AI continues to influence software development and testing. While many of the testing platforms in the market advertise AI capabilities, the actual depth and reliability of those features can vary.
At AIMultiple, we utilize testing tools on a daily basis to determine if our 1,000+ web pages work as intended. Based on our experience, we choose the top AI-augmented testing tools. We’ve aimed to assess their claimed capabilities, areas of focus, and potential fit for different team needs. Follow the links on them to see our rationale.
| Software Best For | ||
|---|---|---|
1. | Testing complex or non-standard UIs across diverse systems | |
2. | Enterprise-scale cross-platform testing | |
3. | Mobile-heavy teams needing scriptless testing and visual validation | |
4. | Agile teams needing fast, low-maintenance UI test automation | |
5. | Large enterprises requiring resilient, end-to-end automation | |
| Show More (5) | ||
6. | Visual regression testing | |
7. | Growing teams needing flexible, all-in-one automation | |
8. | DevOps teams needing integrated UI, API, and performance testing | |
9. | Non-technical teams needing plain-English test creation at scale | |
10. | Technical teams wanting an open-source tool with AI flexibility | |
Top AI Software Testing Tools Compared
| Tool/Vendor | Reviews* | Employee Size | Pricing** |
|---|---|---|---|
Keysight Eggplant Test | 4.0 based on 54 reviews | 25000 | Pricing upon request |
Sauce Labs | 4.3 based on 319 reviews | 300 | Pricing upon request |
Perfecto by Perforce | 4.5 based on 103 reviews | 1600 | Starting at $83/mo, Pricing upon request for Enterprise Edition |
Tricentis Testim | 4.5 based on 49 reviews | 1500 | Pricing upon request |
Tricentis Tosca | 4.2 based on 74 reviews | 1500 | Pricing upon request |
Applitools Eyes | 4.5 based on 60 reviews | 120 | Pricing upon request |
Katalon Studio Platform | 4.3 based on 761 reviews | 300 | $2,199/yr per user |
mabl | 4.1 based on 94 reviews | 100 | Custom Quote(500 credits/mo base) |
Functionize | 4.7 based on 12 reviews | 140 | Pricing upon request |
Selenium | Open-source community project | Free |
* Reviews are based on review platforms such as Capterra and G2.
**All the tools offer a free trial on request.
Selection Criteria:
- The selected vendors should have 100+ employees
- If the tool is open-source, it should have 10k+ Stars on Github
Top AI Powered Testing Tools Analyzed
Keysight Eggplant Test
Eggplant, from Keysight, is an AI-based test automation tool using image recognition and model-based testing. It enables full-system testing by simulating user behavior across UI layers and systems that don’t offer direct access or APIs.
- Core AI Features: Computer vision for UI interaction, auto-generated test cases based on app models, adaptive element recognition, anomaly detection, and predictive UX analytics.
- Best for: Organizations with complex systems or non-standard UIs (e.g., legacy, medical devices, embedded UIs). Suitable for full user-journey testing across heterogeneous environments.
- Platforms: Cross-platform: web, mobile, desktop (Windows/macOS/Linux), screen-streamed UIs (via VNC/RDP), APIs. CI/CD integration included.
- Testing Focus: End-to-end functional testing with strong support for UI/UX validation, performance, and exploratory testing.
- Pricing: Commercial. Licensed per user or execution instance. Free trial or proof-of-concept available upon request.
Sauce Labs
Sauce Labs is a cloud-based testing platform known for its broad browser/device coverage and strong infrastructure. It now includes AI-powered capabilities, particularly through its acquisition of AutonomIQ and other integrations.
- Core AI Features: Converts natural language or recorded sessions into test cases. Includes AI for visual regression (via Screener), test failure clustering, and suite optimization based on code change impact.
- Best for: Enterprises with high test volumes across platforms, and teams adopting low-code or “citizen tester” models. Also suits teams already using Sauce Labs infrastructure.
