mosaic AI is its deep integration with the data layer: Delta Lake, Unity Catalog (data governance), Databricks SQL, and Apache Spark. Models have native access to structured and unstructured data stored in the same ecosystem, eliminating data movement and simplifying governance. The platform runs on AWS, Azure, and Google Cloud.

MLOps LifecycleMLOps LifecycleFull model lifecycle: registry, feature store, prompt management, monitoring and human-in-the-loop.

15/17 supported

Model Registry

Versioning — model artifact versioning
Approval workflows — approval workflow before production
Immutable artifacts — immutability of stored versions
Lineage tracking — tracking data and model relationships
4 / 4 supported · none unsupported

Feature Store

Online serving — real-time feature serving
Offline storage — feature storage for training
Streaming ingestion — streaming ingestion (Kafka, Flink)
3 / 3 supported · none unsupported

Prompt Management

Prompt registry — central prompt repository
Versioning — prompt versioning and history
Testing frameworks — A/B testing and prompt evaluation
3 / 3 supported · none unsupported

Monitoring

Data drift detection — input data drift detection
Concept drift detection — concept drift detection
Hallucination monitoring — LLM hallucination monitoring
Bias evaluation tools — bias evaluation tooling
4 / 4 supported · none unsupported

Human-in-the-Loop

Labeling services — data labeling tools
RLHF workflows — reinforcement learning from human feedback
Manual override — manual override of model decisions
1 / 3 supported · 2 unsupported hidden

Data & KnowledgeData & Knowledge ManagementData connectors, vector database integration, native vector search and data management (PII, provenance, synthetic data).

ApplicationsAI ApplicationsDomains and use cases this platform is best suited for — from RAG and fine-tuning to scientific research.

12

SecurityEnterprise SecurityCertifications, access controls and data-protection features essential for corporate deployments and cloud privacy compliance.

Developer EcosystemDeveloper EcosystemDeveloper resources: available SDKs, supported programming languages, and infrastructure features and model-deployment methods.

SDK Languages
PyPythonscscalarrsqsql
API Type
REST
Community & resources
Templates library
Quickstarts
API Reference
Tutorials
$

Pricing & Business ModelPricing & Business ModelBilling models (usage-based, provisioned throughput), resource limits and SLA parameters (uptime, support tiers).

Pricing models

Usage-based
dbu based

Resource quotas

Per project
Per user
Cost alerting

SLA & Support

99.9%uptime SLA
StandardenhancedEnterprise 24/7

Supported AI Models

3

SourcesDocumentation VaultCentralized hub of links to official sources, technical guides, repositories and release notes.

Data verified: May 4, 2026