Releases

Databricks introduced Agent Bricks, which generates task-specific data and benchmarks to optimize agents for enterprise use cases.

Databricks introduced Lakebase, a serverless Postgres category designed for operational data and AI agents.

Databricks agreed to acquire serverless Postgres company Neon to create Lakebase for AI applications and agents.

Databricks and Google Cloud expanded joint go-to-market and product integrations for Gemini models and enterprise AI.

Databricks and Anthropic established a partnership to offer Claude models natively through the Databricks Data Intelligence Platform.

Databricks enhanced agent evaluation with customizable LLM judges, human review workflows and OpenTelemetry-based MLflow tracing.

Databricks released APIs for embedding Genie conversational analytics into applications, Teams, Slack and SharePoint.

Mosaic AI Gateway added support for OpenAI-compatible external and custom model providers with centralized permissions, routing and monitoring.

Databricks completed $10 billion in equity financing and arranged $5.25 billion in debt facilities at a $62 billion equity valuation.

Databricks announced a Series J targeting $10 billion, with $8.6 billion completed at announcement, valuing the company at $62 billion.

Databricks introduced code-first Custom Agents for building, deploying and evaluating production agent systems using any LLM.

Mosaic AI Agent Framework and Agent Evaluation entered public preview with integrated deployment, evaluation, tracing and governance.

Databricks introduced Apps for building and deploying secure data and AI applications directly on the platform.

Databricks introduced AI/BI, pairing AI-assisted dashboards with Genie conversational analytics built on a compound AI system.

Databricks introduced MLflow Tracing for end-to-end observability and debugging of generative-AI applications and agents.

Databricks launched a framework for authoring, evaluating, deploying and monitoring production-quality compound AI systems.

Databricks agreed to acquire Tabular, founded by the creators of Apache Iceberg, to advance interoperability between Delta Lake and Iceberg.

Databricks optimized DBRX inference and made the model available through Mosaic AI Model Serving.

Databricks released DBRX, a 132-billion-total-parameter mixture-of-experts model with 36 billion active parameters under an open license.

Databricks acquired Einblick, whose natural-language notebook technology and team strengthened AI-native data exploration.

Databricks introduced a data intelligence engine that learns enterprise semantics and powers context-aware assistance and optimization.

Databricks acquired enterprise data replication company Arcion to make operational data available for analytics and AI.

Databricks introduced pay-per-token APIs and provisioned throughput for serving curated open foundation models.

Databricks raised more than $500 million in Series I financing at a $43 billion valuation.

Databricks completed its acquisition of MosaicML, adding foundation-model training, inference, research and open models to its AI platform.