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Drizz raises $2.7M in seed funding •
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Featured on Forbes
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Drizz raises $2.7M in seed funding •
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Featured on Forbes

Modern mobile apps change constantly: UI layouts shift, flows branch, pop-ups appear unpredictably, and backend data changes in real time. Traditional mobile automation struggles to keep up because it relies on fragile selectors, platform-specific tooling, and heavy test maintenance.
Drizz approaches mobile testing differently. It is an automated mobile testing platform for Android, iOS, and mobile web that executes tests visually, the way a real user interacts with an app. Tests are authored in plain English, executed deterministically across devices, and remain stable even as the UI evolves.
This makes Drizz suitable for teams that need reliable end-to-end coverage across iOS and Android without maintaining separate test suites or rewriting scripts every release.
Drizz supports automated testing across:
The same test logic runs across OS versions, screen sizes, and device form factors. There is no dependency on Android- or iOS-specific selectors, accessibility IDs, or UI trees. Tests execute visually, allowing teams to write once and validate behavior consistently across platforms.
Execution is supported in cloud environments, locally connected devices, or private on-prem / VPC deployments for teams operating in controlled or regulated environments.
Drizz replaces locator-based automation with a Vision-AI execution layer that interprets what appears on the screen in real time. Instead of binding steps to XPath, resource IDs, or platform-specific frameworks, each step expresses user intent in structured plain-English commands.
This approach allows Drizz to:
Because intent is preserved visually, tests remain stable across releases without constant updates.
Drizz supports full end-to-end mobile testing across complex real-world scenarios, including:
API testing is integrated directly into UI flows. Teams can define APIs, execute them during tests, and reuse responses later in the flow—allowing true end-to-end validation from backend response to on-screen behavior.
Tests in Drizz are authored using structured, plain-English commands. No programming languages or automation frameworks are exposed. Teams do not need to work with Java, Swift, JavaScript, Appium, XCUITest, Espresso, or Detox.
Key authoring capabilities include:
Tests remain text-based and version-control-friendly, making them easy to review, maintain, and scale across teams.
Drizz executes tests in parallel across multiple devices and OS versions to reduce total runtime. Test plans distribute runs intelligently and support:
Execution works consistently across cloud device farms, local environments, and private infrastructure.
Every Drizz test run produces detailed, traceable execution artifacts:
When a failure occurs, Drizz generates AI-based failure reasoning that explains what was expected, what was observed, and why execution failed. Visual highlights and device logs are included automatically, reducing time spent digging through raw logs.
Drizz integrates directly into modern CI/CD pipelines through APIs and supports platforms such as:
Pipelines receive structured, machine-readable results, making Drizz suitable for automated release gating, regression enforcement, and continuous validation.
Drizz supports enterprise-grade security requirements, including:
This allows teams in finance, healthcare, and other sensitive domains to automate mobile testing without compromising data governance.
Drizz is built to handle the realities of modern mobile apps:
Because execution is visual and human-like, tests remain reliable even under high UI variance.
Drizz provides a single platform for authoring, executing, debugging, and scaling automated mobile tests across iOS and Android. By removing selector fragility and platform duplication, it allows teams to focus on validating real user behavior instead of maintaining brittle scripts.
For teams building fast-moving mobile apps, Drizz delivers stable end-to-end coverage, CI-ready execution, and clear failure insights—without the overhead of traditional automation stacks