AI and software quality
AI is changing software testing. It makes work faster, sharper, and more consistent. But only if you know what you're using it for and what you want to achieve with it. At Cerios, we use AI to enhance quality. In test processes, in tooling, in teams.
Our AI approach
At Cerios, we first test AI in our own projects before we use it for you. In our community, we share knowledge and ask sharp questions. Our consultants use AI for analyses, sharpen user stories and generate test cases. What works, we take with us. What doesn't work, we improve. This is how you get the best out of your software with AI.
AI applications
You can use AI for software quality in various ways. Depending on your situation and goals, you choose the approach that suits you best.
AI in daily testing
Analyze user stories, refine requirements, prepare test cases. This saves time and creates space for work that really adds value: craftsmanship, collaboration and strategic choices.
Validate AI systems
AI works differently than traditional software and requires a different testing approach. We detect bias, ensure explainability and ensure compliance with the EU AI Act. From algorithm to impact, you get full insight.
Making teams AI-savvy
AI knowledge is becoming increasingly important, but not everyone knows where to start. Through training courses, learning journeys and communities, we build skills. For your team and our own consultants, because learning together works best.
Secure AI Deployment
Without clear governance, AI can create more problems than solve them. We set frameworks, ensure transparent processes and guarantee privacy. This gives you AI that you can control and trust.
Assessing AI Readiness
Many organizations don't know where they stand with AI. Where are the odds? What are the risks? Which steps provide the most value? We create a realistic roadmap that suits your organization.
Why do organizations choose us
We are not the first to talk about AI, but we are one of the few to systematically test, apply and further develop it. Our consultants work with it every day. In real projects, with real customers, with real challenges.
This gives us insight into what works and what doesn't. What pitfalls there are and how to avoid them. We are happy to share that knowledge through training courses, communities and concrete projects. Because only if everyone understands AI can we benefit from it together.
Frequently asked questions about software-quality AI
AI often raises the same questions. What does it really deliver, what about safety and when is it useful to use? We'll answer the most common questions so you can quickly know where you stand.
That depends on your current test processes and challenges. If you spend a lot of time on repetitive tasks, have trouble with consistency, or want faster feedback, AI can be valuable. Or maybe test automation without AI is the best choice. We always start with an analysis of your situation.
Safety comes first. We work with platforms within your own environment, such as Microsoft Azure, and set clear governance rules. You always have control over your data and processes.
No, AI empowers testers. It takes over repetitive tasks and provides quick insight into large amounts of data, so that your team can focus on analysis, collaboration, and strategic choices. Human expertise is becoming more important, not less.
For daily use of AI tools for software quality, you can often see a difference within a few weeks. For more complex implementations or building AI skills, we usually count on a few months.
This varies by situation. Some AI tools are relatively easy to add to existing processes, while others require more investment. We always make a realistic cost-benefit analysis first. Should our people take AI training first? Training helps, but it's not always necessary to get started. Learning by doing is just as important. We're gradually building AI skills, tailored to your pace and needs. Some tools can be used immediately. We have various training courses for all levels of knowledge that we can offer at the right time.
By systematically testing, detecting bias and ensuring explainability. We monitor performance and adjust where necessary. Transparency and auditability are key.