Systems | Development | Analytics | API | Testing

Securing AI Interactions: Crossing the Hurdles of MCP Authorization

The rise of large language models (LLMs) and AI-powered applications brings incredible potential, but also poses significant security challenges. These applications have gotten much more useful with the emergence of agentic approaches and the ability to call out to different libraries, systems, and most importantly, to different APIs in order to take actions. They have moved from being a question answering resource to being able to do work, shop on your behalf, book travel, and update code.

Is Data Integration the Real Engine Behind Effective AI Agents? #aiagents

Jay Mishra, our Chief Product and Technology Officer, explains why quality data is the true driving force behind successful AI agents. He also shares how Astera AI Agent Builder seamlessly connects to both internal and external data sources, ensuring that your AI agents are data-driven and ready to deliver powerful results.

Why Data Teams Are Best-Positioned For Agentic AI Success With Data Integration and MCPs

Building AI agents is the first step, and it’s positive to see enterprises exploring this avenue. But it’s only the first step. For true enterprise value, these agents must seamlessly connect to your data ecosystem through robust integration, standardized protocols, and be guided by knowledgeable data teams. The need to give AI agents access to data and connect them to the necessary tools and functions has led to the creation of the Model Context Protocol (MCP).

MCPs, Agents and the Future of Software Testing with Angie Jones

In this LIVE episode of Test Case Scenario, host Jason Baum, along with co-hosts Marcus Merrell and Evelyn Coleman, engages in a compelling conversation with Angie Jones, Global Vice President of Developer Relations, Block, Inc. They delve into the transformative impact of agentic AI and Model Context Protocols (MCPs) on software development and testing.

EP 23 | From Poker Tables to Boardrooms: AI, Risk, and Business Communication with David Daneshgar

In high-stakes environments like professional poker and startup entrepreneurship, precision, timing, and strategy are everything. And nobody knows that better than David Daneshgar. In this episode of The AI Forecast, we’re joined by David Daneshgar, a World Series of Poker champion and now Co-founder and CEO of Whippy, a company using AI to transform how businesses communicate with their customers.

A Vision for the Future: Qlik's New Agentic AI Experience

The future of data and analytics will be nothing like the experience we're used to today. We are at the beginning of a transformation that will fundamentally reshape how businesses use data, make decisions, and create value. At the center of this revolution is Agentic AI. Agentic AI fundamentally changes the way we work with data – moving from passive, reactive AI systems to autonomous, goal-oriented agents capable of reasoning, planning, and executing complex tasks across diverse data landscapes.

What's New in ClearML v3.25: Vector Database support, Smarter Orchestration, and UI Enhancements

ClearML v3.25 introduces native support for vector databases within the Hyper-Datasets feature. This release enables users to store and search embeddings directly inside ClearML, opening the door to powerful custom RAG pipelines. In addition, v3.25 includes expanded orchestration metrics, new Application Gateway UI, and a range of UI upgrades to streamline day-to-day operations.