Your dinner is “out for delivery,” but the map shows your driver has been stuck in one spot for ten minutes. Is the app frozen? Did the GPS fail? We’ve all been there. These small glitches create frustrating user experiences and can damage an app’s reputation. The success of a delivery app hinges on its ability to perform perfectly in the unpredictable real world.
This is where real device testing for delivery apps become the cornerstone of quality assurance. This approach involves validating your application on actual smartphones and tablets, not just on emulators or simulators. Delivery apps are uniquely complex; they juggle real-time GPS tracking, process sensitive payments, and must maintain stable network connectivity as a user moves from their Wi-Fi zone to a cellular network.
Each failed delivery costs companies an average of $17.78 in losses, underscoring the financial and reputational impact of glitches in delivery operations.
An effective app testing strategy recognizes that these features interact directly with a device’s specific hardware and operating system in ways simulators cannot fully replicate. While emulators are useful for basic checks, they often miss critical issues that only surface on physical hardware, such as network glitches, quirky sensor behavior, or performance lags on certain devices.
A robust mobile app testing plan that includes a fleet of real devices is the only way to accurately mirror your customer’s experience, ensuring everything from map tracking to payment processing works without a hitch.
Building Your Digital Fleet: Crafting a Device-Centric App Testing Strategy
You can’t test on every smartphone on the planet, so a smart app testing strategy is essential. The goal is to focus your efforts where they matter most—on the devices your actual customers are using. This begins with market research to understand your user base. Identify the most popular devices, manufacturers, and operating systems within your target demographic to ensure you cover 70-80% of your users. You should also consider the geographic distribution of your audience, as device preferences can vary significantly by region.
With this data, you can build a formal device matrix—a checklist of the hardware and OS versions your testing will cover. A strong matrix includes:
Diverse Platform Coverage: Select a mix of popular Android devices from various manufacturers (like Samsung and Google Pixel) and several iPhone models.
Multiple OS Versions: Include the latest major OS releases for both Android and iOS, as well as some widely used older versions.
A Range of Device Tiers: Test on recent flagship phones, popular midrange models, and older, less powerful devices to catch device-specific UI bugs and performance bottlenecks.
Acquiring and managing such a diverse collection of hardware is a significant challenge. This is where a real device cloud becomes invaluable. Services like AWS Device Farm provide remote access to thousands of physical iOS and Android devices, allowing you to run manual or automated mobile testing on a massive scale without purchasing every handset.
However, even with the power of the cloud, it’s a good practice to keep some core physical devices in-house. This hybrid approach ensures you have handsets for deep, hands-on debugging while leveraging the cloud for broad compatibility checks.
Putting the App Through Its Paces: Core Functional Testing
Once your device matrix is set, it’s time to test the core user workflows on each physical device. Functional testing ensures every feature a user interacts with works exactly as intended. These delivery app test cases should be run manually and, where possible, through automated mobile testing to ensure consistent coverage.
Account Registration & Login
A user’s first impression is often the login screen. Your testing should validate every entry point.
Test the standard email and SMS signup processes.
Verify that social logins (Google, Apple, Facebook) work seamlessly.
Check the password recovery flow.
Attempt to log in with incorrect credentials and invalid multi-factor authentication codes to ensure the app handles errors gracefully.
Menu Browsing & Search
The core of a delivery app is finding food. Simulate users browsing restaurant menus and using the search bar extensively. Test with valid and invalid keywords, partial phrases, and even typos. A smart search function should be able to interpret “vgn pizza” and correctly display results for a vegan pizza.
Cart and Customization
This is where users make decisions that lead to a purchase.
Add items to the cart, adjust quantities, and apply every available customization, like “no onions” or “extra cheese”.
Confirm that the cart’s contents persist correctly if you switch to another app and then return, or even close and reopen the app.
Validate that all calculations—item price, taxes, tips, and promotional coupon codes—update accurately with every change.
Checkout & Payment
The checkout process is a mission-critical flow where failures can directly lead to lost revenue.
