Update & TL;DR

This post was written while Forrester’s research on agentic and autonomous testing was still emerging. Since publication, Applitools has been included in The Forrester Wave: Autonomous Testing Platforms, Q4 2025. The perspective outlined below reflects how this shift has since been validated and formalized by independent industry analysts.

• Agentic automation shifts testing from brittle, script-driven execution to intelligent systems that adapt based on change, risk, and context.
• AI augments human intent rather than replacing QA teams, enabling people to focus on quality strategy, governance, and risk decisions.
• This model is increasingly shaping how autonomous testing platforms are evaluated in the market.

Forrester, a leading global research and advisory firm, identified a major turning point in software testing in its Autonomous Testing Platforms Landscape, Q3 2025. The research describes a shift from traditional scripted automation to AI-augmented systems that can learn, adapt, and act under human guidance. This shift signals the rise of agentic automation: intelligent systems that create, run, and optimize tests within defined boundaries.

As delivery cycles compress and complexity grows, quality and engineering leaders are redefining what effective testing means in practice. Agentic automation bridges human intent with machine-driven precision—transforming testing from a reactive maintenance task into a proactive engine for reliability, speed, and continuous improvement.

From Automation to Intelligence

Traditional automation accelerated execution but left teams managing brittle scripts and endless maintenance. AI-augmented testing changes that dynamic. These systems:

• Learn continuously from results and application change.
• Adapt test scope and prioritization based on business risk.
• Optimize coverage while maintaining human oversight.

The result is testing that behaves less like a checklist and more like a self-improving quality partner, one that scales reliability across every release.

The Three Business Values Driving This Shift

Forrester highlights three outcomes motivating investment in more intelligent testing systems:

1. Accelerate Time to Value – AI-driven generation and self-healing shorten feedback loops and reduce maintenance.
2. Reduce Strategic Risk – Risk-based orchestration and built-in governance connect quality metrics directly to business priorities.
3. Democratize Testing – Low-code authoring and natural-language interaction let non-developers participate in quality, closing skill gaps.

Agentic automation brings these together: human-directed intent, machine-driven efficiency, and transparent oversight.

How AI-Augmented Systems Complement Human Expertise

AI in testing works best as augmentation, not replacement. By handling repetitive execution and maintenance, intelligent systems free QA professionals to focus on:

• Defining risk and coverage strategy.
• Establishing governance frameworks that maintain trust.
• Collaborating earlier with product and development teams.

Agentic automation shifts QA leadership from running tests to steering quality outcomes.

The Role of Visual and Experience Validation

Intelligent automation depends on reliable validation signals. Traditional assertions can’t always capture what matters to real users: layout, accessibility, and experience consistency. 

Visual and experience validation fill that gap, giving AI-augmented systems context they can trust. When machines validate what users actually experience, teams gain both speed and confidence—without rigid pixel-level comparison.

Building Toward AI-Augmented Readiness

Forrester describes this as a maturing market: organizations are blending traditional automation with AI capabilities to move toward greater autonomy over time. QA leaders can start by:

1. Stabilizing automation foundations and addressing flakiness.
2. Adopting AI-assisted detection of UI and data changes.
3. Integrating experience-level validation for richer feedback.
4. Connecting quality analytics to business metrics for continuous improvement.

Each step builds the trust and data maturity required for agentic automation to succeed under human orchestration. As adoption increases, these maturity steps align with how leaders in the market are being evaluated on autonomous capabilities.

What QA Leaders Can Do Next

Forward-looking teams are already experimenting with:

• Adaptive execution that prioritizes tests dynamically.
• Governance dashboards linking coverage, risk, and compliance.
• Visual AI that helps systems understand real user impact.

The goal isn’t full autonomy—it’s AI-augmented confidence: testing that’s faster, smarter, and more inclusive across roles. Read the full report now.

The post Agentic Automation: Preparing QA Leaders for the Next Leap in Testing appeared first on AI-Powered End-to-End Testing | Applitools.

When testing needs to keep up with faster releases and growing complexity, the challenge isn’t just what to automate—it’s how fast you can create and validate reliable tests.

Code and no-code testing now work together to accelerate test creation, expand coverage, and deliver faster feedback across browsers and devices. By combining AI-assisted test creation with visual validation, you can go from setup to scale in hours instead of weeks.

A Smarter Way to Split Your Effort

High-performing teams balance two types of coverage:

• 20% custom flow tests: Focused, AI-assisted checks for your most critical user journeys
• 80% visual coverage: Full-page validation across browsers and devices with Visual AI

This approach ensures your key flows are verified with precision while everything else is continuously validated for layout, content, and visual consistency.

Full-Site Testing in Minutes

With Autonomous testing, you can point to any URL—or even a subfolder—and let AI do the rest. It crawls your sitemap, creates baselines, and runs cross-browser and cross-device tests automatically.

Setup takes minutes. You can schedule recurring tests daily or weekly, and catch both visual regressions and new pages as they appear.

During one large-scale migration, this approach tested more than 1,500 pages across five browsers and devices. Visual AI caught thousands of small layout changes, grouped them by pattern, and reduced the workload to just 10 unique issues after a single fix acceptance.

Depth Where It Matters

For the 20% that need fine-grained control, AI-assisted test authoring speeds up creation. You can describe each action in plain English—“add item to cart,” “verify success message,” or “fill out this form”—and the system turns those steps into repeatable tests.

AI assists by:

• Generating realistic test data
• Creating textual and visual assertions
• Masking sensitive fields automatically

The result: fast, accurate flows that non-coders and engineers can both maintain.

Reliable Execution, Every Time

Applitools’ deterministic LLM executes steps based on visual descriptions, not fragile locators or XPath. That means if a class name or element ID changes, the test still runs correctly.

It also eliminates token costs and flaky reruns common with external LLM agents, since all logic runs natively inside the platform.

Data Validation Included

End-to-end validation doesn’t stop at the UI. Within the same test, you can call APIs, capture responses, and assert that backend data matches what appears on screen.

Visual results, API responses, and data integrity checks all happen within a single low-code environment.

Reuse More, Maintain Less

Reusable test flows—like login, cleanup, or environment switching—save time and cut duplication. You can parameterize roles or URLs, then reuse those flows across staging, integration, and production.

That modular structure lets QA, developers, and product teams collaborate without reinventing the same tests for each environment.

The Fast Track to Full Coverage

By combining AI-assisted test creation with Visual AI validation, teams achieve:

• Broader coverage with less maintenance
• Faster release confidence
• Consistent, human-readable results

Whether you write code daily or prefer a visual test builder, this blended approach keeps quality high and bottlenecks low.

Try It Yourself

See how AI-assisted testing speeds up coverage for your own apps with Applitools Autonomous, or explore how Visual AI helps teams validate every page and device in minutes.

The post Accelerate Test Creation and Coverage with Code and No-Code Speed Runs appeared first on AI-Powered End-to-End Testing | Applitools.

Test automation is essential but often time-consuming. Writing and maintaining tests, generating reliable data, switching tools for API calls, and keeping everything aligned across environments can slow down even the best teams.

The latest updates to Applitools Autonomous, part of the broader Applitools Intelligent Testing Platform, introduce features that significantly reduce this overhead. From natural language test authoring to integrated API testing and deterministic execution, these additions help teams move faster with fewer manual steps. Alongside ongoing improvements to Applitools Eyes, the platform continues to evolve to support modern testing workflows at scale.

New Applitools Autonomous Highlights at a Glance:

• Natural language test creation powered by LLMs
• On-the-fly test data generation
• Enhanced API testing with visual builder
• Deterministic test execution (no LLMs at runtime)
• Upcoming support for mobile apps, IDE integration, and Storybook workflows

Natural Language Test Creation, Powered by LLMs

Instead of writing test steps manually or wrestling with locators, you can now describe your intent in plain English. Applitools Autonomous converts your input into executable test steps.

Autonomous interprets the instruction and adapts to your application’s context. Tests can be created by typing, recording interactions, or letting the system generate steps automatically. This approach makes test authoring more accessible, easier to maintain, and more readable across teams.

On-the-Fly Test Data Generation in Context

Need a specific persona, value range, or edge case? Autonomous now includes built-in test data generation. No external tools required.

Just describe what you need, a French fashion designer or a prime number over 1,000, and the platform generates valid, realistic data at runtime. Datasets are generated ahead of time, so test execution remains fast and predictable.

Enhanced API Testing in the Same Flow

You can now send and validate API requests directly within your test flow, using a Postman-style interface.

Author steps in several ways:

• Describe them in plain English
• Use raw HTTP or cURL
• Use the interactive UI builder

Once executed, responses can be inspected, variables extracted, and values asserted. UI, API, and visual checks all operate in a single environment—no tool switching needed.

Deterministic Execution Model for Reliable AI-Powered Tests

A standout feature of this release is the deterministic execution engine behind every test.

“You don’t need to be a prompt engineer or even a developer to scale automation. But when your test runs, it executes with the speed and reliability of code.”
— Adam Carmi, CTO and Co-founder of Applitools

Unlike some platforms that rely on live LLMs during execution—an approach that can be slow or unpredictable—Applitools separates test creation from test execution.

• LLMs assist during authoring and data generation.
• Test runs are powered by a proprietary deterministic model that ensures speed, stability, and consistent behavior.

