AI-Powered Mobile Test Automation for iOS, Android & API
Tired of spending more time investigating test failures than fixing actual bugs? Want regression checks to run consistently on every build while staying in control over the process?
We connect our AI-driven mobile test automation framework to your iOS or Android apps and their APIs to make that happen. AI agents take on much of the routine test creation and maintenance, giving your team more time to build features and ship them more often with the same quality.
Pilot on one app
Test the framework on one of your apps before committing
Live demo
See the framework run on a real device
Open-source stack
Reduced risk of vendor lock-in
Android, iOS & API
One suite for all three
Why manual mobile regression stops scaling
When you release monthly and the app has a handful of critical flows, manual mobile regression testing works fine. Even if senior developers spend a few hours checking existing features, the release still goes out on time. But when you ship every week or two and the regression list grows every sprint, repeating checks by hand slows development and delivery. An increasing share of your development budget also goes to work you have to replicate with the next release.
How different test automation solutions manage updates
You can automate mobile testing in different ways. Traditional automation gives you code ownership, but engineers write and fix every test by hand. Self-healing test automation tools are faster to set up and adjust to UI changes without interrupting test execution. Our framework pairs suite ownership with AI agents that write and repair tests, validating every fix along the way.
Capability
AI-operated framework
Traditional automation
Self-healing and record and playback tools
Understanding a new app
AI maps app flows
Engineers map flows and define scenarios
Depends on the tool; may record actions or require manual configuration
Initial suite
Generates a baseline suite for review
Engineers write test scripts
Records steps or generates scripts
Failure investigation
Classifies failures, gathers evidence, and looks for likely causes
Engineers inspect logs and reproduce failures
Capabilities vary by tool
Locator repair
Repairs locators, reruns tests, verifies fixes, and explains changes
Engineers update locators and rerun affected tests
May adjust locators when supported
Flaky tests
Investigates timing issues and escalates unresolved failures
Engineers investigate and fix the cause
May retry or stabilize tests
Cloud integration
Provider switching via configuration
Depends on framework and pipeline setup
Depends on tool integrations
Code ownership
Readable, version-controlled code in your repository
Usually code in your repository
Code access and ownership depend on the tool
Time and effort comparisons are illustrative. Actual results depend on app complexity, test scope, and environment.
What automated mobile testing changes for your team
Measuring test automation value by the hours saved on the first run alone is short-sighted. The bigger returns come from test reusability you can apply to dozens or hundreds of future builds with little rework. When the suite remains reliable and easy to maintain, the value of automated mobile testing compounds over time. Here’s what that means for your team.
Faster releases with consistent quality
With continuous testing, every code update triggers your test suite across Android, iOS, and the API. If a critical flow breaks, your team gets an alert with evidence to help investigate the cause while the change is still fresh. You get shorter fix cycles and fewer surprises close to release.
More coverage with the same team
Team members can describe a test scenario in plain English. AI agents turn that description into a working script, and an engineer reviews it before adding to the suite. This way, scaling coverage becomes a matter of a review, not a scripting task.
Faster defect resolution
When a test catches a real defect, your team receives a report with screenshots, the UI hierarchies, and device logs attached. Developers get everything they need to start troubleshooting immediately, cutting down the time spent recreating bugs to find the cause.
A more predictable testing budget
After setup, the suite needs only part-time upkeep that scales with your app’s size and release frequency. The suite can run as often as your deployment pipeline demands without affecting your payroll. This makes it easier to track test automation ROI over time.
More time for product work
Free from regression tasks, developers can concentrate on delivering new features and improving existing functionality. Testers gain more time to expand coverage, and managers can return to delivery planning and team priorities.
Test knowledge your team can reuse
Your suite lives in your repository in plain-English Gherkin scenarios understandable by developers and product owners. The shared record of what gets tested simplifies future test automation maintenance and reduces reliance on the people who originally wrote the scripts.
Find out how much of your regression can run without people
What our mobile test automation framework does
Getting the first tests to pass is the easy part of mobile test automation. The true challenge is maintaining one suite that covers two platforms, an API, and several environments while mobile app development continues. Without a shared approach, platform-specific logic and frequent app changes can produce duplicated scripts and recurring maintenance.
Our test automation framework brings these parts together, blending AI tools with a production-grade automation stack. Teams usually have to choose between two things. With both in one project, your team can generate tests, investigate failures, repair supported issues, and maintain the suite in one place.
Plain-English test scenarios
Following behavior-driven development (BDD), tests describe what the app should do from the user’s point of view. They are defined using Gherkin, a format of Given, When, and Then steps, and Cucumber test automation turns scenarios into executable tests.
UI and API testing in one suite
The framework combines mobile test automation with Appium and API test automation with RestAssured in one Maven project. This lets you validate front-end user interactions alongside the underlying API logic, especially when UI flows are tied to backend responses.
