Knowledge catalogue
This Databricks blog post discusses how natural language processing can accelerate clinical data pipeline development, reducing implementation time from months to minutes. It covers techniques for ext
Databricks discusses how leading technology companies are using Lakebase to eliminate 'builder's tax'—the overhead and complexity costs associated with building and maintaining data infrastructure. Th
LangGuard's agentic workflow governance engine represents one of the first production deployments of Lakebase, Databricks' platform for managing AI agents. The deployment demonstrates how organization
Tomorrow we go live with @Replit CTO @lhchavez to nerd out on how they approach security at the platform and individual project level. 🔐 If you're a professional vibe coder focused on building softwar
This Databricks article examines whether Large Language Model agents can effectively optimize SQL join order, a critical query optimization problem in database systems. The analysis likely evaluates L
This Databricks blog post explains how to use Genie and Agent Bricks to streamline and automate document activation workflows. It likely covers how these tools can help organizations process, manage,
This guide covers the fundamentals and best practices for developing AI-powered applications, likely including key stages from ideation through deployment, technology stack considerations, and integra
This guide from Databricks covers practical techniques and best practices for fine-tuning large language models, including methodologies for adapting pre-trained LLMs to specific tasks and domains. It
Databricks' Unity AI Gateway provides governance and control mechanisms for managing the proliferation of coding agents across enterprises, addressing challenges of oversight, security, and standardiz
pgvector is an open-source PostgreSQL extension that enables efficient storage and similarity search of vector embeddings within a relational database. It allows developers to build vector search capa
AI agents struggle to effectively process and extract information from complex enterprise documents due to limitations in context windows, reasoning capabilities, and handling of unstructured data for
Databricks' AI Gateway provides a centralized governance and control layer designed to manage agentic AI systems, enabling organizations to enforce policies, monitor usage, and maintain oversight acro
The post explains how a quick, one‑hour audit of AI agent usage revealed $1 million per year in avoidable spend. By reviewing deployment patterns and trimming unnecessary calls, the team reallocated r
**Managing AI Coding Costs at Scale** This article addresses the economic challenges of deploying AI coding tools across large teams or organizations. It explores strategies for tracking resource usag
AIOps (Artificial Intelligence for IT Operations) merges AI and machine learning with comprehensive observability to automate event correlation, root‑cause analysis, anomaly detection, incident respon
This article examines the infrastructure approaches and strategies that leading AI companies use to support their AI development and deployment at scale. It likely covers key components such as data p
Decision Execution Platforms represent an evolution beyond traditional dashboards by enabling organizations to not only visualize data insights but also automatically trigger and execute business deci
Serverless PostgreSQL is a managed database service that abstracts away infrastructure management, allowing users to run PostgreSQL databases without provisioning or managing servers. This approach en
A serverless database for AI applications should prioritize scalability, low latency, and seamless integration with machine learning workflows, eliminating the need for infrastructure management. Key
Vector search is a retrieval method that converts unstructured data (text, images, audio) into numerical vector representations and finds similar items by comparing vectors in high-dimensional space,
Retrieval Augmented Generation (RAG) is a technique that combines information retrieval with generative AI to enhance model outputs by fetching relevant external documents or data before generating re
This article explores the applications and impact of artificial intelligence on national security and defense operations, examining how AI technologies are transforming military capabilities, threat d
This guide provides best practices and architectural principles for designing effective data warehouses, covering topics such as schema design, performance optimization, and scalability considerations
This article discusses how healthcare organizations can move beyond basic X12 EDI parsing to implement more comprehensive revenue cycle management workflows using data analytics platforms. It likely a
This article argues that AI projects fail to scale when organizations treat them as one-off innovations rather than integrating them into standard business operations and processes. According to Datab
This resource discusses how healthcare organizations can build learning health systems to succeed under CMS TEAM (Transforming Episode Accountability Models) and advance value-based care (VBC) initiat
This article discusses how organizations can leverage observability data—including metrics, logs, and traces—to proactively identify and prevent incidents before they impact systems and users. It like
This guide provides Chief Financial Officers with strategies for financial management and performance optimization in value-based care models, which shift healthcare reimbursement from volume-based to
Unity AI Gateway introduces new enterprise features including service policies, guardrails, observability tools, and cost controls designed to manage and monitor AI agents and Model Context Protocols
Chief Marketing Officers are increasingly prioritizing AI security infrastructure due to growing risks around data protection, model integrity, and regulatory compliance in AI systems. Organizations m
AI agents are automating traditional manual processes in electric grid operations, improving efficiency and response times for grid management tasks. These autonomous systems leverage machine learning
Clinical operations intelligence in healthcare can be effectively managed and analyzed using a lakehouse architecture, which combines the benefits of data lakes and data warehouses. This approach enab
Data quality is a foundational component of effective AI strategy, as high-quality training and operational data directly impacts model performance, reliability, and business outcomes. The article lik
Claroty developed an AI-powered library that serves as a translation tool for industrial control system (CPS) protocols and communications, helping security teams understand and analyze diverse indust
This article explores how healthcare organizations can uncover insights about operating room efficiency and utilization rates by analyzing scheduling data, likely demonstrating techniques for identify
Mean time to detect (MTTD) is fundamentally constrained by data access capabilities, as organizations cannot identify security incidents or anomalies faster than they can query and analyze their data.