Execute a complete order using every supported payment method, including credit/debit cards, digital wallets, and cash-on-delivery.
Test edge cases relentlessly, such as switching payment methods mid-transaction, entering invalid card details, or applying an expired coupon.
Simulate a network drop during the payment process to see if the app recovers without incorrectly charging the user.
Verify that the final price, including all fees and tips, is correct.
Ensure all payment data is transmitted securely over HTTPS/TLS and that sensitive information is properly masked on-screen.
Real-Time Tracking & Status Updates
After an order is placed, the app must provide accurate, real-time updates.
Confirm that order statuses like “Preparing,” “Out for Delivery,” and “Delivered” appear at the appropriate times.
Watch the driver’s location on the map to ensure the pin moves smoothly and corresponds to the actual delivery route. Discrepancies here are a major source of user frustration.
You can test this without physically moving a device by using GPS simulation tools, which are available in frameworks like Appium and on real device cloud platforms.
Notifications & Customer Support
Finally, test the app’s communication channels. Verify that push notifications for key order events (e.g., “Your courier has arrived”) appear correctly on both iOS and Android. Tapping a notification should take the user to the relevant screen within the app. Also, test any in-app chat or customer support features by sending common queries and ensuring they are handled correctly.
It is vital to perform all these functional tests on both platforms. Pay close attention to OS-specific behaviors, such as the Android back button versus iOS swipe-back gestures, to ensure neither path causes the app to crash or exit unexpectedly.
Beyond Functionality: Testing the Human Experience (UX)
A delivery app can be perfectly functional but still fail if it’s confusing or frustrating to use. Usability testing shifts the focus from “Does it work?” to “Does it feel right?” Real-device testing is essential here because it is the only way to accurately represent user gestures and physical interactions with the screen.
To assess usability, have real users—or QA team members acting as users—perform common tasks on a variety of physical phones. Ask them to complete a full order, from browsing a menu to checkout, and observe where they struggle.
Is the navigation intuitive? Can users easily find the search bar, add toppings to an item, or locate the customer support section?
Are interactive elements clear and accessible? Are buttons large enough to tap confidently without accidentally hitting something else? Do sliders and carousels respond smoothly to swipes?
Does the app feel fast and responsive? Check that load times, screen transitions, and animations are smooth on all target devices, not just high-end models.
Does the UI adapt properly? Verify that the layout adjusts correctly to different screen sizes and orientations without breaking or hiding important information.
Is the app globally ready? If your app is multilingual, test different language and locale settings to ensure that dates, currency formats, and text appear correctly without getting cut off.
Beta testing with a small group of real users is an invaluable practice. These users will inevitably uncover confusing screens and awkward workflows that scripted test cases might miss. Ultimately, the goal is to use real devices to feel the app exactly as your customers do, catching UX problems that emulators often hide.
Testing Under Pressure: Performance and Network Scenarios
A successful app must perform well even when conditions are less than ideal. An effective app testing strategy must account for both heavy user loads and unpredictable network connectivity. Using real devices is the only way to measure how your app truly behaves under stress.
App Performance and Load Testing
Your app needs to be fast and responsive, especially during peak hours like the dinner rush.
Simulate Concurrent Users: Use tools like JMeter to simulate thousands of users browsing menus and placing orders simultaneously, while you monitor backend server response times. One food-delivery case study found that with ~2,300 concurrent users, their system could still process 98 orders per minute with a minimal 0.07% error rate—this is the level of performance to strive for.
Measure On-Device Metrics: On each device in your matrix, record key performance indicators like how long the app takes to launch, how smoothly the menus scroll, and the response time for critical API calls.
Monitor Resource Usage: Keep an eye on battery and memory consumption, especially during power-intensive features like live map tracking, to ensure your app doesn’t excessively drain the user’s device.
Network Condition Testing
Delivery apps live and die by their network connection. Users and drivers are constantly moving between strong Wi-Fi, fast 5G, and spotty 4G or 3G coverage. Your app must handle these transitions gracefully.