This offers the flexibility of AI and the dependability of code, without trade-offs.

What’s Coming Next

Applitools continues to invest in both Autonomous and Eyes, with upcoming features focused on deepening cross-functional collaboration, improving performance, and expanding platform coverage.

For Applitools Autonomous:

• Native mobile app testing: Author and execute tests across devices and operating systems.
• Autonomous MCP server: Translate high-level test cases or BDD scenarios into full test flows.

For Applitools Eyes:

• Eyes MCP server: Move Visual AI directly into your workflow. Maintain, review, and run tests directly from your preferred IDE.
• Visual testing in Storybook: Approve changes directly where components are built.
• Performance improvements for component tests: Shorter pipelines and faster feedback loops.
• Figma collaboration enhancements: Sync designs and visual testing for consistent results.

Where Things Stand Now

Whether you’re building automation for the first time or looking to reduce the overhead of test maintenance, this release meets teams where they are. With natural language authoring, integrated data and API support, and a deterministic execution engine, Applitools helps teams reduce manual effort and work more confidently.

If you’re already using Applitools, now’s a great time to explore the latest features. If you’re just getting started, we invite you to see what’s possible with a free trial for you and your team.

The post Applitools Autonomous and Eyes: New AI Features, Better Execution, and What’s Next appeared first on AI-Powered End-to-End Testing | Applitools.

Building and maintaining automated tests has always been a challenge, especially when it comes to speed, coverage, and collaboration across technical and non-technical roles.

The release of Autonomous 2.2 helps teams reduce the time and effort needed to build and maintain reliable end-to-end tests. It combines LLM-generated test steps, automatic test data generation, built-in API validation, and visual comparisons across environments so that teams can find bugs earlier and release with more confidence.

API Step Builder: Visual API Testing, No Context Switching

Applitools Autonomous has always supported API testing, but with Autonomous 2.2, creating API tests is easier and more accessible than ever.

The new API Step Builder lets you build, run, debug, and update API calls with the UI, directly in your workflow—no code or external tools required.

• Paste in raw cURL or HTTP
• Translate into readable test steps
• Add headers, cookies, auth, body, and parameters visually
• Chain responses into UI steps via variables

Supported Features:

• Full HTTP method support: GET, POST, PUT, PATCH, DELETE, etc.
• Built-in request fields for headers, cookies, authorization, body, and URL params
• Dynamic variables: Ex. use {response.body.token} or {response.body.name} like variables in downstream steps
• Support for raw cURL or HTTP input with automatic translation to English-readable steps

Whether you’re preparing state, validating backend responses, or asserting API behavior, you can now do it all in one place—with a clean, intuitive UI that works just like the rest of Autonomous.

LLM Generated Test Steps: From Business Logic to Automation in Seconds

Write test steps the way you think—in plain English. With LLM Generated Test Steps, you can simply describe your business logic (e.g., “Select Ohio from the state dropdown menu”) and Autonomous will convert it into executable steps.

Let’s say you’re testing a job application page. Instead of clicking through each form field manually, you simply type:

Submit the form as an obscure Tolkien character

Autonomous analyzes the rendered page in real-time, understands the structure and semantics, and breaks down that one line into multiple actionable steps, such as:

• Typing the name and email address
• Selecting an appropriate option from dropdown menus
• Clicking the “Submit” button

The result? A complete, readable, and editable test created in seconds—no coding, no selectors, no extra UI to learn.

Perfect for:

• Speeding up test creation during sprints
• Empowering manual testers to create automated tests
• Eliminating writer’s block in test authoring

Join our Platform Pulse webinar on July 24 to see Autonomous 2.2 in action

Test Data Generation: Realistic Input with Zero Effort

Test coverage is only as good as the data behind it. Autonomous 2.2 introduces natural language–based test data generation that instantly produces realistic data at runtime, helping with edge case coverage and state variability.

Just say what you need:

Submit the form using random data for 90’s TV dads

Autonomous parses your request, uses LLMs to create diverse, high-quality data, and injects it directly into your test. Each run can generate fresh values—so no two executions are the same.

Cross-Environment Visual Comparisons: One Baseline, Many Environments

Ensuring parity across environments—staging vs. prod, dev vs. QA—or locales is critical. Parameterized visual baselines allow test engineers to define and run tests using variable data while still maintaining deterministic baseline comparison.

For example, you can run the same test in different plans—one with {env}=integration, another with {env}=staging—and compare visual differences across each environment without changing a single line of test logic.

• Parameters and datasets handled automatically
• Custom flows and URL List tests supported
• Visual baselines set per unique parameter set
• Abort prevention and value prompts to ensure test validity

Parameter handling is enforced at both test and plan levels—tests abort cleanly if required values are missing, ensuring reliable execution outcomes.

Tunneling Enhancements: Instant Feedback, Zero Guesswork

Tunneling just got easier and more reliable. With tunneling enhancements, Applitools Autonomous now includes improved diagnostics, real-time tunnel status, actionable error codes, and visibility for team admins—not just account owners

Users now get real-time diagnostics:

• Is the tunnel connected?
• Which hosts is it routing?
• Are there errors, and what do they mean?

Admins now get access to error codes, logs, host mapping, and verification checks—all without reaching out to support.

The Bottom Line

Applitools Autonomous 2.2 turns plain English into production-grade automation. Whether you’re testing UI, APIs, internal systems, or staging vs. production, it removes friction that slows QA teams down.

Explore the new features in the product documentation or dive into Autonomous with a free trial.

Quick Answers

The post Applitools Autonomous 2.2: AI-Driven Testing That Thinks Like You appeared first on AI-Powered End-to-End Testing | Applitools.

TL;DR — Applitools brings visual, functional, and autonomous testing together in a single AI-powered platform. Backed by 11+ years of refinement and a dataset of 4 billion real-world images, our Visual AI delivers unmatched accuracy and reliability for enterprise-grade software testing.

Testing today isn’t just about coverage—it’s about confidence, speed, and scaling quality across teams. Whether you’re a developer chasing faster feedback, a QA lead reducing maintenance overhead, or a product owner focused on release velocity, Applitools helps modern teams deliver software that looks right, works right, and evolves with ease.

Here’s how Visual, Functional, and Autonomous Testing all come together in one powerful platform.

Trusted Visual AI with Proven Accuracy

Applitools sets the standard in Visual Testing. Our Visual AI engine delivers 99.9999% accuracy, eliminating false positives and catching bugs others miss.

• 5.8x more efficient than pixel-based tools
• Detect both functional and visual bugs in a single test
• Works with all major frameworks: Selenium, Cypress, Playwright, and more

We didn’t just add AI—we’ve spent 11+ years perfecting it.

A Complete Platform for End-to-End Testing

Applitools goes far beyond screenshots. Our Intelligent Testing Platform includes Autonomous Test Creation, Visual Validation, Cross-Browser + Device Testing, and Accessibility Testing—all in one cloud-based solution.

• Run tests across browsers, devices, and screen sizes in parallel
• Built-in accessibility and compliance testing
• Fully scalable with enterprise-grade performance

Less Test Maintenance with Self-Healing, Smart Grouping & Predictive Analytics

Spend less time fixing broken tests and more time delivering value. Applitools minimizes test upkeep so your team can focus on building.

• Self-healing locators reduce test flakiness and manual updates
• Root cause analysis, smart grouping, and predictive analytics streamline debugging
• Tests automatically adapt as your UI evolves—no babysitting required

Collaborative Testing: How Developers, PMs, Designers & Marketers All Work Smarter with Applitools

Testing shouldn’t be a bottleneck—or limited to just QA. Applitools empowers developers, designers, product managers, and even marketers to collaborate with ease.

• Intuitive UI for reviewing results and managing baselines
• Seamless sharing of results and issue tracking
• Codeless and code-based authoring, no deep technical expertise needed

More than a Decade of AI Leadership

AI isn’t new to us—it’s the foundation of our platform. Unlike newer tools making AI promises, we’ve been building, training, and refining Visual AI to solve real testing challenges at scale for more than a decade.

• Mature, battle-tested AI that improves with scale
• Trusted by engineering teams at Microsoft, Tesla, Salesforce, eBay, and 400+ more
• Over 1 billion visual tests run with our platform

Seamless Integrations & Dev Experience

Great testing fits into your workflow—not the other way around. Our AI-powered test automation works with your tools, languages, and CI/CD pipelines to scale quality without slowing you down. Applitools integrates with:

• Every major framework: Selenium, Cypress, Playwright, Puppeteer, WebdriverIO
• CI/CD tools: GitHub Actions, Jenkins, GitLab, Azure DevOps
• SDKs for Java, JavaScript, Python, C#, and more

Whether you’re in code or no-code workflows, we plug into your stack and scale with you.

24/7 Support That Doesn’t Disappear

Whether you’re mid-sprint or troubleshooting a release, help is always within reach. Get expert guidance anytime—no hoops, no waiting.

• Around-the-clock global technical support
• Extensive documentation, how-tos, and real-time guidance
• Active community forum and dedicated Customer Success Managers (not just for enterprise)

Compare that to competitors with limited support, slow response times, or no dedicated resources unless you’re a top-tier customer.

Smart Investment, Real Value

Our pricing is flexible, predictable, and scales with your needs. You’ll see ROI fast:

• Save hours of test maintenance per sprint
• Eliminate manual bug hunts and false positives
• Deliver faster releases without compromising quality

Explore our current pricing structure, or speak with a testing specialist to build a package that’s right for your team.

