An AI-powered extension for Azure DevOps that leverages cutting-edge large language models to transform how software engineers and QA teams work. By integrating the latest AI technologies directly into your DevOps workflow, it significantly reduces the time spent on documentation, test planning, and code reviews while improving the quality and consistency of your deliverables—all without leaving Azure DevOps. Key capabilities
✅ Acceptance criteria generationConvert user stories into clear, testable criteria in seconds. The AI analyzes your work item description and generates structured acceptance criteria that define exactly what "done" looks like. This eliminates ambiguity during sprint planning and ensures every team member—from developers to testers—shares the same understanding of requirements. By transforming vague stories into precise, actionable conditions, you reduce back-and-forth clarifications, minimize rework, and accelerate your grooming sessions. The generated criteria serve as a contract between stakeholders and the implementation team, making reviews and sign-offs faster and more confident.
🧪 Test case creationPropose structured test cases linked to work items to boost coverage and traceability. Automatically generate comprehensive test scenarios that align directly with your acceptance criteria, ensuring nothing falls through the cracks. Each test case is pre-populated with steps, expected results, and traceability links, saving hours of manual documentation. This capability helps QA teams scale their efforts without sacrificing quality—whether you're working on a single feature or planning regression suites across sprints. The result is higher test coverage, better defect detection before production, and full visibility into which requirements have been validated.
🐛 Create bug from test caseCreate bug with prefilled steps based on a test cases that Failed. When a test fails, capturing all the context manually is tedious and error-prone. This feature instantly transforms a failed test case into a fully detailed bug report—complete with steps to reproduce, expected vs. actual results, and linked work items. Testers no longer need to copy-paste or rewrite information; developers get actionable, consistent bug reports that accelerate root cause analysis. The seamless flow from test execution to bug creation reduces friction, speeds up resolution cycles, and maintains traceability throughout your DevOps pipeline.
🔍 AI code reviews on PRsIdentify potential defects, security smells, style inconsistencies, and maintainability issues on demand. When triggered, the AI analyzes pull request files for code quality concerns, security vulnerabilities, performance bottlenecks, and adherence to best practices. This AI-driven review layer acts as an on-demand senior developer, catching subtle bugs, enforcing coding standards, and suggesting refactorings that improve long-term maintainability. While it may surface more observations than a typical human review, the thoroughness helps teams build stronger, more secure codebases. The result is higher code quality, fewer production incidents, and continuous learning opportunities for the entire development team.
Native Azure DevOps experience: Works where your teams already collaborate—no context switching. Why teams use it⚡ Faster grooming & planning — Transform vague user stories into shippable specifications in minutes instead of hours. AI-generated acceptance criteria eliminate the back-and-forth between product owners and developers, ensuring everyone starts with a shared understanding of what needs to be built. This acceleration means you can groom more stories per session and get to implementation faster. 📊 Higher test coverage — Automatically generate test cases that align perfectly with your acceptance criteria, then link them directly to work items for full traceability. Teams report significant increases in test coverage without adding QA headcount, because the AI handles the tedious documentation work while testers focus on execution and edge case discovery. ✨ Better code quality — Leverage AI-powered code reviews to catch defects, security vulnerabilities, and maintainability issues that might be missed during manual reviews. The AI acts as an additional pair of expert eyes, identifying problems early when they're cheapest to fix and helping teams learn best practices through inline suggestions. 🔐 Full control over your data — Choose between managed AI subscriptions or bring your own Azure OpenAI resource with the BYOK (Bring Your Own Key) plan. The BYOK option gives you complete control over your API keys, model deployments, and token usage—ideal for organizations with strict data governance requirements or those who want to manage AI costs directly through their existing Azure subscriptions. Your code and work items stay within your infrastructure. Getting startedAfter installing the extension, you'll need to activate it before you can start using AI-powered features. Click the extension's page in Azure DevOps to either start a free trial or select a subscription plan that fits your team's needs. The trial gives you immediate access to all capabilities—acceptance criteria generation, test case creation, bug reporting, and code reviews—so you can experience the productivity gains firsthand. Once activated, the extension integrates seamlessly into your existing workflows, appearing directly within work items and pull requests where your team already collaborates.
Release notesv1.0.0 — Initial release: Acceptance criteria generation, Test case generation, Create bug from test case, PR code review |