- Platforms: Web, mobile (real and emulated devices), APIs. Supports Selenium, Appium, Cypress, Playwright, and more.
- Testing Focus: Cross-browser, mobile, and visual testing; some API and performance monitoring; test generation and analytics.
- Pricing: Commercial (Cloud). Subscription based on concurrency and feature tier. Free trial available; open-source access often provided.
Perfecto by Perforce
Perfecto is a cloud testing platform focused on web and mobile testing at scale. Its recent AI additions aim to support autonomous and scriptless test creation while ensuring visual and functional coverage.
- Core AI Features: AI Validation compares screenshots and UI states for visual/functional accuracy. Supports plain-language test descriptions and context-aware testing to minimize false failures. AI-driven analytics assist in failure diagnosis and regression planning.
- Best for: Enterprises testing at scale, especially mobile teams seeking scriptless automation with deep validation. Suitable for functional, performance, and visual QA in one platform.
- Platforms: Web browsers, real/simulated mobile devices (iOS/Android), APIs. Supports Selenium, Appium, hybrid/PWA apps, and integrates with CI/CD pipelines.
- Testing Focus: Functional, visual, performance, and regression testing across browsers and devices. Supports BDD and TDD workflows.
- Pricing: Commercial (Cloud). Annual subscriptions based on concurrency and device access. Free trial and demos available.
Tricentis Testim
Testim (now part of Tricentis) is an AI-powered test automation tool that accelerates web and mobile UI testing. It provides a low-code recorder for creating tests quickly and uses machine learning to maintain and stabilize them. Testim employs generative AI and ML algorithms to generate, execute, and auto-maintain test cases. This makes it especially useful in agile environments where tests need frequent updates.
- Core AI Features: Smart locators for self-healing tests, AI-based step suggestions, root-cause analysis, and GPT-style test generation through a “Copilot” assistant.
- Best for: Fast-moving development teams (especially JavaScript/TypeScript stacks) that need to create stable UI tests quickly and reduce maintenance effort. Includes special support for Salesforce and dynamic web apps.
- Platforms: Web (all major browsers), mobile web, and limited native mobile support. CI/CD integration and cloud execution supported.
- Testing Focus: Functional UI testing, including end-to-end user flows and cross-browser testing.
- Pricing: Commercial (Cloud/SaaS). Free community plan available. Full use requires custom-priced subscription based on test volume and parallel runs.
Tricentis Tosca
Tricentis Tosca is one of the leaders in enterprise test automation that incorporates AI and machine learning to extend its model-based approach. It covers a wide array of application types within a codeless framework. Recent features like Vision AI and Tosca AI Copilot bring intelligent test design and enhanced resilience.
- Core AI Features: Vision AI uses deep learning to visually recognize UI elements across platforms (including remote/Citrix). Tosca AI Copilot leverages LLMs to turn plain language into automated test cases. AI also powers risk-based prioritization.
- Best for: Large enterprises or complex IT environments needing codeless, resilient automation across technologies. Well-suited for continuous testing with strong governance and risk-based release decisions.
- Platforms: Web, Windows desktop, mobile (via Appium or Vision AI), APIs, enterprise platforms (SAP, Salesforce, Oracle). Can test Citrix/VDI sessions visually.
- Testing Focus: Functional and regression testing, business process testing. Also supports API, performance, and data integrity testing.
- Pricing: Commercial (Enterprise). Custom enterprise licensing based on users or nodes. Trial version available.
Applitools Eyes
Applitools Eyes is a commercial testing platform specialized in visual AI testing for UIs. It uses a computer vision AI to compare application screenshots and detect visual regressions. Applitools validates that UI elements render correctly across different browsers, devices, and screen sizes, greatly reducing false positives compared to pixel-by-pixel comparisons. It’s widely used in industries like e-commerce and finance where consistent UI/UX is critical.
