Systems | Development | Analytics | API | Testing

Testing complex UI elements like CAD software, Google Maps, or Citrix environments often leads to brittle tests and false negatives. Vision AI solves these automated testing challenges by recognizing elements just like a human would, reducing manual testing efforts, and improving accuracy. Discover how vision AI strengthens automated testing for visually complex applications. This tutorial shows you how to enhance object recognition in SmartBear TestComplete and eliminate test failures caused by 3D applications, canvas-based apps, and virtualized environments.

Recent SmartBear research shows that 70% of teams are already seeing quality degrade with AI-generated code, creating a real bottleneck in the software-development lifecycle (SDLC). As output increases, QA teams are left choosing between delaying releases to validate changes or shipping faster with less confidence in what’s actually working. In this From the Bear Cave clip, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel dig into a growing gap in modern software development: how AI is accelerating code generation but testing and quality validation aren’t scaling with it.

AI-generated code is flooding your pipelines. Your test automation debt is piling up. If this sounds familiar, you're not alone. Velocity can't come at the cost of quality. As AI transforms how we build software, API testing must evolve. Join Justin Collier, Senior Director, Product Management, and Yousaf Nabi, Developer Advocate, to explore the future of API testing in an AI-driven world.

Learn how to get started with TestComplete in this comprehensive beginner's tutorial. TestComplete is an automated testing platform for desktop, web, and mobile applications – and this guide will help you create your first test in just minutes. What You'll Learn: This video is perfect for test automation engineers and developers new to automated testing. Whether you're testing desktop applications, web apps, or mobile interfaces, this tutorial covers the essential features every TestComplete user needs to know.

When multiple designers and teams contribute APIs, you face inconsistent schemas, divergent patterns, and broken assumptions. However, the "shift-left" approach to API standardization helps you catch issues early, automate compliance, and maintain quality without manual gating – making your API program truly scalable. In this video, SmartBear Senior Solution Engineer Joe Joyce demonstrates how to enforce consistent API standards across large development teams using Swagger Studio's governance, collaboration, and CI/CD integration features.

As software teams move faster across APIs, testing, and observability, keeping application integrity intact is harder than ever. Join SmartBear product leaders for a Now / Next / Later look at how we’re evolving our platform to help teams build, test, and operate software with confidence. What you’ll get from this session: Get a clear view of where SmartBear is headed and how these capabilities come together to help your teams scale quality alongside velocity across the SDLC.

Modern APIs aren’t just read by developers anymore; they’re also interpreted by tools and AI agents. In this video, Solutions Architect Joe Joyce walks through how to enrich an OpenAPI definition in Swagger Studio with meaningful metadata such as descriptions, summaries, operation IDs, tags, schemas, and examples. You’ll see step-by-step how these additions help tools and automated agents better understand API intent, purpose, and semantics. This turns your OpenAPI definition into a contract that scales beyond documentation.

In this demo, you’ll see how Reflect and QMetry work together to connect automated testing with test management. In this short walkthrough, test execution from Reflect flows directly into QMetry, giving your team better visibility, reducing manual effort, and helping you move faster without losing control of quality. If you’re looking to scale testing while keeping everything organized and traceable, this integration is built for you.

Testing teams need to know if they’re ready for a release. Getting answers within Jira, however, often means jumping between multiple screens and reports. In this demo, see how you can query your test data with SmartBear MCP for Zephyr to get insights directly from your testing system of record, so you can make faster, more informed release decisions. From within AI tools like Copilot, Claude, or VS Code, you’ll learn how you can.