Kafka Copy Paste (KCP): How to Migrate to Confluent Cloud in Days, Not Weeks

While Apache Kafka is incredibly powerful, self-managing brokers, upgrades, capacity, security, and incidents can quickly distract teams from what matters most: building real-time applications and delivering business value. Confluent Cloud can remove that operational burden, yet migration can still be seen as risky and tedious.

New in Confluent Intelligence: A2A, Multivariate Anomaly Detection, Vector Search for Cosmos DB, Amazon S3 Vectors, and More

As AI models are increasingly commoditized, the value driver for enterprises is no longer “Which large language model (LLM) are we using?” but “How can we use our data for reliable, real-time AI decisioning?” Agentic AI systems—where agents plan, decide, and act autonomously—are only as useful as the context they have. When that context is stale, fragmented, or locked away behind brittle point-to-point integrations, even the best models fail to deliver.

Simba Connect Demo: Simplify Workday Data Access With SQL

From 51 API Calls to 10 Lines of SQL: Accessing Workday Data With Simba Connect Accessing Workday data through raw APIs means dealing with pagination, rate limits, nested JSON parsing, authentication logic, and dozens of sequential API calls — just to build a simple HR dashboard.

#OnTheSpot: Connecting Structured Data with Live Web Search for Smarter PR

Public relations professionals spend hours pulling coverage reports, but our Director of Corporate Communications Russell Dougan does it in minutes In our latest, Russell shows how he uses ThoughtSpot Spotter to prep for his QBR. By connecting structured data with live web search, Spotter analyzes Q2 media performance and delivers a plan for which publications and podcasts to prioritize in Q3. This is what agentic analytics looks like for comms teams.

Models to Meaning: AI Value in Production w/ Open Source - MLOps Live #42 w/ QuantumBlack

In this session of MLOps Live, Joseph Perkins, Product Manager at Vizro by QuantumBlack, and Gilad Shaham, Director of Product Management, Iguazio (A McKinsey Company) discuss how modern AI teams are moving beyond heavy engineering to deliver production-ready, business-visible AI systems using open-source frameworks like MLRun and Vizro. In this session, you’ll learn how: The session includes a live demo of a gen AI application, showing how MLRun and Vizro work together to deliver both operational control and business visibility in production.

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.