Test on Various Networks: Manually test the app’s performance on different network types to see how it handles latency and limited bandwidth.
Simulate Network Drops: A critical test is to put a device in airplane mode in the middle of placing an order. The app should fail gracefully by displaying a clear error message or queuing the action to retry, rather than crashing or leaving the user in a state of confusion.
Use Simulation Tools: Services like the real device cloud provider Qyrus allow you to automate these tests by setting specific network profiles.
Check Network Switching: Confirm that the user’s session remains active and the app reconnects smoothly when switching between Wi-Fi and a cellular network.
By performing this level of real device testing for delivery apps, you will uncover issues like slower load times on devices with weaker processors or unexpected crashes that only occur under real-world stress.
Final Checks: Nailing Location, Security, and Automation
With the core functionality, usability, and performance validated, the final step in your app testing strategy is to focus on the specialized areas that are absolutely critical for a delivery app’s success: location services, payment security, and scalable automation.
GPS and Location Testing
A delivery app’s mapping and geolocation features must be flawless. On real devices, your testing should confirm:
Accuracy: Addresses are geocoded correctly and the proposed routes are sensible.
Live Tracking: The driver’s icon updates smoothly on the map. If possible, physically walk or drive a short distance with a device to observe this in a real-world setting.
Edge Cases: The app correctly handles users who are outside the delivery zone or scenarios where dynamic pricing should apply.
GPS Signal Loss: The app behaves predictably and recovers gracefully if the GPS signal is temporarily lost.
You can test many of these scenarios without leaving the office. Most real device cloud platforms and automation frameworks like Appium allow you to simulate or “spoof” GPS coordinates. This lets you check if the ETA updates correctly when a courier is far away or test location-based features without physically being in that region.
Payment and Security Testing
Handling payments means handling sensitive user data, making this a mission-critical area where trust is everything.
Validate All Payment Flows: Test every payment gateway and method you support, including digital wallets and cash-on-delivery.
Simulate Failures: Check how the app responds to a payment gateway outage or API timeout. It should roll back the transaction and display a clear error, never leaving the user wondering if they were charged.
Verify Encryption: Use real devices to confirm that all transactions are secured with HTTPS/TLS and that sensitive data like credit card numbers are properly masked on all screens.
Check Authentication: Ensure the app requires users to re-authenticate payments or has appropriate session timeouts to protect user accounts.
Tools and Automation
While manual testing is essential for usability and exploration, automated mobile testing is the key to achieving consistent and scalable coverage.
Automation Frameworks: Use frameworks to automate your regression tests. Appium is a popular choice for writing a single set of tests that can run on both iOS and Android. For platform-specific testing, you can use Espresso for Android and XCTest/XCUITest for iOS.
Cloud Integration: You can run these automated test scripts across hundreds of devices on a real device cloud, dramatically increasing the scope of your mobile app testing without repetitive manual work.
CI/CD Pipeline: The ultimate goal is to integrate these automated tests into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. Using tools like Jenkins or GitHub Actions, you can ensure that every new code change is automatically tested on a matrix of real devices before it ever reaches your customers.
By combining comprehensive functional checks, usability testing, and rigorous performance validation with a sharp focus on location, security, and automation, you create a robust quality assurance process. This holistic approach to real device testing for delivery apps ensures you ship a product that is not only functional but also reliable, secure, and delightful for users in the field.
Streamline Your Delivery App Testing with Qyrus
Managing a comprehensive testing process—across hundreds of devices, platforms, and test cases—can overwhelm even the most skilled QA teams, slowing down testing efforts. Delivery apps face unique complexities, from device fragmentation to challenges in reproducing defects.
A unified, AI-powered solution can simplify and accelerate this process. The Qyrus platform is an end-to-end test automation solution designed for the entire product development lifecycle. It provides a comprehensive platform for mobile, web, and API testing, infused with next-generation AI to enhance the quality and speed of testing.
