Sembi Introduces AI Test Prioritization for TestRail and Xray

Sembi, the premier SaaS portfolio for testing and security solutions, announced AI Test Prioritization for its leading test management brands. This new feature joins the portfolio of AI-powered process improvements already available in TestRail, the leading dedicated QA test management platform, and Xray, the leading test management solution for Jira, to help quality professionals identify high-risk tests faster using AI-powered prioritization based on historical risk, defect patterns, and semantic context.

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“Over the last year, Sembi has introduced AI capabilities that help teams create test cases, accelerate automation, evaluate AI systems, and now prioritize execution, completing the testing workflow,” said Judy Bossi, Vice President of Product at Sembi.

As the volume of AI-generated code ramps up, only 17% of engineering teams feel their testing has improved, according to Sembi’s Software Quality Pulse Report. Teams waste valuable time manually deciding what to test first, while critical defects can remain buried inside hundreds of AI-driven test cases.

Unlike traditional prioritization tools that primarily rely on past failures, TestRail 10.5 and Xray 15.0 combine machine learning with AI-driven semantic analysis to identify high-risk tests even when little to no execution history exists.

“Traditional prioritization models can make it difficult to identify risks when there’s little to no execution data available,” said Annie O’Brien, Head of Product Management at Xray. “By combining historical risk signals with AI-driven semantic analysis, teams can go beyond historical patterns to identify the tests most likely to uncover defects and focus on what matters most.”

Integrated across Sembi’s testing portfolio, AI Test Prioritization leverages tailored machine learning to guide engineers on which tests to prioritize first based on their individual goals:

• Prioritize High-Risk Tests Automatically: Scores every test based on analysis of execution history ranging from seven days to 180 days, eliminating the need for manual execution log review and unlocking actionable data.
• Test Ranking with AI-Driven Semantic Analysis: Uses specific labels (compliance, security, performance) and historical risk signals to create a more meaningful execution order.
• Transparent AI Recommendations: Prioritizes tests with AI-generated values and reasonings, giving teams more confidence in their testing plans.

For Xray customers, AI Test Prioritization brings intelligent risk-based testing directly into Jira-native workflows, helping agile and DevOps teams prioritize testing in the same environment where they manage requirements, issues, and releases. For TestRail customers, it supports dedicated QA teams managing structured test repositories and complex test suites, helping them focus execution on the tests most likely to uncover risk.

To support customer control and data governance, TestRail and Xray both provide administrative controls for managing AI functionality, including the ability to disable AI features at the instance, user, or project level. Customer data is not used to train, fine-tune, or improve generally available AI models. Any data processed by AI services is handled securely, encrypted both in transit and at rest, and is not persistently stored beyond the processing required to deliver the requested functionality.

“AI Test Prioritization represents the next step in the AI-powered testing workflow we’re building across our testing solutions,” said Judy Bossi, Vice President of Product at Sembi. “Over the last year, we’ve introduced AI capabilities that help teams create test cases, accelerate automation, evaluate AI systems, and now prioritize execution. As agentic orchestration and MCP begin to reshape what’s possible across the software quality lifecycle, we’re excited by the potential to create even more connected and intelligent quality experiences in the future.”

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