Introducing ai_decide: make fast decisions on your governed data
Databricks launches ai_decide, a new AI function for fast, low-cost decisions on governed data, replacing LLMs for structured tasks like classification and routing.
SOURCE ARCHIVE · ORIGINAL LINKS INCLUDED
Databricks Newsroom coverage · page 2
Every ClipRaptor briefing sourced from Databricks Newsroom, with a direct link to the original publisher page. Page 2 of 5: briefings 31-60, published Aug 26, 2026 to Sep 30, 2026.
How to scale agentic applications without creating AI sprawl
Enterprises face AI sprawl as agentic applications multiply, requiring shared infrastructure for choice, context, and control to scale without duplicating integrations or governance.
How Databricks rolls out frontier models to 14,000 employees on Day 1
Databricks deployed three frontier AI models to 14,000 employees on launch day, using internal tools to evaluate performance and cost within three days.
Lakebase Search: State-of-the-art full text and vector search for Postgres
Databricks introduces lakebase_vector and lakebase_text extensions for Lakebase Postgres, enabling state-of-the-art full-text and vector search directly within the database, eliminating the need for separate search...
Manufacturing data and AI: Connecting the product value chain
Manufacturers face fragmented data silos across production, supply, and quality systems, complicating defect investigations and cross-stage queries. A modern Data and AI Platform aims to unify these systems without...
Running open-Jev in SQL on Databricks
Databricks enables running open-weight decision models like SemIf-OpenJev directly on governed data via SQL and serverless GPUs, simplifying enterprise applications.
Deploy and manage coding agents at scale with the Unity Gateway CLI
Databricks launches Unity Gateway CLI to let teams adopt the best AI coding models while centrally managing costs, security, and policies across thousands of developers.
Genie One MCP: Give any AI Agent the Right Business Context
Databricks introduces Genie One MCP to provide governed business context to any MCP-compatible AI assistant, enabling reliable, permission-aware answers across existing tools.
The Genie One MCP is now Generally Available
Databricks releases the Genie One MCP server for general availability, enabling AI agents to access unified, governed business context from Genie One via a standardized interface.
Unity Catalog Pages: a governed home for your business knowledge in Genie Ontology
Databricks introduces Unity Catalog Pages to centralize and govern business definitions for AI agents, ensuring consistent and accurate interpretations of key terms across enterprises.
Enabling secure, productive work on personal devices
Databricks outlines a four-layer mobile security framework to protect corporate data on personal devices without compromising user privacy or device control.
Database Branching: A Developer's Guide to Git-Style Workflows
Database branching introduces Git-style isolated environments for databases, enabling safer, faster development and testing without duplicating full datasets.
Database for AI Agents: 5 Evaluation Criteria
Databricks outlines five essential criteria for selecting databases to support AI agents in production, addressing memory, scaling, retrieval, consistency, and unified access.
The Web Search Your Agent Inherited Isn't Good Enough
Databricks introduces Omnigent to unify fragmented agent workflows, replacing three separate tool rebuilds with a single definition while integrating Nimble’s specialized web search to improve accuracy and reduce costs.
Modernizing the Trade Lifecycle With Governed Data and AI
Capital-markets firms are modernizing trade workflows by integrating AI with governed data across research, trading, risk, operations, and compliance to move beyond pilot projects and improve real-time decision-making.
Data Ontology defined: The context layer your AI agents are missing
AI agents struggle with ambiguous enterprise data because they lack human context, prompting a renewed focus on data ontologies to provide trustworthy business definitions and relationships.
How energy teams turn theft detection into governed action with Genie and AI business processes
Energy teams can now turn machine learning theft detection into governed, real-time business actions using Databricks’ lakehouse platform, addressing financial and safety risks from tampered meters.
What is AI analytics? Why it only works on governed data
AI analytics relies on governed data to deliver trustworthy insights, shifting from dashboards to automated, conversational investigations that reduce manual analytical work.
How Databricks’ marketers use data 3x more with Genie, an AI analytics assistant
Databricks’ marketing team tripled data use in decisions by deploying Genie’s conversational analytics assistant, Marge, grounded in a governed lakehouse and tailored to business language.
Health Plans: Your BI Tells You MLR Moved. Can Your AI Tell You Why?
Health plans struggle to explain why financial metrics like MLR shift. AI can now uncover root causes by integrating payer-specific data and business context, enabling faster, more informed decisions.
Improving Lakebase Postgres compute cache
Databricks enhances Lakebase Postgres compute cache by increasing shared buffers to 75% of DRAM on fixed-size computes, improving performance and reducing memory overhead.
Five AI Questions We're Hearing from Financial Services Leaders
Financial services leaders at Sibos 2026 shift focus from AI feasibility to trustworthy governance, highlighting gaps in compliance and operational integration across liquidity, risk, and client engagement.
Beyond embedding: How to secure AI/BI Dashboards for every viewer
Databricks introduces a design pattern to enforce row-level security for embedded AI/BI dashboards, ensuring viewers see only authorized data slices without duplicating dashboards or filters.
Introducing Consort: Test-driven development on a branching database
Databricks introduces Consort, an open-source framework enabling test-driven development on branching databases, shifting schema testing left in the development cycle.
Building for the AI Era: Lakebase, Streaming, and Lakehouse Innovations at VLDB 2026
Databricks will present innovations at VLDB 2026, including Lakebase, streaming improvements, and automated optimizations, addressing AI agent workload demands and real-time analytics.
Enhancing Agent Retrieval with Structured Chart Extraction
Databricks introduces structured chart extraction in ai_parse_document to improve retrieval and answer accuracy for chart-based questions in enterprise documents, outperforming larger multimodal models while using...
What QSR reports miss about the decisions matter the most
Databricks and Lovelytics launched a QSR Executive Performance Control Tower to link performance metrics to root causes and financial impact, enabling faster, joint decision-making between corporate and franchisees.
Vertical Advantage: Transforming Industries with Lakebase and Agentic AI
Databricks partners have launched industry-specific solutions built on Lakebase, a unified transactional and analytical platform, to address real-time operational needs across sectors such as finance, healthcare, and...
Object Storage + WAL: Lakebase Postgres for the agentic era
Databricks introduces Lakebase Postgres, a transaction-centric Postgres deployment that uses object storage and the write-ahead log (WAL) to make agent workloads more efficient and cost-effective.
Introducing Governance Hub: Intelligent, account-level governance over your Databricks estate
Databricks introduces Governance Hub, a centralized account-level tool for monitoring data health, AI usage, and costs across multiple cloud platforms, now available in beta.