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Now accepting Q3 2025 engagements. Limited spots available for enterprise AI deployments.
Reserve your spotYour Private Enterprise Intelligence Layer
Databricks Mosaic AI gives enterprises the infrastructure to train, deploy, and govern private language models at scale. We build the complete AI system — from data pipelines and fine-tuning to RAG, model serving, and Unity Catalog governance.
Build Your Enterprise LLMFine-tune Llama 3.1, Mistral, or other open-source models on your proprietary data — with full reproducibility via MLflow and Unity Catalog lineage.
Databricks Vector Search creates Delta-synced vector indices for real-time retrieval. Your model retrieves fresh, relevant context at inference time.
Row-level security, column masking, and attribute-based access control ensure your LLM respects data boundaries across all queries and agents.
Every fine-tuning run is a tracked MLflow experiment. Compare model versions, reproduce training, and safely roll back production models.
We architect multi-model pipelines: router → specialist → evaluator chains that handle complex enterprise reasoning beyond single-model capability.
Automated evaluation harnesses measure faithfulness, relevance, and safety before any model touches production. No hallucinations reaching your users.
Mosaic AI is Databricks' end-to-end platform for building and deploying enterprise AI — including model fine-tuning, vector search for RAG, model serving, MLflow for experiment tracking, and Unity Catalog for governance. It enables enterprises to build private LLMs without sending data to external providers.
A Compound AI System chains multiple models and tools together: a router model directs queries to specialist models, retrieval systems fetch context, evaluators check output quality, and orchestrators handle multi-step reasoning. This approach handles complex enterprise use cases that single models cannot.