QI Home is where you generate test cases, track coverage, and automate with AI.
\nQI Home is where Atto, the AI feature in Test Management by Testsigma, generates test cases from your requirements, tracks coverage against your modules, builds test plans, and automates test execution. It also detects developer activity from connected Claude Code, Cursor, GitHub Copilot, and Codex context and GitHub pull requests, so your test coverage stays current with what your team is building.
\nYou do not write test cases from scratch. You give Atto the context it needs, and it generates test cases for you. You review what was generated, accept the cases that are accurate, and save them to your library. Coverage, test plans, and quality metrics update as you go.
\nThere are two ways to start: Ad-Hoc, where you attach context manually and trigger generation yourself, and Sprints, where Atto detects a sprint start and begins generation automatically. Everything after generation works the same for both.
\nQI Home gives you two starting points depending on how your team works. The generation trigger is different for each, but the rest of the workflow is identical.
\nAd-Hoc lets you generate test cases on demand by attaching your own context sources, without tying them to a sprint. You open a new session, attach context sources, write a prompt, and click Generate. Atto reads what you have provided and generates test cases mapped to your features.
\nContext sources you can attach include:
\nUse Ad-Hoc when:
\nSprints mode generates test coverage automatically at the start of each sprint, pulling context straight from your linked stories. When a sprint starts in your connected project management tool, Atto detects it and shows a notification. You confirm generation, and Atto pulls in the context linked to the sprint stories, including Figma designs, Confluence pages, PRDs, and relevant pull requests, and begins generating test cases.
\nUse Sprints when:
\nWhether you use Ad-Hoc or Sprints, the next steps are the same. You review the test cases Atto generated, accept the ones that are accurate, and save them to your library. Coverage, test plans, and quality metrics update as you go.
\nReview and Accept Test Cases allows you to browse the generated test cases grouped by scenario, view step-by-step details for each case, and accept or reject them individually or in bulk. Test cases you save go into your library. Test cases you do not accept are tracked as gaps.
\nCoverage and Gaps shows you the coverage percentage per module. Coverage is calculated as accepted test cases divided by accepted plus pending test cases, and rejected cases are excluded. Gaps are pending test cases that have not been accepted yet. They are your signal that certain areas of the application are not yet covered.
\nTest Plans are generated automatically by Atto in four types: Smoke, Feature, Regression, and Deep Regression. Each type is a superset of the previous one. Smoke is always included in Feature, Feature in Regression, and Regression in Deep Regression. Plans are ready to run as soon as you have accepted test cases.
\nQuality Intelligence Metrics are five metrics shown in the session header that together tell you how confident you can be in the current build. The metrics are Coverage, Pass Rate, Confidence, Release Readiness, and Release Gate. They update as test cases are accepted and test runs are executed.
\nOnce a test case exists in your library, Atto can automate it without you writing any code or scripts.
\nAgentic Learning opens a browser, either on Testsigma Lab in the cloud or on your local device, and walks through the test case steps on your live application. Atto observes how the application behaves at each step, learns the element interactions, and generates automated steps. You review the output and save it to your library. The test case moves from manual to automated in a few minutes.
\nCopilot takes those automated steps and executes them in a browser with a live panel showing each step as it runs. You can pause the execution, add new steps mid-run, switch between manual and automated steps, and save the results when done. Copilot also works without Agentic Learning for running any test case interactively, which is useful for quick sanity checks or exploratory runs.
\nDeveloper Context Mapping keeps your test coverage aligned with what your team is actually building.
\nWhen your developers work in Claude Code, Cursor, GitHub Copilot, or Codex, or open pull requests in GitHub, Atto detects that context and surfaces it in the Unmapped Context view in QI Home. Each context entry includes an AI-generated suggestion for which module and sprint it belongs to. You review the suggestion and map it with a few clicks. Once mapped, Atto generates new test cases or updates existing ones based on the code changes or development activity captured.
\nSee Overview: Developer Context Mapping for how the Unmapped Context model works, when to use GitHub versus a CLI tool, and what happens when a developer raises a PR for work already captured as CLI context.
\nAd-Hoc
\n\nSprints
\n\nShared Workflows
\nAutomation
\nDeveloper Context Mapping
\nOthers
\nQI Home requires an active project in Test Management by Testsigma. To attach context from Jira, Azure DevOps, Linear, ClickUp, Confluence, or Figma in Ad-Hoc, you need the respective integration connected to your project. Files, documents, and video recordings can be attached without any external integration. For Sprints, connect your project to a supported project management tool. For Developer Context Mapping, connect your Claude or GitHub account.
For questions or support, reach out to the Testsigma team at support@testsigma.com.
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