“We reduced our testing time from days to hours. Applitools changed how we think about QA.”
— QA Lead, Global Retail Brand

Visual, Functional, and Autonomous Testing—The Applitools Advantage

We combine Visual AI, Autonomous Testing, and a developer-friendly platform into one powerful, scalable solution. With Applitools, your team gets:

• Smarter test creation
• Less maintenance
• Better collaboration
• Faster releases
• And trusted results every time

See What’s New with Applitools Autonomous and What’s Coming with Applitools Eyes

Ready to Test Smarter?

In a crowded automation landscape, it’s not enough to have “AI-powered” features. You need real results. With over a billion visual tests run and trusted by leading enterprises across industries, Applitools isn’t experimenting with AI—it’s already delivering.

Whether you’re starting fresh or looking to scale smarter, Applitools gives your team the tools to automate with confidence and speed.

Ready to see it in action? Start your free trial, book a personalized demo, or explore the platform today.

Applitools helps you test like it’s 2025. Join the world’s top teams already doing it.

The post Visual, Functional, and Autonomous Testing—All in One appeared first on AI-Powered End-to-End Testing | Applitools.

In today’s hyper-competitive environment, efficiency is king. Ensuring quality without slowing down development cycles is a critical priority for organizations looking to stay ahead. Hybrid test automation—combining both coded and no-code tools—has emerged as a game-changer. The smartest organizations are adopting this approach to reduce maintenance, accelerate releases, and empower cross-functional teams.

Applitools customer, Eric Terry, Senior Director of Quality Control at EVERSANA INTOUCH, underscored how a hybrid approach to test automation bridges skill gaps, enhances collaboration, and accelerates time-to-market. This article explores why a dual automation strategy isn’t just an IT initiative—it’s a business imperative.

The Business Risks of Choosing Just One Approach

When organizations lean too heavily on either coded or no-code automation, inefficiencies emerge. Coded automation offers flexibility and customization but demands highly skilled engineers, creating bottlenecks. No-code automation empowers non-developers but may lack depth for complex scenarios.

A hybrid strategy aligns technical capabilities with business needs, ensuring that:

• Routine tasks and UI-driven tests are handled by AI-powered no-code tools like Applitools Autonomous.
• Complex scenarios requiring deep customization leverage coded automation.
• Testing scales across diverse skill levels, unlocking greater efficiency.

Faster Releases, Higher Quality: A Competitive Advantage

Accelerating time-to-market while maintaining quality is a strategic advantage. Companies that integrate both coded and no-code automation realize efficiency gains, including:

• Reduced test maintenance: “We cut test maintenance by 40% by integrating AI-driven no-code automation,” Eric shared.
• Parallel execution: Running tests simultaneously across environments accelerates feedback loops.
• Smarter test selection: AI-powered tools identify the most critical tests, reducing regression cycles by up to 70%.

Collaboration as a Business Driver

Siloed workflows kill efficiency. When manual testers, automation engineers, and developers operate in isolation, knowledge gaps and redundancies increase risk.

Successful hybrid test automation programs:

• Encourage mentorship, where automation engineers guide manual testers.
• Align automated testing efforts with broader business goals.
• Leverage collaborative tools like Azure DevOps and Microsoft Teams for transparency.

Cost Savings: The Overlooked Benefit of Hybrid Automation

Cost efficiency isn’t just about reducing headcount; it’s about maximizing team output. Organizations that embrace a hybrid test automation approach realize:

• Lower hiring costs by enabling manual testers to contribute to automation efforts.
• Higher productivity by freeing developers from routine scripting.
• Broader adoption as business teams leverage no-code tools for non-QA applications, such as UI validation.

“Anytime that you can save some time, it has the potential to that into revenue,” Eric emphasized.

The No-Code Mindset Shift: A Leadership Imperative

Historically, tech leaders viewed no-code solutions as limited. But AI-driven platforms like Applitools are changing the game, allowing teams to scale automation without specialized expertise.

“I think we’ll start to see the uptick,” Eric predicted. “Tools are getting better, and they’re making automation more accessible than ever.”

See first-hand how Applitools can help your teams bridge skill gaps and scale test automation with a free trial.

Next Steps: Implementing a Hybrid Approach in Your Organization

For leaders looking to integrate both coded and no-code automation, consider these steps:

1. Assess your skill gaps – Identify where no-code solutions can bridge inefficiencies.
2. Start small, then scale – Pilot no-code automation for repetitive workflows.
3. Foster a whole-team quality mindset – Align teams around a shared automation vision.
4. Leverage AI-powered tools – Reduce maintenance while increasing test accuracy.

Future-Proof Your Testing Strategy

In the words of W. Edwards Deming, “It is not necessary to change. Survival is not mandatory.” Organizations that resist automation evolution risk falling behind. By strategically integrating both coded and no-code automation, businesses position themselves for faster innovation, higher quality, and stronger collaboration.

Hear more of EVERSANA’s story by watching Code or No-Code Tests? Why Top Teams Choose Both.

The post Bridging the Gap: Why Businesses Thrive with Hybrid Test Automation appeared first on AI-Powered End-to-End Testing | Applitools.

Testing modern software applications is becoming increasingly complex. With dynamic interfaces, personalized user experiences, and rapid deployment cycles, software engineering and QA leaders need efficient solutions that keep pace with development demands. While traditional test automation struggles to provide sufficient coverage and reliability, Applitools Autonomous emerges as a powerful, scalable solution that leverages no-code testing to achieve end-to-end testing workflows.

In this post, we’ll explore how integrating no-code and AI-driven end-to-end testing can solve common challenges, streamline processes, and empower QA teams to deliver high-quality applications faster.

The Problem with Traditional Testing

Many QA teams continue to rely on outdated methods that make it difficult to scale. Here are some key issues with conventional test automation approaches:

• Limited Test Coverage
  Traditional testing tools often fail to provide complete coverage. Most teams automate less than 20% of test cases, leaving large portions of applications vulnerable to defects.
• High Maintenance Overhead
  Scripts break with even minor UI updates, requiring significant manual effort to fix.
• False Positives
  Conventional pixel-based validation frequently flags irrelevant discrepancies, leading to wasted time and effort.

These limitations slow development cycles and increase costs—making it difficult to deliver the seamless, trustworthy experiences users expect.

The Promise of No-Code End-to-End Testing

Applitools Autonomous offers a fresh approach by combining no-code capabilities with AI-powered automation. This allows teams of all skill levels to create and maintain end-to-end tests with minimal effort while achieving broader test coverage and better accuracy.

Key Benefits of No-Code End-to-End Testing

• Simplified Test Creation: With no-code functionality, creating tests doesn’t require advanced coding skills. The Autonomous platform allows teams to write test flows in plain English or with an interactive browser, simplifying test authoring for non-technical users and engineers alike. A simple command like “Click the Login button” is all it takes to generate testing steps. 

• Effortless Scalability: Scalable end-to-end testing is easy with the Autonomous platform. Whether you’re testing small applications or large enterprise systems, the tool adjusts to your needs while maintaining consistency across devices, browsers, and resolutions.
• Self-Maintaining Tests: Tests created with Autonomous adapt automatically to UI changes, drastically minimizing maintenance. This ensures QA efforts remain efficient, even as your application evolves.
• AI-Driven Visual Validation: Applitools’ industry-leading Visual AI offers powerful visual testing capabilities. It intelligently identifies functional and visual changes in an application’s UI, avoiding false positives and ensuring a seamless user experience.
• Seamless Integration: Fully cloud-based and compatible with existing workflows, the Autonomous platform requires no local installations or complex configurations.
• API Testing Made Simple: For teams that need to validate backend and API responses alongside front-end testing, the Autonomous platform integrates API testing seamlessly into end-to-end workflows. 

Functional Testing in Action

The Autonomous platform simplifies every aspect of end-to-end testing. Testers can automate complex processes in minutes. For example, to validate workflows like contact forms or checkout processes, users can author functional tests in plain English (or even another language)—no coding required. This feature ensures testing of every critical business flow with precision. 

Why No-Code End-to-End Testing is a Game Changer

With built-in support for API testing, data-driven tests, and advanced visual validation, the platform ensures QA teams have everything they need to run comprehensive, scalable end-to-end tests. And by eliminating barriers to automation, the no-code approach lets QA teams focus on what truly matters—improving application quality and delivering a superior customer experience.

Major enterprises using Applitools’ Autonomous platform have already seen measurable benefits:

• Five-fold Increase in Test Coverage—extending seamless automation across devices and browsers.
• 35% More Defects Detected Early—preventing costly errors from reaching production.
• Hundreds of Hours Saved Per Release—thanks to minimized test maintenance and faster execution.

These results highlight the efficiency and precision that no-code end-to-end testing can bring to development cycles.

Unlock the Full Potential of End-to-End Testing

Applitools Autonomous is redefining how QA teams approach application testing. By combining no-code capabilities with advanced AI technologies, it offers a complete solution for comprehensive end-to-end testing across modern software applications.

Get a Closer Look

If you’re interested in seeing more, the full webinar is available on-demand and dives deeper into real-world use cases. Additionally, you can explore the platform firsthand with a free 14-day trial that allows you to test all the features on your own projects, giving your team the opportunity to experience the efficiency and accuracy it brings to end-to-end testing. Sign up for your free trial now.

