Systems | Development | Analytics | API | Testing

The Fastest Route to AI-Ready Data - Analyst Studio Demo

Most data teams spend 80% of their time prepping data instead of driving strategy. In the agentic era, that's not just slow—it's a blocker. In this session, Anjali Kumari demonstrates how to go from raw, siloed data to trusted insights in under 10 minutes. This segment shows you how to empower your team with AI-ready data without the pipeline sprawl or surprise cloud bills. In this video, you’ll see a live walkthrough of how to.

Confluent Intelligence expands real-time business data to enterprise AI

Support for the Agent2Agent protocol helps connect AI agents anywhere in real time so they can collaborate at enterprise scale. Multivariate Anomaly Detection takes anomaly detection to the next level, stopping problems before they start.

Al boosts developer speed, so why does it slow testers down?

AI slows testers down when it’s added without a tester-first experience. Testers naturally question coverage and intent, so Katalon designs AI around real testing workflows to boost productivity instead of creating friction. — Alex Martins, VP of Strategy at Katalon Follow Katalon for more insights in our series!

Reflect vision-based AI demo | Create one test for multiple platforms

Create a single mobile test that runs reliably on both iOS and Android - without building separate tests per platform or relying on brittle, platform-specific locators. In this high-level demo, we use SmartBear Reflect’s vision-based AI to record a typical workflow in a sample coffee app, where each step is backed by visual context and intent. Then we run the same test across a mix of Apple and Android devices, including an iPhone, to show how Reflect adapts to the environment at runtime and helps reduce flakiness and false positives.

Enterprise AI Infrastructure Security Series - 1) Intro

Welcome to Part One in this series covering AI Enterprise Security with ClearML. How do you secure an AI platform, ensure compliance, and still give your teams the access they need to move fast? ClearML builds security, compliance, and cost control into every layer of the platform — the guardrails are invisible to your AI/ML teams, but not absent. In this video, I introduce the six layers of the ClearML Enterprise security stack: Identity & Access, Configuration Governance, Automation Security, Compute & Data Access Governance, Model Serving, and Audit & Compliance.

AI Agents & Enterprise AI Governance: The WPP Blueprint for Brand Brains | The Data Chief

AI agents are transforming enterprise AI, governance frameworks, and business decision-making. In this episode, we explore agentic AI systems, decision intelligence, and brand brains — AI systems designed to produce brand-specific, production-grade content that differentiates businesses. Join @wpp's Daniel Hulme & podcast host Cindi Howson for this insightful discussion. If you're a Chief Data Officer, Chief AI Officer, or enterprise leader, this conversation explains how to deploy AI agents safely, govern them effectively, and automate complex decisions while augmenting human creativity.

How AI Augments Human Creativity at Scale: The WPP Blueprint

Learn how AI agents are reshaping enterprise decision-making, AI governance, and brand creativity. Daniel Hulme, Chief AI Officer at WPP & CEO of Satalia/Conscium, explains how AI agents, decision intelligence, and his concept of “brand brains” (AI systems designed to create brand-specific, production-grade content) are changing how organizations operate. He shares why companies don’t have data problems but decision-making problems, and how AI can augment human creativity at scale.

Maintaining compliance when adopting AI in regulated industries

Key Takeaway: Organizations in regulated industries can adopt AI without compromising compliance. Automated testing enables continuous validation of AI-enabled systems while maintaining the predictability, documentation, and audit-readiness that regulators require. In compliance-first industries, such as banking, healthcare, or telecommunications, AI adoption is rarely a simple technology decision. You are often caught between two competing pressures.