- Core AI Features: Visual AI engine detects meaningful changes in layout, color, and content, trained on large UI datasets. Offers Ultrafast Grid for parallel visual rendering and AI-powered layout matching.
- Best for: Visual regression testing of web or mobile apps where look-and-feel must remain consistent. Great for QA teams focusing on pixel-perfect UI and user experience validation across multiple platforms.
- Platforms: Web and mobile applications (browser-based testing, native mobile via screenshot comparison). Can integrate with Selenium, Cypress, Playwright, etc.
- Testing Focus: Visual UI testing and regression validation. Also supports functional test assertions via its SDK.
- Pricing: Commercial SaaS. Free limited plan (one user, 100 visual checkpoints/month). Full plans are usage-based and require contacting Applitools.
Katalon Studio Platform
Katalon Studio is an automation platform offering low-code scripting with AI-enhanced features for test generation, maintenance, and validation. It balances ease of use with depth and flexibility, appealing to mid-sized and growing QA teams.
- Core AI Features: Self-healing locators, Smart XPath, visual testing via Applitools integration, GPT-based test generation, and analytics for flaky test detection and risk coverage.
- Best for: Teams needing a broad, out-of-the-box testing platform for web, mobile, API, and desktop apps. Well-suited for mid-sized teams scaling automation without full enterprise costs.
- Platforms: Web, mobile (via Appium), Windows desktop, APIs. Compatible with Windows, macOS, and Linux. Integrates with CI/CD and ALM tools.
- Testing Focus: Functional UI and API testing, regression testing, visual checks, and light load testing through integrations.
- Pricing: Freemium + commercial. Free tier for small projects. Paid plans start around $170/user/month. Enterprise packages available.
Mabl
Mabl is an AI-driven test automation platform that provides an all-in-one solution for functional, API, and performance testing. It emphasizes ease of use so that everyone on a dev team can contribute to test automation. The platform runs entirely in the cloud and integrates tightly with CI/CD pipelines.
- Core AI Features: ML detects UI changes and adapts tests. Auto-healing locators, anomaly detection (e.g., slow page loads or JS errors), AI-generated test suggestions, and visual regression built into test flows.
- Best for: Agile and DevOps teams seeking integrated testing for UI, API, and performance. Particularly useful in fast-changing web app environments.
- Platforms: Web applications, APIs, and hybrid/mobile web apps. Tests run on mabl’s cloud grid or on-prem.
- Testing Focus: Functional UI and API testing, visual testing, accessibility checks, and lightweight performance validation.
- Pricing: Commercial (Cloud). Usage-based enterprise pricing. Free trial available; occasional limited free tier.
Functionize
Functionize is an AI-powered test automation platform that automates the QA lifecycle from creation to execution. It uses machine learning and neural networks to generate and maintain tests, often calling its test bots “AI Test Agents.” Functionize allows tests to be written in plain English and emphasizes self-healing capabilities that reduce ongoing maintenance.
- Core AI Features: Deep learning engine analyzes user flows and DOM changes. Tests are created from user interactions and improved through reinforcement learning. Supports NLP-based plain-English test writing and root cause failure analysis.
- Best for: Enterprise QA teams looking for a codeless or low-code solution that non-developers (e.g., analysts, product owners) can use. Especially useful for testing complex web applications at scale.
- Platforms: Primarily web applications. Also supports API testing and basic mobile testing. Cloud-based, browser-accessible, and integrates with tools like Jenkins, Bamboo, and TeamCity.
- Testing Focus: End-to-end functional testing with emphasis on regression stability and cross-browser compatibility.
- Pricing: Commercial (Cloud). Custom pricing based on usage. Unlimited users/tests per plan. Free trial available.
Selenium
Selenium is a widely-used open-source browser automation framework. It enables cross-browser testing on Linux, macOS, and Windows, supporting all major browsers. While Selenium itself provides the core for web UI automation, recent developments integrate AI-driven plugins (such as self-healing locators and smart element identification) to improve test stability and maintenance.