Runs across devices and environments
Real device testing and cloud device testing on LambdaTest or BrowserStack use the same scenarios across development, staging, and production.
Built for reliable test execution
The framework validates its configuration before each run, reruns only failed tests, and saves failure artifacts like screenshots and device logs to a shareable Allure report.
Plugs into your CI/CD
Built as a standard Java-based Maven project, the suite integrates natively into your existing CI/CD test automation pipeline, be it Jenkins, Azure DevOps, or GitLab.
TECH STACK
Cucumber
RestAssured
Appium
Maven
Allure
AI QA automation that keeps your mobile tests working
AI that runs on every build must make financial sense beyond the engineering time it saves. That’s why the framework matches tasks to the right level of reasoning. Lightweight models read logs and parse reports, saving high-reasoning LLMs for code generation and architecture decisions. This agentic testing setup keeps AI test automation costs predictable as execution volume grows under normal use.
From app package to working regression suite
Once you provide your Android or iOS build, our engineers run the AI agents. They map your app’s structure, identify UI elements, and generate scenarios alongside automation code that powers them. At the end, you receive a baseline regression suite ready for your team’s review. The steps are the same for Android and iOS test automation.
01
Add the app
APK or IPA file
02
Run /ingest-app
Starts the analysis
03
AI maps the app
Screens, elements, locators
04
Run /generate-tests
Scenarios and test code
05
Review the suite
Engineers check the baseline
06
Run anywhere
Local or cloud devices
Three commands that reduce manual QA
/ingest-app
Maps the screens, UI elements, identifiers, and the most stable way to locate each element.
Replaces manual app exploration and reverse engineering
/generate-tests
Creates readable Gherkin scenarios and the automation code behind them.
Replaces much of the manual test scripting and setup
/retry-failures
Reruns failed tests, investigates likely causes, and attempts verified repairs.
Reduces repetitive debugging and test maintenance
Every failure is analyzed
Traditional test reports show that something failed, not why. A lot of debugging time goes into test triage, especially when flaky tests and real defects look the same in a report. Agents that perform test failure analysis to identify likely causes and decide what to do next reduce triage and diagnosis overhead. Depending on their findings, they repair the test, rerun it, or pass the issue to your team as a bug report or another format that suits your workflow.
Changed UI element or locator
Compare the current UI with the expected element and update the locator if the match can be verified.
Timing issue or flaky test
Inspect execution evidence and retry, adjusting synchronization only when the evidence supports the cause.
Application or API regression
Flag the behavior for investigation with complete evidence.
Device or environment issue
Check available logs and execution context, then retry or report the issue for human review.
Nothing is guessed. Every decision is backed by evidence collected during the run.
Verified repairs on top of self-healing
Self-healing tests can adapt to an updated UI locator when an app’s interface changes. But a passing test doesn’t prove the root cause was fixed. Our framework includes an extra verification step to separate verified repairs from unresolved failures that only appear fixed. After examining the failure, the agent attempts a repair when appropriate and reruns the test to check the result. If the test still fails or the cause remains uncertain, the agent hands over the issue with the collected evidence.
Failure detected
Repair attempted
Retest and verify
What we automate and what stays with your testers
You can’t automate every stage of the mobile testing strategy at once. Trusting AI to write a test before you know how a feature should work can lock in incorrect logic as the expected result. Testers still need to explore new functionality first and define how it should work. Once the feature is stable, you can move those checks to the automated regression suite, and from that point, our framework takes over.
Automated by AI
- Regression flows across iOS and Android
- Automated smoke testing on every build
- API checks behind the UI
- Evidence collection
- Repeatable runs on real and cloud devices
Led by your testers
- Exploratory testing
- First pass on brand-new feature
- Visual and UX judgment
- Accessibility and localization review
- Acceptance checks for specific scenarios
- Release sign-off
Our framework automates functional regression across the UI and API. Need performance or security testing, too? Explore our QA & software testing services
Test the framework on your app before you commit
A focused pilot on one of your apps and its core user flows lets you see what mobile test automation can realistically do for your team. The pilot gives you a working regression suite, an understanding of how much can be automated, and what it would take to broaden coverage to other apps.
The pilot
We configure the framework for one app, agree on the critical user workflows to cover, and build a working suite that fits into your current processes. At the end, you get an assessment of what automation can and cannot do.
What you keep
The suite stays in your repository, integrates with your build pipeline, and produces Allure reports your team can share with stakeholders. You can run it on every build, whether you continue with our mobile test automation services or maintain it yourselves.
After the pilot
Once the pilot proves its value, we can configure the framework for the rest of your apps, reusing its core automation setup. This reduces setup time for each new app and accelerates test coverage expansion.
