Systems | Development | Analytics | API | Testing

AI claims automation is becoming a major focus for insurers as manual claims processing continues to create cost, speed, and customer-experience challenges. Traditional systems often route documents through multiple human reviewers, creating bottlenecks that consume time and operational resources.

Debugging is an essential skill that allows software developers to prevent crashes and maintain reliable code. Virtually all applications run into bugs at some point, due to logic errors, unexpected inputs or system interactions. It’s vital that we have effective tools and processes to resolve them. This guide will give you a step-by-step guide to debuggging, highlighting common error types with practical means to resolve them.

Progressive Web Apps (PWAs) combine the reach of the web with many native app capabilities. Users get an app-like experience without the traditional app-store download process, while developers can build and maintain experiences from a shared web codebase. This doesn’t mean PWAs are simple to build, however. They must provide a reliable experience across different browsers, devices and network conditions.

On June 25, 2026, new cloud testing standards were formally announced, establishing a unified baseline for validating performance, security, and compliance in cloud environments worldwide. These standards are the result of years of technological advancement and an industry-wide push for more rigorous, repeatable validation methods as cloud architectures have grown increasingly complex.

AI adoption across multifamily and PropTech has outpaced the rules meant to govern it, and one of those rules is now in force. On August 2, 2026, the transparency obligations under Article 50 of the EU AI Act began to apply, setting specific requirements for how certain AI systems interact with people and how AI-generated content is marked and disclosed.

The CDO’s job can be boiled down to ensuring data access, building innovative data products, and managing data responsibly.

Regulated QA teams carry a pressure most testing platforms weren’t built to solve for at the same time. Every release still needs traceability from requirement to test case to defect that holds up under audit. Approvals and evidence still need to be airtight. At the same time, agile releases, DevOps pipelines, and AI-assisted development keep moving, whether or not the testing platform underneath has kept pace.

Imagine telling an AI assistant: “Find me waterproof trail shoes, size 10, under €140, delivered before Friday. Use my usual card if the total stays within budget.”