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As AI-powered agents begin to play a more active role in quality engineering, regulated industries especially in BFSI, healthcare, and government face a critical question: How do you scale agentic QA without losing control, visibility, or auditability? This blog explores how to make agent-augmented QA compliant, explainable, and trustworthy, not just in spirit, but in process, tooling, and evidence. We’re not talking about testing AI systems.

September brings a powerful wave of innovation across the Katalon Platform, led by the new StudioAssist Agent Mode, AI-driven insights in TestOps, and smarter, more resilient executions in TestCloud. This month’s updates redefine productivity for modern QA teams, helping testers code faster, debug smarter, and execute at scale with confidence.

By now, most teams experimenting with AI-augmented testing have started with narrow, tactical use cases: writing test cases faster, summarizing logs, or tagging defects. These are useful — and they build trust in the tech. But true value emerges when you stop thinking of agents as plug-ins, and start thinking of them as a virtual QA team, a set of coordinated roles that evolve how testing is done, how it’s governed, and how it delivers value across the delivery lifecycle.

The new StudioAssist Agent Mode turns your AI assistant in Katalon Studio into a connected, context-aware testing partner. It now supports MCP Servers, HTTP-based services that let the agent fetch real-time information and perform actions directly inside your project. Katalon ships with two built-in MCP Servers: You can also add your own HTTP-based MCP Servers to extend StudioAssist’s reach. (Note: authentication support is coming soon.)

We are pleased to announce the launch of the QualityKiosk–Katalon Joint Innovation Lab on October 15th, marking a significant milestone in our shared mission to advance the future of test automation and quality engineering. This strategic collaboration between QualityKiosk Technologies and Katalon reflects our commitment to empowering enterprises with prebuilt, next-generation testing and automation solutions designed to enhance agility, efficiency, and innovation.

Traditional test metrics like automation %, pass/fail rates, and defect counts don’t reflect the impact of introducing agents into the QA process. This blog explores a new class of KPIs designed to measure how well your virtual test team is performing including Agent Assist Rate, Human Override Rate, Scenario Coverage Delta, and Review Time Saved.

As organizations explore more advanced uses of agentic testing, a compelling vision emerges: a modular virtual test team composed of AI agents, each playing a focused role like Test Architect, Test Designer, Executor, and Summary Agent. While still early in real-world adoption, this model offers a way to coordinate intelligence at scale, with humans guiding the system and autonomy granted based on task risk and maturity.

In August, Katalon delivers a blend of AI intelligence and enterprise readiness. From TestCloud’s flexible configurations and TestOps’ new AI-powered root cause analysis, these updates enable teams to debug smarter, share insights more widely, and maintain quality at scale.

Agentic testing isn’t just about faster execution - it’s about uncovering what’s missing from your test suite. This blog explores a forward-looking model where AI agents help identify gaps in traditional, deterministic systems through techniques like scenario delta detection, data condition surfacing, edge path exploration, and test case obsolescence tracking.

Today, Gartner released the first-ever Magic Quadrant for AI-augmented Software testing, and I’m very excited to share that Katalon has been named a Visionary!