SmartBear, helping teams build, test, and ship quality software at AI speed and scale, has announced new capabilities for BearQ, its agentic QA system, that move beyond standard test automation to continuously understand what needs testing and coordinate quality across the software delivery lifecycle.
SmartBear has announced new capabilities for BearQ, its agentic QA system: Sources and Workflows.
Sources extends BearQ's understanding beyond the application to requirements, bugs and existing test coverage.
BearQ now connects with Atlassian Jira to understand what should be tested, and with SmartBear Reflect and SmartBear Zephyr to recognize what's already tested.
More Sources are planned for Q4, and Workflows lets teams orchestrate sequences of QA activities and decide when they run and how much autonomy BearQ gets.
A recent SmartBear survey found trust is software experts' biggest barrier to adopting autonomous testing.
BearQ's progressive autonomy model lets teams start with people reviewing and approving its work, then automate more as confidence grows.
"Jira is where teams plan, track, and manage work. But those tasks are just part of what QA helps reconcile – there's also bug reports, and existing manual and automated tests," said Alan Braun, head of product ecosystem at Atlassian. "Tools like BearQ that bring together information help identify and test what actually matters."
"Autonomous testing is the first step. The bigger opportunity is connecting everything that informs software quality – how an application behaves, what teams intend it to do, and the testing that already exists," said Bridges Smith, vice president of product management for AI at SmartBear. "With Sources and Workflows, we're bringing those pieces together so teams can build on their existing testing investments and progressively introduce more autonomy into how they manage quality. That's the next step in our vision for BearQ: moving beyond autonomous testing toward autonomous quality, with humans defining the guardrails and level of control."
As AI accelerates development, QA's challenge is no longer just automating individual tests, it's continuously understanding what needs testing, what's already covered, and how to coordinate that work across increasingly complex systems. New BearQ capabilities Sources and Workflows address this by connecting what BearQ learns from testing an application with the quality context around it, and then coordinating the work that follows.
Sources: A 360-degree view of quality. Sources extends BearQ's understanding beyond the application to the requirements, bugs, and existing test coverage across a team's QA ecosystem. With this context, BearQ helps teams find coverage gaps, avoid duplicate tests, and focus new testing where it matters most.
Workflows: From quality intelligence to coordinated action. Workflows lets teams orchestrate sequences of QA activities and decide when they run and how much autonomy BearQ gets. Schedules, BearQ events, or external systems such as CI/CD pipelines can trigger a workflow to prepare environments, run targeted or regression tests, and update connected systems. This extends BearQ's autonomy beyond individual tests to the processes teams use to manage quality.
BearQ's progressive autonomy model is what gives teams control, and according to a recent SmartBear survey, trust is software experts' biggest barrier to adopting autonomous testing. Teams can start with people reviewing and approving its work, then automate more of the process as their confidence grows, using review steps and focus areas to decide how autonomously BearQ operates. Together, these capabilities help teams ensure application integrity, meaning applications work as intended, reliably, and at scale.
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.
