Systems | Development | Analytics | API | Testing

Your pipeline is green. But do you actually know what you tested? Most teams don’t know what changed, what was covered, or what risk remains. That’s the gap Quality Intelligence solves. It turns test and engineering data into real, evidence-based confidence so you can release faster, with less risk. With Tricentis SeaLights, you can move from assumption to understanding. So you don’t just test more, you understand more!

Dive into the pros and cons of data masking and synthetic data generation, with real-world examples and practical use cases. In this webinar, Perforce Delphix experts Ilker Taskaya and Hims Pawar show you how to select the right approach based on your specific needs, compliance requirements, and data accessibility challenges.

The tsunami of AI-generated code creates downstream bottlenecks for QA teams, and shift-left or traditional test automation aren't enough in the AI era. In this From the Bear Cave session, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel unpack how AI code generation impacts software quality and why traditional testing struggles to keep up.

Learn more: Speedscale.com.

Find out the key differences between GDPR (focused on data privacy) and the EU Data Act (focused on data ownership and portability). In this clip from the OpenLogic webinar, "Navigating EU Compliance: Open Source Strategies for Digital Sovereignty and Resilience", Perforce CISO Aaron Kiemele explains that contract clauses locking data into proprietary silos are now hard to enforce, and businesses must have credible, tested plans to exit a software platform if data policy or residency requirements shift.

Get information about the practical compliance requirements of the EU AI Act, the first AI regulatory framework with real enforcement teeth. In this clip from OpenLogic's webinar "Navigating EU Compliance: Open Source Strategies for Digital Sovereignty and Resilience", Perforce CISO Aaron Kiemele walks through classifying AI systems by risk level, establishing human oversight and audit trails, and documenting training data provenance — while noting that these steps are straightforward but frequently overlooked by organizations.