Systems | Development | Analytics | API | Testing

AI has transformed software development, dramatically increasing velocity. The challenge now is maintaining quality at that speed. Engineering leaders across the industry are searching for a real answer. On March 18, we’re unveiling our solution. Join our livestream for an exclusive product reveal featuring special guest, John Romero. A legend in the industry and the perfect voice to help us unveil what we've been building.

The AI revolutionized coding, but software testing hasn’t caught up. Until now. Meet BearQ: QA built for the age of AI. BearQ introduces a new paradigm of autonomous, agentic quality assurance. Instead of static scripts and brittle frameworks, BearQ’s specialized AI agents – the QA Lead Agent, Tester Agent, and Explorer Agent – work continuously to: Testing was a static checkpoint. Now it’s a living, learning system that ensures application integrity.

Agent-powered code generation is happening at unprecedented speed, creating a growing gap between development velocity and your ability to validate what's being built. This leaves organizations unsure if their applications are doing what's intended or missing what's required. That's why SmartBear delivers application integrity for the AI era – ensuring continuous, measurable assurance that your software just works as intended, with governance to operate at AI speed and scale.

Poorly documented or inconsistent error models lead to brittle clients and unreliable automation. Whether you're building APIs for human developers or AI agents, proper error handling is crucial for automation and reliability. In this guided tutorial, SmartBear Solutions Engineer Rosemary Charnley demonstrates how to design robust error models in OpenAPI specifications using Swagger Studio.

API design, functional testing, and governance shouldn’t live in silos. In this demo, Product Owner Wojciech Nowacki walks through a practical, end-to-end workflow that connects: You’ll see how API definitions created in Studio feed directly into automated functional testing ensuring style compliance, functional correctness, and governance checks across the full API lifecycle. Perfect for API platform teams, architects, and developers looking to unify design and test automation.

As AI agents increasingly interact with APIs, design clarity and structured metadata matter more than ever. In this focused demo, Senior Solutions Engineer Mairtín Conneely take us through how to use Spectral rulesets in Swagger Studio to automatically enforce AI-ready API design standards across your OpenAPI definitions. This video covers:What “AI-ready” API design meansCreating custom Spectral rulesImporting governance rules into Swagger StudioRunning automated AI-readiness checksScaling API quality with governance automation.

Create a single mobile test that runs reliably on both iOS and Android - without building separate tests per platform or relying on brittle, platform-specific locators. In this high-level demo, we use SmartBear Reflect’s vision-based AI to record a typical workflow in a sample coffee app, where each step is backed by visual context and intent. Then we run the same test across a mix of Apple and Android devices, including an iPhone, to show how Reflect adapts to the environment at runtime and helps reduce flakiness and false positives.

In this video, you’ll discover how SmartBear QMetry's AI-powered test generation automatically transforms requirements into complete, executable test cases within minutes. Watch as we demonstrate test generation cases from Jira, Rally, and Azure requirements, demonstrate how to refine existing tests, and save your teams hours of manual work.

SmartBear Zephyr is the Jira-native test management and automation platform that empowers your team to deliver better software, faster. While Zephyr Standard is a powerful foundation, Zephyr Advanced takes your automation to the next level.

SmartBear Zephyr is the Jira-native test management and automation platform that empowers your team to deliver better software,faster. By creating test cases, linking them to user stories and requirements, and monitoring progress all within Jira, you can unify your testing and development efforts. This short video demonstrates how to use a test case in Zephyr, known as the “Call to Test” capability. You’ll see how you can reference and reuse test cases across multiple Jira projects, no matter the test case type.