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Docket

AI-powered web QA testing automation
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Role QA

Docket is an AI-powered platform designed to automate QA testing for web applications. It allows teams to create, run, and manage tests using natural language, eliminating the need for coding.

Key Features:

  • AI Agents for Web Testing: Utilizes AI to automate testing processes.
  • Natural Language Testing: Enables users to test applications using plain English, without requiring coding.
  • Intelligent Stability: Interacts visually with applications using a real browser, adapting to UI updates and eliminating reliance on DOM selectors, XPaths, or Playwright scripts.
  • Easy to Maintain: Adapts tests to UI changes, suggests new tests for evolving features, and continuously flags real bugs.
  • Vision-based AI: Understands the application visually and semantically, similar to a human.
  • Automated Test Execution: Handles the execution of tests.
  • Actionable Reports: Generates reports that provide insights into test results.

Use Cases:

  • Automating QA testing for web applications.
  • Creating and managing test suites without coding.
  • Detecting various types of bugs, including broken flows, payment errors, authentication problems, and unexpected behaviors.
  • Empowering any team member to create tests using natural language.

Benefits:

  • Saves Time: Empowers team members to create tests quickly using natural language, makes tests resilient, slashes maintenance through automatic updates, and handles test execution and reporting.
  • No Coding Required: Simplifies test creation and management for non-developers.
  • Resilient Tests: AI makes tests resilient to UI changes, reducing maintenance effort.
  • Continuous Bug Flagging: Automatically flags real bugs as they occur.
  • Comprehensive Bug Detection: Catches issues that impact users, categorizing them by severity.
  • Simplified Onboarding: Provides guided onboarding and initial test suite building by the Docket team.
  • Automates QA testing for web applications
  • Creates test cases using natural language input
  • Runs and manages tests for web applications
  • Interacts visually with applications, mimicking user behavior
  • Adapts tests to UI updates, ensuring test resilience
  • Suggests new tests for evolving features
  • Continuously flags real bugs
  • Understands applications visually and semantically, including objectives and test criteria
  • Detects user-facing issues such as broken flows, payment errors, authentication problems, and unexpected behaviors
  • Categorizes issues by severity, from critical failures to minor bugs
  • Generates actionable reports
  • Empowers team members to create tests without coding
  • Reduces maintenance efforts by automatically suggesting smart updates for tests
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