Digital native companies often face significant challenges in scaling AI systems beyond initial proof-of-concept stages, despite their technical advantages and cloud infrastructure. The article examin
The Federal Data Paradox examines how U.S. federal agencies accumulate vast amounts of data but face significant barriers to accessing and utilizing it effectively. The article likely discusses challe
This article likely discusses predictive maintenance and failure detection in industrial turbines, examining how data analytics and machine learning can identify warning signs before catastrophic fail
Overall Equipment Effectiveness (OEE) dashboards often present misleading metrics due to data quality issues, incomplete visibility into production factors, or misalignment between how OEE is calculat
Financial services institutions (FSIs) traditionally rely on fragmented, siloed systems — such as portfolio platforms, reconciliation software, and ERP tools — that prevent client-facing, operation...
Lakebase provides database‐branching functionality that lets coding agents work on isolated data copies during the agentic software development life cycle (SDLC). Each branch gives an agent its own sa
**Summary:** The article titled *“How to scale agentic applications without creating AI sprawl”* is currently incomplete, containing only placeholder text (“Buil Buil Buil”). No substantive guidance o
The article introduces the Unity Gateway Command Line Interface (CLI) as a tool for deploying and managing coding agents at large scale. It outlines how users can automate agent deployment, monitor pe
**Genie One MCP: Give any AI Agent the Right Business Context** The guide introduces Genie One MCP as a framework for embedding relevant business context in artificial intelligence agents, enabling th
**Summary** The documentation titled *“Unity Catalog Pages: a governed home for your business knowledge in Genie Ontology”* describes Unity Catalog Pages as a central, governed repository for storing
Today, we are excited to announce enhancements to the borderless Lakehouse, our answer to how data engineers, data scientists, and increasingly, AI agents, can query governed data directly where it li
An embedded AI/BI dashboard can be securely shared with multiple viewers while ensuring that each viewer can see only their authorized rows. This protection is achieved through group‑based row‑level s
This research details an agentic framework that automatically generates custom GPU kernels and rigorously validates them. By integrating automated synthesis and thorough performance testing, the syste
Fast, fault‑tolerant PyTorch training on AI Runtime is designed for GPU scale environments where failures occur routinely. By employing intelligent data loading and robust checkpointing strategies, th
**Vertical Advantage: Transforming Industries with Lakebase and Agentic AI** The article details how Lakebase’s unified data‑lake platform, coupled with Agentic AI’s autonomous decision‑making agents,
**Agentic Workflows** enable automated systems to execute complex tasks by orchestrating multiple agents that interact with each other and external services. They delegate subtasks, monitor progress,
Agentic AI empowers telecom finance teams to preserve margins by rapidly detecting and preventing revenue leakage across billing, provisioning, and cost‑allocation processes. The technology automates
This guide explains how AI customer service operates, focusing on the use of AI agents and sentiment analysis to interpret and respond to customer interactions. It provides practical instructions for
Genie Code surpasses three leading coding agents on more than 400 real‑world coding tasks, achieving the highest accuracy among the compared solutions. It also reduces cost by roughly 50 % per task an
Retail Finance teams are increasingly deploying agentic AI to safeguard omni‑channel margins. These systems automatically monitor sales performance, forecast demand, and adjust pricing or inventory co
The article discusses the disparity between healthcare organizations' capabilities in leveraging data and AI for ambulatory care versus inpatient settings, highlighting how ambulatory providers often
This guide provides criteria and best practices for assessing enterprise analytics platforms, likely covering key evaluation factors such as scalability, performance, integration capabilities, ease of
Imperial College London is leveraging a modern data platform to accelerate dementia research by enabling faster analysis of large-scale datasets and improved collaboration among researchers. The platf
DataOps is a set of practices and tools that apply DevOps principles to data engineering, focusing on automating data pipelines, improving data quality, and enabling faster iteration cycles. The strat