The post No-Code End-to-End Testing with Applitools Autonomous appeared first on AI-Powered End-to-End Testing | Applitools.

Testing workflows just got an upgrade! Autonomous 2.1 simplifies end-to-end testing by offering faster test creation and maintenance while expanding mobile support. This release focuses on improving the efficiency and flexibility of your testing processes with features designed to simplify workflows, enhance modularity, and provide greater control.

Let’s explore the highlights of this release and how they can benefit your end-to-end testing. 

Key Features in Autonomous 2.1

Modular Test Design

Create a test once and reuse it across multiple workflows, eliminating the need to duplicate steps. This not only saves time but also ensures consistency and reduces the risk of errors. By enhancing reusability, this feature significantly accelerates test creation and simplifies maintenance, particularly for workflows shared across teams.

Use case example: Faster test authoring in Banking

For financial institutions, reusing a shared “User Login” test across workflows like “Fund Transfer,” “Loan Application,” and “Account Overview” simplifies test maintenance and ensures consistency. Autonomous 2.1 empowers teams to avoid recreating login steps for each flow, saving time and enhancing reliability.

Simplify Test Maintenance

Easily modularize your testing process by extracting repeated steps into standalone tests. This feature simplifies maintenance and improves by allowing your team to maintain one test and apply those updates to wherever you may be reusing extracted test flows. With fewer errors and a more streamlined test design, your team can focus on delivering quality faster.

Learn how to build no-code, autonomous end-to-end tests and explore some of these new features in our upcoming webinar, Building No-Code Autonomous End-End Tests

Record Assertions

Record assertions directly within your tests to ensure critical content is displayed accurately, without requiring manual scripting. This capability is especially valuable for localization efforts, enabling teams to validate translated content on multilingual websites. By reducing setup complexity, testers can achieve faster and more accurate validations.

Use case example: Maintain compliance with localization

On multilingual websites, recording assertions ensures translated content (e.g., terms and conditions, error messages) is displayed correctly. This is crucial for maintaining legal compliance and providing a seamless user experience in different languages.

Make Responsive Testing Easier

Ensure cross-device compatibility by configuring display viewport sizes—such as mobile, tablet, or even a custom size—directly in your custom flow tests. This ensures accurate validations across devices, making it ideal for e-commerce businesses and other industries prioritizing multi-device compatibility. Streamlining these configurations reduces setup time and ensures your users have a seamless experience across platforms and devices.

Pro tip: While Applitools Ultrafast Grid lets you run the same test across multiple browsers and devices, we recommend creating separate tests for specific screen sizes when unique screen elements, like a hamburger menu, appear only on certain viewports.

Flexibility in Test Configuration

We’ve decoupled the application and plan from individual tests, offering greater flexibility and a more intuitive workflow for configuring tests independently. You can now run tests ad-hoc—even trigger test execution via the REST API—and configure run properties like parameters, browsers, devices, and concurrency limits. This change not only enhances the user experience but also lays the groundwork for advanced capabilities in future releases, ensuring a scalable and adaptable testing environment.

And There’s More…

Autonomous 2.1 lets you navigate more intuitively with an updated interface reflecting application hierarchy and copy tests across applications while preserving reusable flows. For added security, sensitive test data like passwords is now encrypted and masked, and TOTP support for 2FA enables secure workflows with Time-Based One-Time Passwords.

Try Autonomous 2.1 for Free With Your Team

With Autonomous 2.1, you’ll experience faster test creation and simplified maintenance, particularly for workflows reused across multiple teams or applications. This release represents a significant step toward more efficient, scalable, and user-friendly testing processes.

Try out Autonomous 2.1 for free with your team and see how it can revolutionize your testing efforts.

The post Introducing Autonomous 2.1: Speed Up Testing with Modular Test Design appeared first on AI-Powered End-to-End Testing | Applitools.

Efficient software testing plays a crucial role in the digital financial industry, where customer trust relies on reliable systems and smooth user experiences. AI-powered tools are revolutionizing software testing for online banking. Learn how Applitools’ Autonomous Testing Platform, an AI-driven testing solution, can boost efficiency and ensure seamless functionality for digital banking platforms.

AI-Powered Testing for Visual Verification

Modern interfaces are becoming more dynamic, making software testing more challenging than ever. Applitools uses AI-powered end-to-end testing to deliver accurate, human-like visual validation. With this advanced approach, teams can easily detect visual bugs, handle dynamic content, and solve multi-device rendering issues. Compared to traditional testing tools, Applitools’ AI testing solution offers a faster, more reliable way to ensure seamless user experiences across all platforms.

Visual AI “sees” applications as a human would, identifying not just design inconsistencies, but functional issues within complex environments. This human-eye accuracy is especially critical for financial applications, where misdisplayed data or minor UI errors can compromise user trust.

Visual Verification with AI gives QA teams:

• Precise identification of visual bugs, such as misaligned content or missing elements.
• Compatibility across a range of devices, screen sizes, and browsers.
• Reduced false positives, ensuring only actionable defects are flagged.

Challenges in Automated Testing for Financial Apps

Some of the key challenges QA teams face in the financial services industry include testing data-heavy dashboards, personalized user experiences, and meeting strict compliance requirements. QA teams also navigate the complexity of testing constantly changing data, such as account balances and transactions, while ensuring seamless functionality across multiple devices and screen sizes. These unique testing challenges highlight the importance of effective QA processes in delivering reliable, user-friendly financial services.

Adding to these complexities are regulatory requirements, like accessibility compliance mandated by guidelines such as the European Accessibility Act. Traditional tools often fall short in dynamically adapting to such changes, leading to increased bottlenecks.

Common Obstacles Faced by QA Teams:

• Exponential growth in test scenarios due to dynamic UI states.
• Maintaining coverage amid rapid deployment cycles.
• Lacking tools to validate compliance and localization needs.

The Role of Visual AI and Autonomous in Testing

Applitools’ Visual AI is transforming the way teams approach UI testing. Developed with 11 years of research and development, this powerful technology compares both visual elements and DOM structure to deliver comprehensive UI validation. Key features like automated baselining and self-healing tests make maintaining tests easier, especially during frequent code updates or UI changes.

The Autonomous platform takes Visual AI testing to the next level by integrating it with end-to-end test workflows. The platform simplifies visual, functional, API, and accessibility testing. With Autonomous, teams can automate testing, schedule tests, validate results, and efficiently manage issues—all from a user-friendly interface.

Features of Visual AI & Testing with Autonomous:

• Self-healing capabilities to adapt tests to UI updates without manual adjustments.
• Natural language authoring that allows easy collaboration between technical and non-technical team members.
• Supports functional flows like login processes while ensuring personalized data fields meet validation patterns.

Efficiency and Coverage Improvements

A top US bank improved testing efficacy using Applitools Autonomous. By adopting Visual AI and scaling to test its entire ecosystem, the bank achieved:

• 5x Test Coverage Expansion across all devices and browsers.
• 35% More Defects Caught weekly within earlier production stages.
• Up to 999 Hours Saved Per Release by reducing manual test generation and maintenance efforts.

This expansive coverage allowed the team to uncover bugs that would otherwise have been missed, delivering higher-quality software quicker.

Visit the event archive to see more of the case study and watch the full session on-demand.

Security and Integration Features

Data security and adaptiveness in distinct environments are primary concerns in financial testing. The webinar addressed how Applitools ensures client protection with private cloud implementations and a secure architecture for test data management. The platform seamlessly integrates with firewalls and various development ecosystems, making it an ideal choice regardless of organizational infrastructure.

Ensuring Data Privacy and Flexibility:

• Test data secured using encryption and private cloud options.
• Compatible with diverse environments, both behind firewalls and in SaaS architectures.
• Allows scalability without compromising compliance adherence.

Strengthen Financial Application Testing

AI-assisted testing is helping overcome the hurdles posed by traditional testing. By integrating Visual AI with a broad end-to-end testing workflow, financial institutions can drastically enhance their QA practices. More importantly, these improvements do not require trade-offs between coverage, speed, and accuracy.

If you’re ready to elevate your testing game, particularly in high-demand sectors like online banking, platforms like Autonomous present an opportunity you can’t afford to miss.

Explore the full webinar on-demand or reach out to learn how Applitools Autonomous can streamline your QA efforts and ensure the flawless delivery of digital experiences.

The post End-to-End Testing Solutions for Online Banking Software Applications appeared first on AI-Powered End-to-End Testing | Applitools.

Nowadays companies are investing a lot of money into QA efforts to increase the quality of the software products being released. However, the traditional QA method is not only time-consuming and ineffective but also often disappointing in its results. This triggers inefficiency, additional expenses, and ultimately, higher risk for delivering the end product with visual or functional issues. The pressure to release frequently and stay ahead of the competition can lead to insufficient testing resulting in bugs and other issues that negatively affect the user experience.

Today’s users require software that has functional capabilities, better graphics and is easier to use. To meet these expectations, a lot of testing needs to be done for the application’s visuals and user interface. This is because as the software development life cycle progresses the testing teams are put under pressure as development teams release products faster.

In this blog, we will explore the challenges of testing modern applications and how these challenges can be addressed by utilizing the AI-powered testing tool, Applitools Autonomous.

