Egeria Resource Explorer: Effective Exploration and the Survey Funnel – Part 1: Active Scouting Beyond the Catalog Perimeter
Originally posted here by Dan Wolfson, Founder, Pragmatic Data Research Ltd. and member of the LF AI & Data Context Intelligence Work Group Enterprise data catalogs are rarely built in a vacuum. Most are created with deliberate purpose: to satisfy a regulatory mandate, support a critical data migration, power an… Read more.
Egeria 6.0: Doing More With Half the Footprint
By Mandy Chessell, Egeria Project Leader, Pragmatic Data Research (PDR) Ltd Part 1 of a four-part series on recent work in the Egeria project, an LF AI & Data project for open metadata and governance. Open metadata platforms have a reputation problem: they tend to get bigger, not smaller, as they mature.… Read more.
Putting RGAF to Work: Build and audit responsible AI with open source
As generative artificial intelligence shifts from experimental play to enterprise-grade deployment, the conversation has moved from what constitutes responsible AI to how we actually achieve it. This shift is being spearheaded by the LF AI & Data, an umbrella foundation under the Linux Foundation that supports and sustains open source… Read more.
Budgets as code with Flyte, OpenLineage, and Marquez
Authors: Ashok Prakash, Staff Engineer at Apple Isan Sahoo, Principal Engineer at Oracle In the world of multi-tenant GPU clusters, managing spiraling cloud costs is a persistent challenge. Traditional retrospective chargeback often fails to prevent budget violations, leaving teams struggling to control spend after the fact. To solve this, we're… Read more.
Demo to Production: An Open Source Architecture for Reliable AI Agents
Author: Ashok Prakash, Senior Principal Engineer at Oracle AI Summary The promise of AI agents is simple: automation. The reality, as many production teams have learned, is a story of unpredictable failures, security holes, and runaway costs. Moving an agent from a controlled demo to a reliable, cloud-native service is… Read more.
Turning Climate Risk Into Actionable City Plans with Trustworthy AI Agents
How do you turn climate risk data into clear next steps a city can actually act on? Wavestone set out to answer that at the IBM Watson TechXChange hackathon. They built Hive.ai, an open source platform that uses BeeAI — an LF AI & Data project — to generate city-specific… Read more.
