Systems | Development | Analytics | API | Testing

Test Smarter, Not Larger: How SLMs Are Outperforming Massive AI Models in QA Efficiency

For years, the tech world has been captivated by the sheer scale of Artificial Intelligence. Headlines trumpet models boasting trillions of parameters, hinting at a future where massive AI effortlessly solves our most complex challenges. Giants like GPT-4 and Gemini Ultra, with their vast architectures, have set the benchmark. Yet, in the specialized arena of software quality assurance, a fascinating counter-narrative is emerging: sometimes, smaller is indeed better.

The EU AI Act: Key Implications for Using Data in the Modern Enterprise

The EU AI Act is a new law changing how organisations develop and deploy AI-powered solutions worldwide. Complying with it is a chance for organisations to stand out and build trust with customers through responsible AI use — all while continuing to innovate. As predicted by McKinsey and others back in 2023, AI (specifically generative AI) has become a key part of daily business operations across many industries.

Introducing Asgardeo MCP Server

Today, we're excited to officially release the Asgardeo MCP Server, enabling developers to securely manage their Asgardeo organizations using natural language—right from their favorite code editors like VS Code, Claude Desktop, Cursor, Windsurf, and other MCP-compatible clients. Asgardeo already supports Login Flow AI and Branding AI, making it easier to build secure, customized login and registration experiences using plain language.

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).

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.

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.