You will see detailed examples of how Applitools Autnonmous addresses different types of testing like functional, visual, and API testing.

Challenges In Testing Modern Applications

Below are some of the challenges we often face while testing modern applications.

Too Many Scenarios

Modern applications are highly complex, with hundreds of end-to-end scenarios that need to be tested across a vast array of screens, devices, and browsers. 

Too Many Screens & Devices

In modern applications, users access digital content on a wide variety of devices, browsers, and screen sizes, each with its own unique characteristics. Manually verifying that an application looks and functions correctly across all these environments is nearly impossible without automated assistance. Traditional testing methods cannot scale to meet this demand, often resulting in inconsistent user experiences and missed visual bugs.

Constant UI Changes

In dynamic development environments, user interfaces (UIs) are constantly evolving. Even minor changes to the UI can require updates to test scripts. This constant maintenance burden can slow down the development process and lead to outdated or ineffective tests.

Different Skill Sets

Teams often consist of members with varying technical skills, leading to the use of different tools and approaches to testing. This creates silos within the organization, where engineers and non-technical testers might not collaborate effectively. So far we have seen the challenges in testing modern applications.

Types of Testing Using Applitools Autonomous

Applitools Autonomous, powered by Applitools’ proven Visual AI, offers a game-changing solution that allows teams to automate and streamline testing across various dimensions. In this blog, we’ll explore the types of testing you can perform using Applitools Autonomous and how it simplifies the testing process.

Full Website Testing

One of the key features of Applitools Autonomous is its ability to conduct a Full Website Test with minimal effort. Simply by entering your website’s URL, Autonomous crawls the sitemap and automatically creates a test suite covering every web application page.

Benefits of Full Website Testing:

• Comprehensive Test Coverage: Automatically creates tests that span the entire site.
• Visual AI Validation: Screenshots are taken and compared in real time to identify visual discrepancies.
• Technical Issues Detection: Automatically detects issues like HTTP errors, timeouts, and structural changes (added/removed pages).
• Cross-Environment Consistency: Ensures your website renders consistently across all environments.

With just a URL input, Applitools Autonomous handles the heavy lifting of testing, giving teams complete coverage across all environments.

URL List Testing

If you don’t need to test your entire website, or if you want to focus on specific pages, Applitools offers URL List Testing. This allows you to upload a list of important URLs that you want to validate across different browsers and devices.

Benefits of URL List Testing:

• Custom Test Plans: Create targeted test plans for critical or specific parts of your website.
• Visual and Functional Validation: Detect visual differences, server errors, and loading failures.
• Quick Setup: Simply upload a CSV, XLS, or sitemap file to initiate the testing process.

This method gives you granular control over which parts of your web application are tested, ensuring the most important areas receive detailed attention.

Custom Flow Testing

For complex workflows, Applitools Autonomous offers Custom Flow Testing, which allows you to simulate end-user actions across your site. For example, you can test user journeys like logging in, adding items to a cart, and checking out — with every action captured step by step.

Benefits of Custom Flow Testing:

• Workflow Validation: Ensure that user flows, from login to checkout, function correctly.
• Real-Time Interaction: Record steps in an interactive browser, which are automatically converted into plain English for easy review.
• Dynamic Content Testing: Easily handle personalized content and dynamic data using Visual AI, ensuring accuracy even with fluctuating data.

Custom Flow Testing is ideal for complex, multi-step processes, such as eCommerce workflows or user registration flows.

Cross-Browser and Device Testing

Cross-browser testing can be a significant bottleneck in the development process, but Applitools Autonomous eliminates this pain point. It replicates browsers in seconds, cutting down the time required for Cross-Browser and Device Testing by up to 90%.

Benefits of Cross-Browser Testing:

• Fast Replication: Save time by reducing cross-browser testing time by up to 90%.
• Consistent Testing: Validate how your site performs across multiple browsers and devices with minimal effort.

By reducing the time spent on browser replication, teams can focus on identifying and resolving any browser-specific issues faster.

API Testing

Applitools Autonomous doesn’t just stop at visual testing—it also enables API Testing. You can initiate HTTP requests directly in your tests, manage application states, and store responses for use in later test steps.

Benefits of API Testing:

• Seamless Integration: Initiate API calls and validate responses as part of your testing workflow.
• State Management: Manage application states before or after the UI flow without complex logic.

API Testing combined with visual validation ensures that your web app’s functionality works correctly and efficiently across the board.

Example of Testing Using Applitools Autonomous

In the below section, you will see the different types of testing you can perform using Applitools Autonomous.

Full Website Testing

In full website testing, users provide the URL they want to scan and specify the test environments where they want to execute the scan. Additionally, users can set optional settings such as a maximum number of URLs and select a custom flow to run before the test. Once these steps are completed, the website is ready to be scanned.

For example, let’s look at the site https://dan.sandbox.applitools.com/e-commerce.

Steps to Create a Full Website Test

1. Navigate to Test Management
   • In the navigation bar, go to Test management > Tests.
   • Click Create a new test and then select Create a full website test.

2. Enter the URL: In the URL field, input the website homepage in the format https://www.example.com/.
   
   Alternatively, you can enter the full path to the sitemap or a sub-directory, such as https://dan.sandbox.applitools.com/e-commerce/type/books.
   
   If a sub-directory is specified, Autonomous will use the sitemap in the root directory to identify URLs within the sub-directory. If the sub-directory has its own sitemap, provide the full path to that sitemap.

3. Default Test Environments: The test will use the below environments by default, each defining a browser, operating system, and screen size. You can click on an environment to remove it from the test. After creating the test, you can add or modify environments in the test plan.
   • Chromium, Linux, 1440 x 900
   • Chromium, Linux, 360 x 780
   • Microsoft Edge, Windows, 1080 x 1920
4. Optional Settings:
   • Set the Limit: To limit the number of URLs in the initial test run, click on Optional settings and select Set a max number of URLs to include in the test, then enter the desired number of URLs.
     
     This helps the first test run quickly and get preliminary results. This setting only applies to the first run; future runs will include all URLs in the sitemap, with new URLs marked as “New” in the results.
     
     Note: If you have a trial account, note that there is a limit to the number of tests you can include in a full website test.
   • Custom Flow and Authentication: To enter basic authentication or run a custom flow before each URL opens, click on Optional settings and choose Select a custom flow to run before this test.
     
     You can select Basic authentication and enter a username and password. This adds an authentication-encoded string in each URL, ensuring the username and password are included.
5. Click the Next Button: Once the above steps are completed, your website is ready to be scanned.
   
   Once you click the Next button, Autonomous can then develop baseline data at every screen on the website. These are the initial test images which are in most cases used to identify changes in subsequent test iterations. The maximum count of baselines to be generated is obtained by multiplying the count of URLs in the test by the count of environments.
   
   You can see baseline data is created for every screen in the screenshot below.

6. Execute the Test: Once the baselines have been created, click Run Test. Autonomous will run the test to create a checkpoint for each screen and then compare the checkpoint to the baseline determining any issues and if the screen has changed.
7. Execution report: Once the execution is complete, click Review Results to view all test results on the Results page.
   
   Clicking on the Results tab on the left side lets you see the details of the Pass and Fail test cases. In the screenshot, we can see one test case failed. When we tried to find out the reason it was discovered that this test case was failing because of the 404 error screenshot attached below.
   
   This lets us automatically find technical issues, pages that were added or removed from the website, visual disparities, and unexpected alterations on any of the pages.

URL List Test

A URL list test allows users to create a list of URLs with combinations that will be used for testing. This is especially useful when you have no sitemap, want to crawl specific URLs in your domain, or need to crawl URLs of other domains too.

While setting up your URL list test you should create a file with the URL to be tested and check if all of them are properly loaded. The list should be in CSV, XLS, TXT, or a sitemap .xml file format. The sitemap .xml should only contain the URLs you are going to test—not all URLs on your site.

Steps to Create a URL List Test in Applitools Autonomous

1. Navigate to Test Management: In the navigation bar go to Test Management > Tests.
2. Create a New Test: Click on Create a new test and select the URL list from the dropdown.

3. Enter Test Details:
   • Test Name: Enter a name for the test. This will appear in the list of tests.
   • Description: (Optional) Add a description of the test.
   • Application: Select the application the test should be associated with. Every test must be linked to an application. If you have an existing full website test or another test linked to the same application, associate this test accordingly. For more details, refer to the “Applications” section in the platform documentation.
   • Plan: Choose the associated plans. Plans define the schedule, environment, and test parameters. A test can belong to multiple plans, and the list of available plans will depend on the application associated with the test. For more details, refer to the “Plans” section.

4. Run a Flow Before Each Step (Optional): If you need to perform an action (such as entering authentication credentials or closing a popup) before each step, click Select a flow to run before the screen URLs. For more details, see the “Flow to Run Before Steps” section of the documentation.
5. Import URLs: Click Import URL list to upload a comma-separated text file, CSV, or XML file with the list of URLs you want to test.
   
