Quality assurance teams across modern software development face a new reality. AI enabled applications do not behave like traditional systems. Outputs shift based on context....Read More The post ...

In the next few years, software testing — a critical but traditionally manual phase of development — is poised for a ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Strategic AI-driven QE can be the key to accelerating delivery, strengthening reliability and maintaining market velocity.

Key opportunities in the Global App Test Automation Market include leveraging AI and machine learning to enhance testing efficiency, advancing cloud-based real device testing solutions, and ...

Imagine a customer placing an order online. They browse a website, add items to a cart, and complete the checkout process. It ...

What happens when Ramp-testing a vehicle happens around the assembly line, earlier-faster-deeper-and-smarter than before? And ...

Generative AI is rapidly changing how software is designed, built, and maintained. As these systems become more capable, they are also reshaping how quality assurance teams approach testing, ...

IoT penetration testing is a security assessment of the complete IoT ecosystem, from backend systems and cloud services to mobile devices and hardware. It involves a multi-stage simulated attack on ...

Micro1 is building the evaluation layer for AI agents providing contextual, human-led tests that decide when models are ready ...

If AI writes code like a teenager, then testers need to be the adults in the room. That doesn’t mean standing at the end of ...

As enterprises rethink their testing strategies, many teams are reviewing AI test automation tools that can help modernize QA ...