Insights

OctoPerf stands out as a modern, user-friendly platform that empowers us to simulate real-world conditions and ensure your applications can handle peak demands.

In today’s fast-paced world of software development, integrating Artificial Intelligence (AI) into your testing processes should no longer be just an option but a smart move to enhance your testing capabilities. AI-powered testing brings a multitude of advantages that can significantly boost the efficiency, accuracy, and cost-effectiveness of your QA efforts.

In the ever-evolving world of artificial intelligence, large language models (LLMs) have emerged as some of the most powerful tools for understanding, generating, and predicting textual content. Think of them as superheroes using deep learning techniques and huge sets of data to understand, generate, and predict textual content - what words should come next.

When planning a test automation strategy, one of the most common questions is: Should I use a script-based approach, or go for module-based test automation? Both approaches offer distinct advantages, but determining the right fit for your application depends on various factors.

In today’s fast-paced software landscape, time to market, risk management, and cost efficiency are key drivers of success. At Qnit, we believe in testing smarter—not harder. This strategy isn’t just a slogan, it’s a mindset that helps our clients optimize their testing processes, achieve faster releases, and maximize risk coverage while keeping costs under control.

In early 2015, Qnit didn’t exist—at least, not in the form it is today. Instead, there was a small but highly dedicated Quality Assurance (QA) team working within PRODYNA. This group of experts was focused on ensuring software quality, so much so that they developed their own in-house test automation tool, Nabucco, tailored to meet their unique needs.