   Alternatively, enter a single URL and click Add URL to manually add URLs one by one.
6. Set Match Level: The default match level for all URLs is set to Strict. If you want to change the match level for a particular URL, click the area to the right of the URL and select the desired match level from the dropdown.
7. Advanced Settings: To configure additional advanced settings for the test or individual URLs, refer to the Advanced Test Settings section for further customization options.
8. Finalize and Run: Once the configuration is complete, choose one of the following actions:
   • Create (or Update): Saves the test to the associated plans without running it.
   • Create & run > Create & run test: Saves and runs the test as a single instance without executing any other tests in the plan. You will be asked to choose a plan to determine the test environments. You can view the results on the Results page, and the test will be listed as “Run without a plan.”
   • Create & run > Create test & run plan: Saves the test and executes all associated plans, including all tests within those plans. Results can be viewed on the Results or Plans pages.

Custom Flow Testing

The Autonomous Applitools Custom Flow Test is an intelligent and streamlined way to automate end-to-end testing of specific workflows on a website. This feature enables testers to design a sequence of actions or user scenarios, for instance, login, adding items to a shopping cart, and navigating to a checkout page while at the same time, every action is recorded for evaluation purposes.

Key Components of Autonomous Custom Flow Test

• Interactive Browser: Autonomous provides an interactive Chrome-based browser that allows users to manually interact with the application. Testers can perform actions like clicking buttons, filling in forms, scrolling, or navigating between pages.
  
  The interactive browser records every action in real time and automatically translates them into test steps, simplifying the test creation process.

• User Action Steps: Go to Test Management > Tests in the navigation bar. Click on Create a new test and select Custom Flow from the dropdown.
  
  
  The below screen will then open when you click on Custom flow:
  
  
  In the screenshot below, you can see the recorded steps resulting from using the interactive browser:
  
  
  Actions performed in the browser, such as clicking or typing, are captured as plain English commands. These steps can be easily added, modified, or deleted.
  
  For instance, a step might read: “Enter “standard_user” as username”, Enter “secret_sauce” as password, and  “Click on the Login button.” Autonomous also offers auto-suggestions to ensure that the commands are valid, reducing the risk of errors and speeding up the creation of test scripts.
• UI Validation Steps: Visual validation is a core feature of the Autonomous test. At key points in the workflow, Autonomous takes screenshots to validate the user interface. These visual checkpoints help ensure that there are no unexpected visual changes (known as visual diffs) between test runs.
  
  Screenshots act as baselines and provide insights into the accuracy of the UI across different devices and resolutions.
  
  In the below screenshot, you can see that after logging into the application we are visually verifying the page.
  

Use Cases of Custom Flow Testing

Let’s take the example of https://www.saucedemo.com/ where a user may perform the actions below. 

• Login into the application with Username and Password
• Click on Add to cart against the product “Sauce Labs Backpack”
• After adding the item to the cart place the order 
• Finally, verify the confirmation message

For the given use case, we have two options to write the test script:

• Manually add user actions: This involves explicitly defining each user action in the script or code.
• Record the steps: This option allows the user’s interactions to be captured automatically by recording the steps as they are performed.

Both approaches can be utilized based on the specific requirement or convenience. In the screenshot below you can see the above use case is recorded.

Debug or Modify a Test

In the screenshot below you can see we can perform various actions by clicking on any existing action. The user has clicked on an action (likely Step 7, clicking a button with a CSS selector) that reveals a dropdown menu providing options such as:

• Run next steps: Executes the remaining steps in the test from the selected point onward.
• Set as current step: Marks the selected step as the starting point for future test execution.
• Run until here: Runs the test from the beginning up to the selected step, stopping just before it.
• View execution result: Displays the outcome of the selected step, including logs or screenshots, if applicable.
• Edit step: Allows modification of the selected step, such as changing input values or actions.
• Duplicate: Creates a copy of the selected step, useful for repeating actions with minor adjustments.

Previewing Test Steps in the Interactive Browser

This approach saves time during the test construction process because it enables previewing of the test steps as one proceeds with the development of the test script in an interactive browser.

When in an interactive browser running a test there is an option where you get to see the screen as it was before each step was performed and after.

How to Preview a Test Step

Place the mouse pointer over an icon before one or several particular test steps, and you will be provided with a thumbnail of the screen. For a more detailed view of the screen, navigate to the icon on the toolbar to open the full-size picture preview.

On the top of the preview window, you can find information such as the step number, command run, and its status—pass or fail.

Use the icons behind the worksample Click on Action to see the screen before the step and Outcome to see the screen after the step. When viewing the action window the element clicked on during the step is highlighted in pink.

Running the Test from the Start

To start the test from the first step you can just press the “Run” button or “Rerun test from start” which is above the list of the steps.

Once started, Autonomous will go through each step one by one while taking a screenshot of the application at every step. If the browser is not already connected, then the Run will also create the connection before the test is carried out. This way it can be ensured all the steps are performed correctly and also shows the status of a particular step.

• icon indicates that the step was successful
• icon shows that Autonomous couldn’t process the step, and the test will stop at that point without continuing further

During the test, you can pause or stop it at any time by clicking the Pause or Stop buttons.

API Test

Applitools Autonomous is not limited to functional and visual testing. It can also be used for API automation. Supporting all CRUD operations, it allows you to execute standard HTTP actions like GET, POST, PUT, and DELETE in your tests. This adds versatility to its API testing capabilities.

Autonomous also enables you to validate test operations that cannot be confirmed via the UI, such as verifying form submissions through backend records. Additionally, it ensures backend APIs expose the correct endpoints, function as expected, and return proper responses, headers, and cookies.

GET Requests

For GET requests let’s take an example of https://gorest.co.in/

Navigate to Test Management: In the navigation bar, go to Test Management > Tests. Click on Create a new test and select the Custom Flow from the dropdown.

Use Case 1: API Response With Positive Validation

Objective: Hit the API endpoint and verify the following:

• response.status (HTTP status code)
• response.body[0].title (Title of the first object in the response body)
• response.body[0].id (ID of the first object in the response body)

In the screenshot below you can see all the above validations have passed.

You can then hover over a response value to view options to copy the following information to the clipboard:

• Copy Property Value: Copies the actual value from the response, e.g.,{“id“:157394,”user_id“:7436337,”title“:”Vulgus enim alius comis et officia.”,”body“:”Tametsi suscipit reiciendis. “}
• Copy Property Accessor: Copies the accessor to retrieve the value programmatically, e.g., {response.body.0}
• Copy Property Checkpoints: Copies a formatted checkpoint to use in a test, e.g., verify that {response.body.0.id} is 157394 and verify that {response.body.0.user_id} is 7436337

Use Case 2: API Response With Negative Validation

Objective: Hit the API endpoint and verify the following:

• response.status (HTTP status code)
• response.body[0].title (Title of the first object in the response body)
• response.body[0].id (ID of the first object in the response body)

In the screenshot below you can see title validation is failing when we are verifying the title of the first object.

POST Requests

For POST requests let’s take an example of the site https://reqres.in/api/users

Use Case 1: API Response With Creating User

Objective: Hit the API endpoint https://reqres.in/api/users

• Pass the body in the request 

{

    “name”: “morpheus”,

    “job”: “leader”

}

POST https://reqres.in/api/users with header “Content-Type: applitcation/json” and header “Accept: application/json” and body ‘{     “name”: “morpheus”,     “job”: “leader” }’

• Verify the status 201

In the screenshot below you can see test case is passed and a new record is created with the status “201”.

Use Case 2: API Response With Registering User – successful

Objective: Hit the API endpoint https://reqres.inhttps//reqres.in/api/register

• Pass the body in the request 

{

 “email”: “eve.holt@reqres.in”, 

“password”: “pistol” 

}

POST to https://reqres.in/api/register with header “Content-Type: application/json” and body ‘{     “email”: “eve.holt@reqres.in”,     “password”: “pistol” }’

• Verify the status 200
• Verify ‘token’ is generated

Summary

In the rapidly evolving software industry, companies are pouring resources into quality assurance to ensure smooth product launches. However, traditional QA methods are often too slow, costly, and ineffective, which can lead to bugs, poor user experiences, and product defects.

However, AI-powered tools like Applitools Autonomous offer a powerful solution to these challenges. By automating functional, visual, and API testing, Applitools enhances testing efficiency and effectiveness, ensuring higher-quality releases while reducing the risks of user dissatisfaction.

About the Author

Kailash Pathak (Applitools Ambassador | Cypress Ambassador)

Senior QA Lead Manager with over 15 years of experience in QA engineering and automation. Kailash holds certifications including PMI-ACP®, ITIL®, PRINCE2 Practitioner®, ISTQB, and AWS (CFL).

As an active speaker and workshop conductor, Kailash shares his expertise through blogs on platforms like Medium, Dzone, LambdaTest, Talent500, The Test Tribe, and his personal site https://qaautomationlabs.com/

The post Comprehensive Testing with Applitools Autonomous: A Deep Dive appeared first on AI-Powered End-to-End Testing | Applitools.

The demand for high-quality software in the fast-paced tech environment has never been greater. Since companies spend more on QA to make sure their products are not buggy and look good, traditional testing is not enough. Test cases are manual and take time, automation also has its limits, especially when it comes to user interfaces with complex and fast-changing elements. AI-driven software testing comes into play, in this case revolutionizing the way quality is ensured.

Applitools Autonomous is a leading AI-based testing platform that reduces the time and effort required to create, maintain, and run tests. The most effective way of using it is as a tool in visual and functional testing and a valid scalable solution for contemporary applications.