Here is how Qyrus helps:
Codeless Automation: Drastically reduce the time it takes to create automated tests. Qyrus offers a no-code/low-code mechanism, including a mobile recorder that captures user actions and converts them into test steps in minutes. Your team can automate the entire user journey—from login to payment to order tracking—without writing extensive code.
True Cross-Platform Testing: Use a single, comprehensive platform to test your mobile applications (iOS & Android), web portals, and APIs, ensuring seamless integration and consistency.
Integrated Real Device Farm: Get instant access to a vast library of real devices to achieve maximum device coverage without the overhead of an in-house lab. Qyrus provides a diverse set of real smartphones and tablets, providing over 2,000 device-browser combinations, with 99.9% availability.
AI-Powered Autonomous Testing with Rover AI: Go beyond scripted tests. Deploy Qyrus’s Rover AI, a curiosity-driven autonomous solution, to explore your app, identify bugs, and uncover critical user paths you might have missed.
Seamless CI/CD Pipeline Integration: Integrate Qyrus directly into your CI/CD pipeline. The platform connects with tools like Jenkins, Azure DevOps, and Bitrise to run a full suite of regression tests on real devices with every new build, catching bugs before they reach customers.
Best Practices for Automation and CI/CD Integration
For teams looking to maximize efficiency, integrating automation into the development lifecycle is key. A modern approach ensures that quality checks are continuous, not just a final step.
Leverage Frameworks
For teams that have already invested in building test scripts, there’s no need to start from scratch. The Qyrus platform allows you to execute your existing automated test scripts on its real device cloud. It supports popular open-source frameworks, with specific integrations for Appium that allow you to run scripted tests to catch regressions early in the development process. You can generate the necessary configuration data for your Appium scripts directly from the platform to connect to the devices you need.
The Power of CI/CD
The true power of automation is realized when it becomes an integral part of your Continuous Integration and Continuous Deployment (CI/CD) pipeline. Integrating automated tests ensures that every new build is automatically validated for quality. Qyrus connects with major CI/CD ecosystems like Jenkins and Azure DevOps to automate your workflows. This practice helps agile development teams speed up release cycles by reducing defects and rework, allowing you to release updates faster and with more confidence.
Conclusion: Delivering a Flawless App Experience
Real device testing isn’t just a quality check; it’s a critical business investment. Emulators and simulators are useful, but they cannot replicate the complex and unpredictable conditions your delivery app will face in the real world. Issues arising from network glitches, sensor quirks, or device-specific performance can only be caught by testing on the physical hardware your customers use every day.
A successful testing strategy for delivery mobile applications must cover the full spectrum of the user experience. This includes validating all functional flows, measuring performance under adverse network and battery conditions, securing payment and user data, and ensuring the app is both usable and accessible to everyone.
In the hyper-competitive delivery market, a seamless and reliable user experience is the ultimate differentiator. Thorough real device testing is how you guarantee that every click, swipe, and tap leads to a satisfied customer.
Don’t let bugs spoil your customer’s appetite. Ensure a flawless delivery experience with Qyrus. Schedule a Demo Today!
Why 2026 Testing Needs One Platform, Not Many
A TestGuild x Qyrus Webinar Recording
The pace of software development has never been faster. AI-driven coding assistants like Devin, Copilot, and CodeWhisperer are accelerating release velocity, but QA hasn’t kept up.
Dev and Testing today are like two sides of a seesaw:
On one side → Dev teams are racing ahead with AI-powered speed.
On the other → QA teams overwhelmed by code explosion, flaky automation, disconnected tools, and brittle pipelines.
In the middle → The imbalance that slows releases and compromises quality.
On August 5, 2025, Qyrus teamed up with Joe Colantonio, founder of TestGuild, to explore how testing teams can finally bring balance back.
Why Watch the Recording?
In this session, Ameet Deshpande (SVP, Product Engineering at Qyrus) revealed why traditional testing stacks collapse at scale, and why agentic test orchestration — not tool count — is the real game changer.