What we need from you to get started
- App and environment access
- Required credentials and accounts
- Device and network access
Pilot – Prove the approach on one app.
Reuse – Extend the framework to other apps.
Standardize – Build a shared approach across teams.
Prefer a demo first?
Want to see the framework in action before committing to a pilot? We’ll demonstrate the workflow from test creation and execution on Android and iOS devices to result reporting in Allure using a sample app.
Who benefits most from AI-operated test automation
The framework is especially valuable for product companies and enterprises that release mobile apps regularly and want to automate time-consuming regression checks without losing the human judgment critical to reliable releases.
Regression falls on your developers' shoulders
You release often but can’t measure coverage
You ship every week or two, but nobody can say for sure what was tested in the last build. Automated test results give your team a consistent record of every flow you’ve tested previously.
You manage several mobile apps
When each product team has its own testing approach, maintaining consistent coverage is quite difficult. One cross-platform test automation supports Android and iOS, so all your teams share the same structure and reports.
You already pay for device cloud
You pay for access to devices, but your team still conducts ad-hoc manual checks. Our framework automates repeatable checks on your device cloud, helping you get more value from your investment.
How we bring mobile test automation into your workflow
A testing automation strategy needs to fit your release cycles and team’s approach to working. Our framework isn’t a plug-and-play solution with a fixed setup. We learn your app and testing needs to connect our framework to your existing setup with minimal changes to your workflow.
Scope and outline strategy
We identify critical user flows, target platforms, test environment, and access requirements to set the scope for test automation development.
01
STEP
02
STEP
Connect framework
After connecting the framework to your app, the agents start mapping the screens and build a locator strategy.
Establish baseline suite
Our engineers review the first AI-generated test scenarios and automation code to verify they work as expected.
03
STEP
04
STEP
Integrate CI/CD and reporting
We connect the validated test execution to your pipeline and configure Allure reports for convenient review of test results.
Hand over and train your team
Together we decide which checks still need a human touch and teach your team to run commands and review AI-generated work. You also get documentation of what the suite covers and what stays with your testers.
05
STEP
06
STEP
Maintenance and scaling
If you choose test automation as a service, our team takes care of all framework maintenance needs and future coverage extension. Or train your team to manage the suite in-house.
01
STEP
Scope and outline strategy
We identify critical user flows, target platforms, test environment, and access requirements to set the scope for test automation development.
02
STEP
Connect framework
After connecting the framework to your app, the agents start mapping the screens and build a locator strategy.
03
STEP
Establish baseline suite
Our engineers review the first AI-generated test scenarios and automation code to verify they work as expected.
04
STEP
Integrate CI/CD and reporting
We connect the validated test execution to your pipeline and configure Allure reports for convenient review of test results.
05
STEP
Hand over and train your team
Together we decide which checks still need a human touch and teach your team to run commands and review AI-generated work. You also get documentation of what the suite covers and what stays with your testers.
06
STEP
Maintenance and scaling
If you choose test automation as a service, our team takes care of all framework maintenance needs and future coverage extension. Or train your team to manage the suite in-house.
Not sure your app is ready for automation? Start with the pilot to find out.
FAQ
Traditional frameworks give engineers tools, and engineers do all the work. AI-powered mobile test automation adds AI agents on top of a code-based test automation framework. They perform repetitive tasks like app mapping, test generation, and attempted failure repair, so you get the same engineering quality with far less manual effort. That’s what makes AI test automation practical for small teams.
No, and it isn’t meant to. The answer to manual vs. automated testing is usually both. AI agents take over automated regression testing and day-to-day checks that eat into every release. Testers remain process owners, doing higher-value work, setting the expected behavior for AI to follow, and staying responsible for final release sign-off.
The framework tests Android, iOS, and APIs in one Maven project. We use mobile test automation with Appium because it drives native apps on both platforms from a single codebase. Selenium works only in web browsers, so it can’t test native mobile apps. The framework relies on RestAssured for API test automation, Cucumber and Gherkin to write readable test scenarios, and Allure for reporting.
First, AI agents analyze test failures and sort them by cause. If it’s a broken locator, the agent repairs the test, reruns it to verify the fix, and explains the change for an engineer to approve before it’s merged. For flaky tests, it stabilizes waits when timing is the cause. Rather than automatically applying fixes, the framework checks the cause first and repairs only what it can verify.
Setup consists of three steps and can take anywhere from 40 to 200+ hours. We connect the framework, create a baseline suite, and integrate reporting into your pipeline. The range is wide because the work volume depends on the app’s size, complexity, and how easy it is to automate. We give a concrete estimate for test automation development after a scoping call.
Yes. We can start with a pilot on one of your apps and its core user flows. You get a working suite in your repository and a realistic view of what you can automate. If the results work for you, you can use our mobile test automation services to scale to other apps. Or you can start with a live demo.