In this blog, we will explore AI-driven testing, what are the challenges of testing modern applications, and how an AI-powered testing tool, like Applitools Autonomous, is helpful in testing applications.

About AI-Driven Testing

The phrase “AI-driven testing” describes the usage of artificial intelligence techniques to help the software testing process. Organizations can leverage machine learning, natural language processing, and other types of artificial intelligence technologies to streamline their testing processes, saving time and resources and optimizing the delivery of high-quality software.

AI-Driven Testing Key Concepts

Automation of Test Creation

The manual script writing of traditional testing can be slow, and prone to errors. This is automated with AI-driven testing in which test cases are automatically generated from the application’s structure, user flows, and user behaviors. For example, Applitools Autonomous can scan an application’s sitemap and spin up comprehensive test suites without you having to do any manual input.

Visual Validation

Visual validation is the strong point of AI-driven testing, making sure the UI functions and looks good on every device and browser. AI can also detect visual discrepancies and changes to the UI that certainly wouldn’t be picked up by standard testing methods.

Dynamic Test Maintenance

Test cases inevitably grow outdated, and applications are always in flux—that can mean a lot of work to keep them up to date. Testing platforms driven by artificial intelligence automatically adapt the tests to complement changes within the application’s UI or functionality. It reduces the burden of maintenance for QA teams and keeps testing relevant and efficient.

Predictive Analytics

Because AI can analyze historical test data to predict potential problem areas in an application, teams can concentrate their testing resources on applications’ high-risk areas. This predictive ability helps an organization’s resources get allocated better and cuts down on the likelihood of critical bugs slipping through the cracks.

Natural Language Processing (NLP)

NLP is often part of AI-driven testing tools that enable users to create test cases based on plain language text. This feature makes it easier to test so that non-technical team members can collaborate on testing with technical team members.

Challenges In Testing Modern Applications

Below are some of the challenges that we often face while testing modern applications.

Too Many Scenarios

Modern applications are highly complex, with hundreds of end-to-end scenarios that need to be tested across a vast array of screens, devices, and browsers. 

Too Many Screens & Devices

In Modern applications, users access digital content on a wide variety of devices, browsers, and screen sizes, each with its own unique characteristics. Manually verifying that an application looks and functions correctly across all these environments is nearly impossible without automated assistance. Traditional testing methods cannot scale to meet this demand, often resulting in inconsistent user experiences and missed visual bugs.

Constant UI Changes

In dynamic development environments, user interfaces (UIs) are constantly evolving. Even minor changes to the UI can require updates to test scripts. This constant maintenance burden can slow down the development process and lead to outdated or ineffective tests.

Different Skill Sets

Teams often consist of members with varying technical skills, leading to the use of different tools and approaches to testing. This creates silos within the organization, where engineers and non-technical testers might not collaborate effectively.

So far we have seen the challenges in testing modern applications. Now let’s see how we can leverage AI to take over the heavy lifting in testing using Applitools Autonomous.

About Applitools Autonomous

Before we dive into Applitools Autonomous, it’s important to understand what autonomous testing is. Let’s use a car analogy to differentiate between manual, automated, and autonomous testing.

Manual testing is like driving a car with a manual transmission, where the driver is fully engaged in controlling the accelerator, brake, and clutch. Every action requires constant attention and input from the driver.

Automated testing, on the other hand, is like driving a car with an automatic transmission. While the clutch is handled automatically, the driver still needs to manage the accelerator, brake, steering wheel, etc. It reduces the manual effort but still requires active engagement.

Autonomous testing is like a self-driving car. Here, you just input your destination, and the car takes over, driving you to your destination while you focus on other things. Similarly, autonomous testing aims to eliminate human intervention, but we’re not fully there just yet. Just like self-driving cars are still evolving, fully autonomous testing is a future goal we are working towards.

Applitools Autonomous With AI

Applitools Autonomous revolutionizes the testing process by bringing the intelligence and precision of top QA professionals to an unprecedented scale through AI. 

As the first autonomous testing platform, Applitools Autonomous lightens the load on your development team by automating the entire testing lifecycle—from test creation and execution to maintenance and reporting.

Applitools Autonomous is an autonomous testing platform designed to automate and enhance the entire software testing process.

Here’s a breakdown of how it works:

• Automated Test Creation: Applitools Autonomous intelligently scans your application’s sitemap to automatically generate comprehensive test cases for every URL. This ensures that your application is thoroughly tested across all pages, eliminating the need for manual test script writing.

• AI-Driven Visual Assertions: The platform applies advanced visual AI to monitor and track changes at both functional and visual levels. Whether it’s a minor UI adjustment or a significant functional update, Applitools Autonomous ensures that any deviation is detected and addressed to maintain the highest standards of user experience.

• Continuous and Scalable Testing: With Applitools Autonomous, your tests can be seamlessly integrated into your CI/CD pipeline or scheduled to run periodically. This means your application is continuously tested, providing real-time feedback and enabling faster, more reliable releases. The AI-driven approach ensures scalability, making it possible to manage even the most complex applications with ease.

• Dynamic Test Updates: As your application evolves, the platform automatically updates tests to reflect changes in the UI or functionality. This reduces the need for manual maintenance and keeps your tests relevant and effective.
• Test Results Analysis: After running tests, the platform provides detailed reports, highlighting any issues found. These reports include screenshots, logs, and other relevant data to make it easier to diagnose and fix problems.

Types of Testing with Applitools Autonomous

Applitools Autonomous allows for different types of testing, all powered by its Visual AI:

• Full Website Testing: Enter your website URL, and Applitools autonomously crawls and tests every page for both functional and visual consistency.
• Functional Testing: Ensure that user flows work as expected with AI validating both the logic and appearance of your UI elements.
• Visual Testing: Identify visual differences and UI discrepancies across devices to provide a consistent user experience.
• Regression Testing: Compare current test runs with historical data to catch any regressions introduced by new changes.
• API Testing: Automate API validation to ensure backend services work seamlessly with the UI.

Key Benefits of Applitools Autonomous and My Thoughts

Applitools Autonomous has some strong features that make it worth looking into if you’re trying to streamline your testing process. Here’s my take on the key benefits:

Automatic Test Case Generation

One thing I found impressive is how Applitools generates test cases automatically by crawling your site’s sitemap. It saves a lot of manual work, which can really make a difference when you’re managing multiple test scenarios. The fact that you can describe workflows in plain English is a nice touch, making it easier for non-technical folks to get involved.

Faster Test Creation

The speed of test creation is something that stood out to me. Applitools Autonomous claims to generate tests up to 10 times faster, and in practice, it does seem significantly quicker than traditional methods. The ability to instantly validate thousands of elements and group similar errors together really helps to keep things moving efficiently.

AI-Driven UI Validation

Visual AI is one of the more compelling features. It does a great job of catching both visual and functional issues across different devices and browsers. This kind of coverage is essential if you’re dealing with a variety of platforms and need consistent performance and appearance across all of them.

Proactive Bug Detection

I also like how you can schedule tests or integrate them into a CI/CD pipeline. This means you can catch bugs early on, which is always a plus. Dealing with issues earlier in the process tends to save time and money down the line, and the proactive nature of this feature is a big win.

Generative AI for Expanded Coverage

By scanning the root domain, Applitools builds out Visual AI scans for each page. This feature is really useful for getting broader test coverage without much manual effort, something I think teams dealing with large-scale applications will appreciate.

NLP Test Builder

The Natural Language Processing (NLP) test builder is another feature that caught my eye. It allows anyone on the team to create tests by describing steps in plain English, which makes the tool accessible to non-technical members. It definitely lowers the barrier to collaboration, which is always a plus.

Faster Test Execution

Running tests at scale can be a pain, but Applitools Autonomous handles this well with its DOM replication technology. It cuts down on test execution time, which makes it easier to test across multiple browsers and devices efficiently.

Automated Test Maintenance

One of the more practical benefits is automated test maintenance. As your UI changes, the tests update themselves, which minimizes the need for manual updates. This reduces the ongoing workload and keeps your tests relevant without constant tweaking.

Dashboards and Insights

Lastly, the dashboard is quite intuitive. It consolidates all your test results and provides a clear breakdown, making it easier to analyze outcomes and resolve issues quickly. The actionable insights offered by Applitools help speed up decision-making and improve overall application quality.

Applications Suited for Testing Using Applitools Autonomous

Applitools Autonomous is designed to enhance the testing process across a wide variety of applications, making it an ideal choice for different sectors and use cases. Here are some of the types of applications that are particularly well-suited for testing with Applitools Autonomous:

• Web Applications
  Applitools Autonomous can help web applications in particular, and those with dynamic user interfaces in general, in a big way. What’s more, this platform is capable of carrying out full website tests, to ensure that not only every page on the website is working as anticipated, but the brand appears as intended across all browsers and devices.
  
  Example: A social media platform like Facebook requires constant updates to its features and UI in some way. By automating testing, we can be sure that the user interface stays consistent across browsers and devices—e.g. post creation, messaging, and notifications—with Applitools.
• Mobile Applications
  Because users have access to the same application on different mobile devices, testing responsive design, testing functionality or both are absolutely necessary. The main thing that Applitools Autonomous shines at is validating mobile apps so that they always have a clear, smooth experience across various screen sizes and orientations.
  
