Frequently AskedQuestions

QApilot’s baseline is zero-touch sanity coverage. The autonomous crawler explores the app like a real user, identified critical flows, and generated executable test cases without any upfront scripting or setup. The outcome is immediate visibility into app health rather than exhaustive regression on Day 1.

QApilot explores your app like a real user and builds a knowledge graph of screens, flows, and interactions. This allows it to identify meaningful user journeys and generate test coverage automatically.

QApilot focuses on critical user journeys first, providing immediate visibility into app behavior. Coverage expands over time as the system continues exploring and learning.

No upfront scripting or setup is required. You can start with your app build, and QApilot handles exploration and test generation automatically.

Yes, after the first crawl, once the base knowledge graph is in place, you can guide exploration, prioritize flows, and refine generated coverage based on your testing goals through the "Crawl More" option.

QApilot uses Appium under the hood, with additional customizations for stability, healing, and orchestration. Selecting an Appium version ensures compatibility with your existing ecosystem and allows smoother CI/CD integration without unexpected runtime mismatches.

No. While native IDs can be leveraged when available, QApilot layers contextual understanding and self-healing on top. This significantly reduces flakiness compared to traditional record-and-playback approaches that rely purely on selectors.

Recording is useful when you want to explicitly define specific flows, edge cases, or validations that require precise control.

Yes. Recorded tests are supported by AI self-healing, which helps them adapt to UI and flow changes over time.

Yes. Both are part of the same system and can be combined within the same test suites and execution flows.

QApilot is designed to plug directly into CI/CD pipelines and scale execution across multiple devices. Tests can be triggered as part of your pipeline, and parallel execution is supported. Scale depends on the device provider and license configuration, which we size based on your release frequency and device coverage needs.

QApilot integrates seamlessly with existing device cloud providers like BrowserStack or LambdaTest. The choice is entirely yours based on availability and existing licenses. QApilot behaves identically regardless of the provider and also includes built-in parallel execution licenses that can be used alongside your existing setup.

QApilot integrates with your CI/CD pipeline to trigger test runs automatically as part of your release process.

Yes. QApilot supports parallel execution across multiple devices and environments, depending on your setup.

Tests can run on real devices, cloud device farms, or integrated environments based on your infrastructure.

QApilot reduces flakiness through AI self-healing and context-aware execution, ensuring tests remain stable even as the app evolves.

Yes. Execution notifications are configurable. You can route updates to different Slack channels based on product, environment, or release type, ensuring the right teams get the right signals without noise.

Reports include execution results, screenshots, UI metadata, issue detection, and contextual insights to help teams understand failures clearly.

Each failure is mapped to the exact screen and interaction, supported with visual evidence and technical context, making debugging faster.

Yes. Reports and notifications can be routed to tools like Slack, ensuring the right teams receive relevant updates.

Yes. Intelligent bug detection surfaces issues like action latency, page load failures, and accessibility gaps during execution.

Flutter apps often lack stable selectors and involve complex transitions across Flutter, native, and webview contexts, making automation more challenging.

QApilot uses context switching, AI-assisted element discovery, and adaptive execution to ensure reliable testing across Flutter-heavy applications.

Yes. QApilot supports seamless interaction across Flutter, native, and webview layers within the same execution flow.

QApilot is built on a system of specialized AI agents that collaborate using a shared knowledge graph to enable autonomous testing.

The knowledge graph acts as the central context layer, capturing screens, flows, and interactions and enabling agents to make informed decisions.

Yes. QApilot supports Bring Your Own Agent, allowing custom agents to use the knowledge graph and extend testing workflows.

Custom agents can read from the knowledge graph, perform specific tasks, and contribute results back into the system.