AI is transforming quality engineering, bringing greater efficiency, precision and innovation to how software is delivered. See how these solutions can speed up your workflows, reduce manual effort and help your teams make smart decisions with confidence.
Robby Putzeys, Resillion’s Global Head of Software Testing Practice, Jon Anthony, founder of Adappt Artificial Intelligence, and Bert Lagaisse of KU Leuven will take a look at the changes likely to arise when adopting AI-generated coding. Together, our experts will thoroughly analyse what you should consider before and during the adoption process.
As businesses increasingly adopt AI-driven solutions, AI-generated code is emerging as a critical trend, offering both incredible opportunities and significant challenges.
Are you prepared for the risks and rewards?
A structured assessment identifies inefficiencies and bottlenecks across the software engineering lifecycle. This process highlights where AI can deliver measurable improvements. For example by accelerating delivery, enhancing quality or reducing operational overhead.
Generative AI supports tasks such as test case creation, test automation and requirements analysis. These capabilities reduce manual workloads, improve consistency and enable faster, more reliable releases.
Applying AI to software engineering data uncovers patterns, surfaces actionable insights and guides better decision-making. Naturally this leads to improved performance, reduced costs and shorter time to market.
AI systems are validated to ensure they are explainable, compliant and free from bias. This supports responsible innovation and ensures alignment with industry standards and regulatory frameworks.
Our comprehensive AI-enabled QA assessment helps organisations evaluate their readiness for AI, identify practical use cases and implement strategies to integrate AI seamlessly into their QA processes.
AI detects anomalies, clusters similar failures and identifies root causes faster than manual methods. This cuts triage time and speeds up resolution.
By integrating AI into CI/CD pipelines, it’s possible to generate real-time quality feedback. This supports faster, more reliable releases in agile and DevOps environments.
AI analyses user behaviour and feedback to prioritise features and fixes that matter most. This keeps development aligned with real-world needs.
Test cases are automatically generated from requirements, user stories or production logs. This improves coverage, speeds up test creation and enhances consistency across releases.
Providing solutions in a unified, structured approach across all critical domains to enable end-to-end quality - Because we’re the only ones who can.
Contact us for a free consultation and find out how we can make a difference to your business
