Databricks

Databricks showcases Agent Bricks, a platform for building and optimizing AI agents directly on user data to enhance automation and decision-making.

Databricks Showcases Agent Bricks for AI Agent Development

Databricks is highlighting its Agent Bricks product, a platform designed to help users build and optimize AI agents directly on their data. This offering underscores Databricks' commitment to providing comprehensive tools for AI development, enabling businesses to leverage their data assets more effectively for intelligent automation and decision-making.

Databricks announced the public preview of a new embedding model for agentic workflows, aiming to enhance AI agent performance and efficiency.

Databricks Introduces SOTA Embedding Model for Agentic Workflows

On March 17, 2026, Databricks announced the public preview of a State-of-the-Art (SOTA) embedding model specifically designed for agentic workflows. This new model aims to significantly enhance the performance and efficiency of AI agents by improving their ability to understand and process complex information. The preview allows users to test and provide feedback on the model's capabilities.

Databricks announced Agent Bricks and Databricks Apps to enable shipping production-ready enterprise AI agents to business users.

Databricks Enhances AI Agent Development with Agent Bricks

Databricks announced on March 16, 2026, the capability to ship quality enterprise AI agents to business users with Agent Bricks and Databricks Apps. This feature empowers organizations to develop and deploy sophisticated AI agents efficiently, ensuring they are production-ready for business applications. It aims to bridge the gap between AI development and practical business deployment.

Databricks enhances Delta Sharing with Attribute-Based Access Control (ABAC) support, enabling more granular security and simplified data sharing for organizations.

Databricks Enhances Delta Sharing with ABAC Support

Databricks announced on March 16, 2026, that Delta Sharing now supports Attribute-Based Access Control (ABAC). This enhancement allows for more granular and flexible data access management for both providers and recipients, improving security and simplifying data sharing across organizations and with external partners.

This is a commentary on the semiconductor industry, not a concrete new development from a specific company.

Databricks Launches Lakebase Serverless Postgres Database for AI

Databricks has introduced Lakebase, a new serverless Postgres database specifically designed for the AI era. This product aims to simplify data management and accelerate AI development by providing a purpose-built solution for modern data needs. It allows organizations to build and optimize agents directly on their data, streamlining workflows and enhancing AI capabilities.

This article provides a general overview of the semiconductor industry's trends and outlook, without reporting on a specific new development or concrete event.

Serverless Workspaces in Azure Databricks Now Generally Available

Databricks announced on March 13, 2026, that Serverless Workspaces in Azure Databricks are now Generally Available (GA). This milestone signifies that the serverless offering is production-ready, providing customers with simplified management and enhanced scalability for their Databricks environments on Azure. The GA status allows broader adoption and utilization of these advanced features.

This article is a commentary on AI regulation and industry impact, not a report of a concrete new development.

Databricks Launches Genie Code: Bringing Agentic Engineering to Data Work

Databricks launched Genie Code, an autonomous AI agent designed to revolutionize data engineering, data science, and analytics operations by improving the success rate of coding agents.

This is not a concrete new development and therefore not eligible for a signal.

Databricks acquires Quotient AI to power AI agent evaluations

Databricks acquired Quotient AI, a company specializing in AI agent evaluation and reinforcement learning, to enhance the reliability of AI agents in production environments.