Systems | Development | Analytics | API | Testing

That’s a wrap on API Summit 2025! At our eighth annual event, the brightest minds in the worlds of APIs and AI gathered in New York City to define the next chapter of digital innovation. We're entering an era where APIs are not just connecting services but connecting intelligence. APIs are the neural pathways of this new AI world, where agents will reason, act, and collaborate through endpoints. At this year's API Summit, we saw how quickly this vision is becoming reality.

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.

Key Takeaways Enterprise data teams spend millions on warehouse infrastructure while still designing schemas the way they did in 1995—one entity at a time, one relationship at a time, hoping the model survives its first encounter with production data. The irony runs deep: organizations racing to deploy real-time analytics are bottlenecked by modeling processes that take six to eight weeks before a single pipeline runs. Data warehouses succeed or fail on design.

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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.

If you’ve been following Kong, you know that Kong was the first in the API platform space to introduce an enterprise-grade AI Gateway for LLM workloads. Today, we’ve also introduced a new enterprise-grade MCP Gateway to ensure that you can roll out production-ready MCP deployments. But we are focused on more than just the Gateway. Today, we’re excited to announce additional MCP workflow support in the Konnect Developer Portal and a brand new MCP integration solution, the MCP Composer.

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.

A few years ago, we looked across many deployments and noticed a pattern: teams would build prototypes, spin up ML pipelines, and then stall. The model’s accuracy dropped. The “aha insights” dried up. The data scientists would get stuck waiting for dashboards to refresh, or data to be cleaned.AI is sexy. It sells. But it doesn’t do itself. The missing piece? Data readiness. Not just fast data.