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Atai - Automated Testing AI

Atai uses Vision AI to generate automated test cases for web applications by interpreting natural language prompts

Instead of manually scripting tests, you describe what you want tested, including success criteria and edge cases, and the system builds executable test cases through its Sprucebot assistant. The technical architecture…

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Atai uses Vision AI to generate automated test cases for web applications by interpreting natural language prompts. Instead of manually scripting tests, you describe what you want tested, including success criteria and edge cases, and the system builds executable test cases through its Sprucebot assistant. The technical architecture runs on the Spruce Development Platform as a single Skill, built in TypeScript with websocket communication and MongoDB as the default database. Sprucebot operates as what they call an "Agent's Agent," functioning as a management layer above the generative AI rather than as a direct contributor.

The test generation pipeline works through parallel processing. You can create multiple test cases simultaneously from prompts, and the system converts these into reusable test steps that run without requiring AI on subsequent executions. This means zero cost reruns once a test's been built. Each test step captures a screenshot that's automatically saved to an S3 bucket, creating a visual record of execution. The Ride Alongs feature lets you watch tests build in real time and stop the process to adjust prompts if the AI's heading in the wrong direction.

Test maintenance happens through an automated repair function. When UI elements change in your application, the system can update affected tests rather than requiring manual rewrites. You can configure dummy data for variables and user credentials, which helps test different scenarios without exposing real information. The system handles unlimited test suites, cases, and runs, so there's no artificial cap on testing scope.

Integration points are limited but specific. The Vision AI component currently only works with OpenAI, despite documentation suggesting broader model support. Screenshot storage connects to AWS S3, either through your own bucket or Atai's infrastructure depending on which pricing tier you choose.

Two pricing options exist. The cloud subscription costs nineteen dollars monthly and includes the core testing features with managed infrastructure. The Download for Life version runs ninety nine dollars as a one-time purchase, adds full source code access, and lets you provide your own OpenAI API key and S3 storage. That version only runs on Mac. Both tiers include feature updates.

The primary technical limitation is the OpenAI dependency for Vision AI functionality. This creates a single point of failure if that API's unavailable and means you can't substitute alternative vision models regardless of pricing tier. The Mac-only restriction on the downloadable version limits deployment flexibility for teams on other operating systems. Real-time monitoring works across both versions, but the cloud subscription doesn't expose the underlying source code.

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Frequently asked

7 questions
Does Atai support automated testing without coding?
Atai generates test cases from natural language prompts rather than requiring manual scripting. You describe what needs testing, including success criteria and edge cases, and the Sprucebot assistant builds executable tests through Vision AI interpretation. The system converts these into reusable test steps that run repeatedly without AI involvement after initial creation. This approach reduces the technical barrier for test creation, though you'll still need to understand testing concepts like edge cases and success criteria to write effective prompts.
How much does Atai cost per month?
Atai offers two pricing models: a cloud subscription at nineteen dollars monthly or a one-time payment of ninety nine dollars for lifetime access. The cloud version includes managed infrastructure and all core testing features with unlimited suites, cases, and runs. The lifetime download adds full source code access and lets you provide your own OpenAI API key and S3 storage, but it's Mac only. Both tiers include feature updates.
Can Atai repair tests automatically when the UI changes?
Atai includes a test repair function that updates test cases when UI elements change in your application. Rather than manually rewriting affected tests, the system detects changes and adjusts the test steps accordingly. This maintenance feature works through the same Vision AI pipeline that generates initial tests. The repair process still requires some oversight to verify the updates match your testing requirements, particularly for significant interface redesigns.
What AI models does Atai work with for visual testing?
Atai currently only supports OpenAI for its Vision AI functionality, despite documentation suggesting broader model compatibility. This creates a dependency on OpenAI's API availability and pricing structure. The cloud subscription includes API access in the monthly fee, while the Download for Life version lets you provide your own OpenAI API key. There's no option to substitute alternative vision models like Claude or local open-source alternatives at this time.
How does Atai handle test data and user credentials?
Atai provides dummy data configuration for variables and user credentials, allowing you to test different scenarios without exposing real information. You can set up addresses, login credentials, and other variables that get injected during test execution. The system stores this configuration data in MongoDB by default and references it across multiple test runs. Screenshots from each test step get saved to AWS S3, either through Atai's infrastructure on the cloud plan or your own bucket with the downloadable version.
Can I watch Atai build tests in real time?
The Ride Alongs feature lets you monitor test creation as it happens through websocket communication between the interface and testing engine. You can observe how the Vision AI interprets your prompts and generates test steps in real time. If the system's heading in the wrong direction, you can stop the process and adjust your prompt before continuing. This real-time monitoring also works during test execution, showing you each step as it runs with corresponding screenshots saved to S3.
Is Atai suitable for testing mobile applications?
Atai focuses on web application testing through Vision AI interpretation of browser-based interfaces. There's no mobile app component or specific support for native iOS or Android application testing. The system uses browser automation to interact with web apps, capturing screenshots at each step for visual verification. Teams needing mobile testing would require a different tool, though you could potentially test mobile-responsive web interfaces through standard browser testing.

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