Systems | Development | Analytics | API | Testing

AI is evolving faster than the guardrails meant to validate it, leaving organizations exposed to compliance risk, model drift, opaque decision paths, and breakdowns in trust.

Getting the right answer to a technical question, right when you need it, can be the difference between a minor speedbump and a major roadblock. We all know the feeling of being stuck on a specific error or needing a quick "how-to" guide to keep a project moving. That's why we’re excited to announce that the new 24/7 Katalon Support Assistant is now live in production! It's an AI-powered technical support agent and the fastest way to get the help you need, anytime.

Insurance companies face unique challenges in delivering reliable software quickly. Policy updates, claims processing, and regulatory compliance all demand precision and speed. Manual testing alone can create delays, introduce errors, and increase operational risk. That's where test automation for insurance industry comes in. Repetitive regression tests that previously take up so much time can easily be automated.

In today's digital-first world, we face a profound paradox. The technology that connects us, powers our businesses, and fuels innovation is also leaving a significant and growing impact on the environment. Data centres use more energy than certain nations, harmful code wastes gigawatts of electricity, and the ongoing need for more powerful gear means that creation and disposal never stop.

Load testing, performance testing and stress testing are often mixed up, but in today’s CI/CD pipelines and production-grade engineering, they are solving completely different purposed. If you want to: Automate testing within CI/CD pipelines, such as with Keploy, JMeter, Locust, or k6 This guide discusses the difference like Performance testing, Load testing and Stress testing.

We’ll always remember 2025 as the year AI code assistants went big. Copilot, Cursor, Claude, Windsurf, whatever. Developers went from mistrusting these tools, to being expected to turn over much of their coding labor to them. Even if, according to an extensive Stack Overflow survey, only 3 percent of professional developers say they ‘highly trust’ AI coding tools.

After some testing and bug fixes, one common question always remains: how do teams make sure that those defects are truly resolved, and no new regressions creep in? That’s where retesting testing becomes vital. Retest testing forms a very important aspect of any QA cycle, ensuring that the reported defects are fixed and working correctly before the software moves to production. Without it, even simple patches can introduce silent issues into live environments.