- Core AI Features: By itself, Selenium isn’t AI-powered, but tools like Parasoft Selenic extend it with self-healing test execution and intelligent locator suggestions. AI add-ons analyze DOM changes and automatically update selectors to prevent flaky tests.
- Best for: Teams seeking a free, extensible automation solution with a large community, and willing to incorporate AI plugins for smarter test maintenance. Ideal when you need full control and integration into CI pipelines, and have resources to build on Selenium’s ecosystem.
- Platforms: Web applications (all modern browsers); supports various programming languages via WebDriver.
- Testing Focus: Functional UI testing (web). Can be extended to API or mobile with related projects, though primarily web UI.
- Pricing: Free and open source. AI extensions may come from commercial vendors or open projects; Selenium itself has no cost.
What Are AI-Powered Testing Tools?
These tools leverage AI or machine learning to automate and enhance software testing—from generating test cases to detecting bugs, optimizing coverage, and adapting to UI changes. You can think of them as smart assistants for QA teams or developers.
Core Features of AI Powered Testing Tools
| Feature | What It Does | Why It Matters |
|---|---|---|
Self-Healing Tests | Automatically updates test scripts when UI elements or structure change | Reduces test flakiness and maintenance in dynamic applications |
Smart Test Generation | Generates test cases using AI from code, user stories, or natural language | Speeds up test creation and improves test coverage |
Visual AI Testing | Detects visual or layout issues using intelligent image comparison | Identifies UI bugs that traditional testing might miss |
Natural Language Testing | Converts plain language into executable test cases | Allows non-technical team members to contribute to testing |
Anomaly Detection | Identifies irregular test results or failure patterns automatically | Uncovers hidden, non-obvious bugs |
Test Prioritization | Uses AI to determine which tests to run first based on risk and historical data | Optimizes test execution time and resource usage |
Coverage Analysis with AI | Maps tests intelligently to code coverage or functional areas | Highlights gaps in testing with greater accuracy |
Exploratory Testing Bots | Simulates real-user behaviors to uncover unexpected paths or edge cases | Enhances discovery of critical issues outside scripted flows |
Smart Element Locators | Tracks UI elements intelligently even when DOM or labels change | Creates more stable and maintainable UI tests |
CI/CD Integration | Seamlessly integrates with development pipelines | Enables continuous testing and faster release cycles |
Testing AI Software vs. AI-Powered Software Testing Tools
Testing AI Software
This refers to evaluating software that contains AI components, such as machine learning models or intelligent agents. The focus is on:
- Model performance (e.g., accuracy, precision, recall)
- Robustness and bias under varying conditions
- Explainability and compliance with regulations
- Integration of the AI model into the application
In this case, you’re testing the AI itself.
AI-Powered Software Testing Tools
These are tools that use AI techniques to enhance the software testing process. They’re applied to any kind of software and help by:
- Generating test cases automatically using NLP
- Detecting bugs and anomalies through intelligent code analysis
- Prioritizing tests and predicting high-risk areas
- Improving test coverage with data-driven insights
Here, AI is used as a tool to make testing smarter and more efficient, rather than being the thing under test.
What to pay attention to when choosing a testing tool
Each of these tools claim that they bring AI capabilities to software testing – not just as buzzwords but as proven features that reduce manual effort or catch issues humans might miss.
When selecting an AI-augmented testing tool, consider your team’s size, the types of applications under test, and integration needs:
- The larger vendors (Tricentis, Keysight, Sauce Labs, etc.) offer comprehensive solutions suited for enterprise-scale environments.
- Tools like Katalon or mabl cater to teams that want advanced features with slightly lower cost or complexity.
- For those preferring open-source, Selenium remains the foundation for many AI enhancements in testing, and its ecosystem of AI plugins continues to grow. By leveraging these AI-driven tools, QA teams can achieve faster test creation, more resilient test suites, and ultimately higher software quality with less maintenance overhead.
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