You’ll learn:
✔️ The hidden costs of multi-tool chaos in QA ✔️ How AI Agents are reshaping automation and triage ✔️ Why agentic orchestration matters more than adding “just another tool” ✔️ How Qyrus SEER (Sense, Evaluate, Execute, Report) introduces a new era of autonomous testing
Meet the Experts
Ameet Deshpande
Senior Vice President, Product Engineering, Qyrus A technology leader with 20+ years in Quality & Product Engineering, Ameet is building the next generation of agentic, AI-driven quality platforms that deliver true autonomy at scale.
Ameet Deshpande
Senior Vice President, Product Engineering, Qyrus A technology leader with 20+ years in Quality & Product Engineering, Ameet is building the next generation of agentic, AI-driven quality platforms that deliver true autonomy at scale.
Access the Recording
This exclusive session has already taken place, but the insights are more relevant than ever. Fill out the form to watch the recording and discover how Qyrus SEER balances the Dev-QA seesaw once and for all.
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Save the Date 📅 October 8–9, 2025
📍 Bengaluru, India
India is leading one of the most ambitious digital transformations in the world, and APIs are at the center of that shift. From payments to healthcare, logistics to customer experience, APIs are the invisible engines driving billions of interactions every day. That’s why API Days India 2025 is the event to watch—and we’re excited to share that Qyrus will be there as a Silver Sponsor.
The event takes place at the Chancery Pavilion in Bengaluru, bringing together 800+ API experts, CTOs, product leaders, and developers from leading organizations. This year’s theme, “Future-proof APIs for billions: Powering India’s digital economy,” could not be more relevant.
qAPI, Powered by Qyrus
With qAPI, powered by Qyrus, APIs aren’t just about connecting systems. They’re about building digital experiences that are scalable, resilient, and rooted in quality.
qAPI is our end-to-end API testing platform designed to simplify and strengthen the way enterprises validate, monitor, and secure their APIs. From functional and performance testing to security and contract validation, qAPI helps teams accelerate releases, reduce risks, and deliver APIs that perform reliably at scale. By combining automation, intelligence, and real-time insights, qAPI empowers businesses to keep pace with innovation while ensuring flawless digital experiences.
Don’t Miss Our Keynote with Ameet Deshpande
We’re especially proud to share that Ameet Deshpande, Senior Vice President of Product Engineering at Qyrus, will deliver a keynote session at API Days India.
📅 October 8, 2025 ⏰ 4:00 PM – 4:20 PM IST 📍 Grand Ballroom 2, Chancery Pavilion 🎤 Session: “Rethinking Software Quality: Why API Testing Needs to Change”
In this session, Ameet will explore the unique challenges of API-driven ecosystems and explain why traditional QA strategies are no longer enough. With over two decades of experience leading large-scale transformation across financial services, cloud, and SaaS platforms, Ameet will share how enterprises can:
Move beyond outdated QA approaches
Adopt agentic orchestration
Leverage intelligence-driven automation for speed and resilience
If you’re looking to future-proof your API testing strategy, this is a session you won’t want to miss.
Meet the Qyrus Team at Booth #6
The conversation doesn’t stop at the keynote. Our team will be at Booth 6, ready to connect with API enthusiasts, developers, and enterprise leaders. Whether you’re curious about no-code, end-to-end API testing with qAPI, want to explore real-world solutions to API challenges, or simply want to exchange ideas, we’d love to meet you.
And here’s the fun part, visit our booth for surprise raffles and giveaway prizes. We promise it’ll be worth your time.
See You in Bengaluru
API Days India is the tech conference where the future of India’s digital economy takes shape, and we’re thrilled to be part of it.
Mark your calendar for October 8–9, 2025 and join us at the Chancery Pavilion.
Catch our keynote with Ameet Deshpande on October 8 at 4 PM.
Visit us at Booth 6 for conversations, demos, and giveaways.
We can’t wait to meet you in Bengaluru and start rethinking the future of API testing together.