  Example: Instagram is dependent on visual appearance and relies on mobile applications. Applitools Autonomous is able to validate that images load correctly (or the user interface adapts to different devices) and that the app’s functionality is still in check after an update.
• Ecommerce Platforms
  Ecommerce applications need to be very well tested to make sure a user can smoothly navigate around, make purchases, and get correct information. The Applitools Autonomous engine can be expanded to verify the visual aspects of the platform and the functional flows (e.g. shopping cart, payment process…) as well.
  
  Example: There are several features that Amazon has to validate: product search, shopping cart functionality, and payment process. Using Applitools we can address these problems by automating the visual and functional testing of all elements to make sure that everything does work seamlessly and the users all get a consistent user experience across different devices.
• SaaS Products
  Examples of software as a service (SaaS) applications are constantly delivering new features and enhancements. Autonomous from Applitools helps you make sure existing functionality does not break while validating the user interface against any visual differences in a regression backlog.
  
  Example: CRM tools such as Salesforce are always busy introducing new features. Applitools Autonomous can run regression tests that run automatically to verify that new updates do not break existing functionalities and that the user interface is still friendly for the user.
• Healthcare Applications
  In the healthcare sector, applications must be user-friendly and reliable. Applitools Autonomous can validate that interfaces are intuitive and that crucial functionalities, such as patient records or appointment scheduling, work without issues.
  
  Example: Applitools Autonomous ensures that crucial functionalities, such as appointment scheduling and medical record access, are tested for both usability and visual consistency.

Conclusion

In a rapidly evolving tech landscape, the need for high-quality software has become paramount. As traditional testing methods struggle to keep pace with the increasing complexity of applications, AI-driven testing solutions like Applitools Autonomous emerge as game-changers. This platform not only streamlines the testing process through automation but also enhances the quality of software by leveraging advanced AI techniques.

About the Author

Kailash Pathak (Applitools Ambassador | Cypress Ambassador)

Senior QA Lead Manager with over 15 years of experience in QA engineering and automation. Kailash holds certifications including PMI-ACP®, ITIL®, PRINCE2 Practitioner®, ISTQB, and AWS (CFL).

As an active speaker and workshop conductor, he shares his expertise through blogs on platforms like Medium, Dzone, LambdaTest, Talent500, The Test Tribe, and his personal site https://qaautomationlabs.com/

The post AI-Driven Testing with Applitools Autonomous: What You Need to Know appeared first on AI-Powered End-to-End Testing | Applitools.

Modern ecommerce applications are more than digital storefronts. They’re immersive, complex experiences designed to captivate and engage customers—customers that spent well over $1 trillion in 2024 (over $220 billion during seasonal shopping surges).

Ecommerce applications are now multifaceted ecosystems that require high reliability, fast updates, and seamless performance across devices. With features like multi-step checkout, dynamic promotions, and personalized recommendations, these applications present a unique challenge for testing teams: ensuring consistent quality in an environment of constant change.

From adaptive content testing to streamlined cross-platform validations, AI-powered testing helps software test and development teams deliver personalized, high-quality experiences to their shoppers.

Step 1: Addressing the Core Challenges in Ecommerce Application Testing

To understand how AI-powered testing can enhance quality, we first need to think about the primary complexities in ecommerce applications:

• Dynamic Content
  Promotions, recommendations, and A/B testing create a dynamic landscape where content changes rapidly, which can lead to issues in test reliability.
• Multifaceted User Journeys
  A typical user flow can include browsing, filtering products, adding items to a cart, and various checkout steps, each with variations like promotional codes and payment methods.
• Cross-Platform Consistency
  Ensuring a consistent experience across mobile, desktop, and tablet adds another layer of complexity, requiring cross-device and cross-browser validations to prevent regressions. 

These challenges make e-commerce application testing labor-intensive, especially for teams relying on traditional methods–manual or automated.

Step 2: Leveraging AI to Manage Complexity in Ecommerce Testing

Let’s explore how AI-powered testing can help address the common pain points of ecommerce application testing:

Autonomous Testing for Comprehensive Flow Coverage

Autonomous testing provides broad page coverage by automatically creating visual tests for each page from a single URL. For more complex, critical user journeys, custom flow tests blend human oversight with AI assistance to ensure thorough validation.

AI tools, like Applitools Autonomous, can learn the structure of complex user journeys—like multi-step checkouts or specific promo code applications—and adapt to new scenarios with minimal manual intervention. For developers, this means reduced time writing scripts and a faster feedback loop, as the AI detects critical paths and validates user interactions autonomously.

Test Tip: Use autonomous testing to cover frequently changing paths like checkout, where many variations (promo codes, payment methods) need to be validated with each update.

Visual AI for Dynamic Content Testing

AI-powered visual testing focuses on meaningful changes, helping to identify only the differences that impact user experience. Traditional test automation often flags minor layout shifts that don’t affect usability, leading to unnecessary noise. On the other hand, Visual AI detects layout issues that matter, minimizing false positives and simplifying testing for high-variance content.

Use Cases: Visual AI is particularly effective in handling promotional banners, personalized ads, and product recommendations. It ensures that these elements render correctly without producing redundant alerts.

Cross-Browser and Cross-Device Testing

Ensuring consistency across devices and browsers is crucial in ecommerce. Testing with a tool, teams can validate both functionality and appearance across multiple environments in parallel, enabling broader test coverage with significantly reduced runtime.

Tool Tip: For each release, use the Ultrafast Grid to run tests across all targeted browsers and devices simultaneously. By testing in parallel, you can catch visual and functional discrepancies early, ensuring consistent experiences across your audience’s preferred devices.

AI for Personalized and Edge Case Testing

AI-powered testing can adapt to personalized and localized content variations. This allows you to verify account-based and user-specific scenarios, like tailored recommendations, language translation, and geolocation-based offers. The AI dynamically generates test scenarios for real-world edge cases, validating content presentation, accuracy, and functionality across users.

A/B Testing and Experimentation

AI testing tools can run tests alongside A/B experiments to quickly validate different scenarios and identify potential issues without extensive setup or downtime. Integrated into CI/CD pipelines, AI can seamlessly support experimentation, allowing you to test new features or changes with agility.

Test Tip: Use AI for A/B testing by validating that both variations display correctly and function as expected. This can streamline experiment verification and minimize risk.

Accessibility Compliance with AI

Accessibility is key to ensuring inclusivity for all of your shoppers when you consider that 4.4% of the world’s population is colorblind. Even more shoppers have contrast sensitivity issues (we don’t know about you but some of us are just getting old). AI-driven testing identifies accessibility issues early, such as missing alt text, improper color contrast, and navigation difficulties. With accessibility testing integrated into automated pipelines, developers can confidently meet compliance requirements while optimizing the experience for users with disabilities.

Step 3: Applying AI Testing in Real-World Ecommerce Scenarios

Ensuring that every scenario receives accurate validation across all paths and user types can be hard but your team can quickly improve test coverage by integrating AI into the below scenarios:

• Multi-Path Checkout Testing
  AI testing tools validate complex checkout flows, including various payment methods, promo codes, and cart adjustments. This reduces the risk of abandoned carts due to broken checkout paths and ensures seamless user experiences.
• Product Filtering and Sorting
  Filtering and sorting are essential for user navigation. AI testing validates the functionality and accuracy of filters by testing different combinations. This ensures the results match user criteria and display correctly.
• Personalized Content Validation
  Personalized recommendations, banners, and product listings are critical for user engagement. AI-powered testing verifies that these elements display correctly based on user data, ensuring consistency without disrupting the layout.

Step 4: Getting Started with AI-Powered Testing

To maximize the benefits of AI in ecommerce application testing, you can follow these best practices:

• Integrate AI into your CI/CD Pipeline
  Embedding AI testing into the CI/CD process ensures that every change undergoes rigorous testing before reaching production. This allows for fast iteration and high-quality releases.
• Prioritize Dynamic and High-Risk Areas
  Focus AI testing on paths that involve dynamic content, personalized features, and checkout flows. These areas tend to have the highest variance and the most critical impact on user experience.
• Leverage Parallel Testing
  Run cross-platform tests in parallel to streamline testing cycles and get immediate insights into how changes impact various devices and browsers.
• Use AI for Regression and Smoke Tests
  Routine regression and smoke testing can become resource-intensive. By automating these with AI, you free up resources for more complex testing, ensuring each release is stable.

To Wrap Up…

As AI becomes an integral part of the testing process you can shift your focus toward building new features and enhancing shopper experiences by maintaining a high standard of quality:

• Reduced Manual Work and Faster Releases
  By automating repetitive tasks and handling edge cases, AI-powered testing allows QA teams to focus on high-impact scenarios, reducing time to market.
• Increased Test Coverage and Accuracy
  AI’s ability to adapt to dynamic content and complex scenarios broadens test coverage and increases the accuracy of results, ultimately reducing production issues.
• Adaptability to Ongoing Changes
  AI-powered testing lets ecommerce sites handle constant updates and seasonal changes without extensive reconfiguration so that shoppers have a seamless experience.

AI-powered testing is now an essential strategy for ecommerce test and dev teams to meet user expectations and stay competitive. You can try out these strategic steps with a free trial of Applitools Autonomous.

The post A Guide to AI-Powered Ecommerce Application Testing appeared first on AI-Powered End-to-End Testing | Applitools.