SmartBear has announced AI enhancements for API testing, UI test automation, and test management across its product suite, the SmartBear Application Integrity Core, adding agentic and AI firepower to human-led testing workflows and marking the highest volume of AI features released at one time.
New agentic capability in Reflect allows developers and QA engineers to generate automated tests directly from their coding environment through the SmartBear MCP server.
New Rovo agent skills for Zephyr enable natural-language queries within Atlassian Jira to evaluate test coverage, search test executions, and assess release readiness.
AI capabilities are now available for on-prem tools including natural-language AI test generation in ReadyAPI and enhanced AI-based object detection in TestComplete.
The enhancements follow SmartBear’s recent release of BearQ, its fully autonomous testing solution.
A SmartBear study found that 70% of respondents are concerned that quality is already suffering as AI speeds code creation, and 68% worry that faster AI code development will create testing bottlenecks.
SmartBear defines application integrity as continuous, measurable assurance that software works as intended with governance to operate at AI speed and scale.
The new capabilities add agentic and AI firepower to human-led testing workflows—including leveraging AI for on-premise applications. They follow SmartBear’s recent release of BearQ, its fully autonomous testing solution, to round out the industry’s most comprehensive portfolio of AI-infused application testing products.
“SmartBear is firing on all cylinders to enable QA teams to move faster and improve application level testing. We see some teams racing toward fully autonomous solutions like BearQ, and others deploying AI-enabled tools to complement human-directed automation or even manual workflows,” said Vineeta Puranik, SmartBear CPTO. “We meet customers where they are on their AI journeys by helping teams adopt AI confidently, scale testing effectively, and maintain application integrity as software delivery accelerates.”
New agentic capability in the SmartBear test automation platform, Reflect, lets developers and QA engineers generate automated tests directly from their coding environment. By invoking Reflect through the SmartBear MCP server, teams can pull in richer context, drawing on existing test assets, unified visibility and reporting, and development history. This creates context-aware tests agentically and accelerates automation adoption without starting from scratch.
New Rovo agent skills for Zephyr enable natural-language queries within Atlassian Jira to evaluate test coverage, search test executions, and assess release readiness, so QA teams can quickly identify gaps and prioritize testing work.
SmartBear has also added AI capabilities to its on-prem tools for desktop testing and secure, local environments—including natural-language AI test generation in ReadyAPI for building complex multi-step API tests, and enhanced AI-based object detection in TestComplete. This improves automation reliability for rapidly changing applications, all with enterprise governance controls to meet compliance and quality standards.
SmartBear defines application integrity as continuous, measurable assurance that software works as intended, with governance to operate at AI speed and scale. Given the increasing speed of AI-driven code creation, and the risks associated with that code, new solutions are needed to ensure application testing keeps up.
In the recent SmartBear Study: Closing the AI Software Quality Gap, 273 software testing and quality decision makers found that seven of 10 respondents are concerned that quality is already suffering as AI speeds code creation and 68% are worried that faster AI code development will create testing bottlenecks.
“Organizations are looking for practical ways to apply AI across their software delivery lifecycle,” said Chris Lewis, CEO of Praecipio, an Atlassian-specialized management consulting firm and SmartBear partner. “Capabilities like these from SmartBear help teams uncover testing gaps and act on them quickly, exactly the kind of innovation we help our clients operationalize.”
More enhancements to the SmartBear product line are expected later this year to drive even faster test creation, trustworthy automation, and quality management that is more intelligent and scalable. To hear more about our product roadmap, register for the “SmartBear Roadmap: Delivering Application Integrity Across the SDLC” webinar for April 8, 2026 at 10 a.m. ET.
About SmartBear
SmartBear delivers application integrity for modern tech stacks, ensuring continuous, measurable assurance that software just works as intended – with governance to operate at AI speed and scale. SmartBear offers deep test automation, API lifecycle management, and observability capabilities. With integrations across the SDLC, it sets a new quality standard for application delivery teams.
SmartBear is trusted by more than 16 million developers, testers, and software engineers across 32,000 organizations, including 75% of the largest financial institutions and industry leaders such as Adobe, JetBlue, and Microsoft. SmartBear’s best-loved brands include Swagger, TestComplete, Reflect, QMetry, Zephyr, and more. As stewards of a collaborative open source community, SmartBear meets customers where they are to make our technology-driven world a better place.
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