The world of software testing moves fast, and staying ahead requires tools that not only keep pace but actively drive innovation. At Qyrus, we’re relentlessly focused on evolving our platform to empower your teams, streamline your workflows, and make achieving quality more intuitive than ever before. May was a busy month behind the scenes, packed with exciting new features and significant enhancements designed to give you even more power and flexibility in your testing journey.
Get ready to explore the latest advancements we’ve rolled out across the Qyrus platform!
Complex Web Tests, Now Powered by AI Genius!
Manual coding for complex calculations in web tests? Consider it a thing of the past! We’re thrilled to introduce a game-changing AI feature that lets you generate custom Java and JS code using simple, natural language descriptions. Just tell Qyrus what you need the code to do, and our AI gets to work, even understanding the variables you’ve already set up in your test. This AI Text-to-Code conversion is seamlessly integrated with our Execute JS, Execute JavaScript, and Execute Java actions, designed to produce accurate, executable snippets right when you need them. You maintain control, of course – easily review, modify, or copy the generated code before using it.
A quick note: This powerful AI code generation is currently a Beta feature, and we’re actively refining it based on your feedback!
Enhanced Run Visibility for Web Tests
But that’s not all for Web Testing this month. For our valued enterprise clients, managing your test runs just got clearer. You now have enhanced visibility into your test execution queues, allowing you to see detailed information, including the exact position of your test run in the queue. Gain better insight, plan more effectively, and stay informed every step of the way.
Sharper Focus for Your Mobile Visuals
Visual testing on mobile is crucial, but sometimes you need to tell your comparison tools to look past dynamic elements or irrelevant areas. This month, we’ve enhanced our Mobile Testing Mobile Testing capabilities to give you more granular control. You can now easily ignore specific areas within your mobile application screens, excluding those regions entirely from visual comparisons.
Additionally, you can ignore the header or footer of the screen meaning that you can easily compare different execution results and not run into issues due to differences in the notification bar or in a footer.
This means cleaner, more relevant results and less noise when you’re ensuring your app looks exactly as it should across devices. Focus on what truly matters for your app’s user interface integrity.
Device Farm: Smoother Streaming, Better Guidance
We know your time on the Device Farm Device Farm streaming screen is valuable, and a smooth experience is key. This month, we’ve rolled out several user experience improvements to make your interactions even more intuitive. The tour guide text has been refined to be more informative, guiding you clearly through the features.
We’ve also added a Global Navbar directly inside the device streaming page, providing consistent navigation right where you need it. Plus, for those times you’re working with a higher zoom percentage, we’ve included a handy scroll bar to make navigating the page much easier. Small changes, big impact on your workflow!
Desktop Testing: Schedule Your Success
We’re excited to announce that test scheduling is now available in Qyrus Desktop Testing. This highly requested feature, already familiar from other modules, brings a new level of automation to your desktop workflows. It’s particularly powerful for those complex end-to-end test cases that span across different modules, perhaps starting in a web portal, moving through a back office, and ending in servicing.
Now, you can schedule these crucial test flows, ensuring your regression suites run automatically, even aligning with deployment schedules. This means no more worrying about desktop availability at the exact moment of execution – Qyrus handles it for you. With this feature, efficiently managing tests for workflows impacting dozens of test cases becomes significantly simpler.
Smarter AI for Broader Test Coverage
Our commitment to leveraging AI to make testing more intelligent continues this month with key improvements to both TestGenerator and TestGenerator+. We’ve been refining these powerful features under the hood, and the result is simple but significant: you should now see more tests built by the AI compared to previous versions.
Remember, TestGenerator is designed to transform your JIRA tickets directly into actionable test scenarios, bridging the gap between development tasks and testing needs. TestGenerator+ takes it a step further, actively exploring untested areas of your application, intelligently identifying gaps, and helping you increase your overall test coverage. These enhancements mean our AI is working even harder to help you achieve comprehensive and efficient testing with less manual effort.
Ready to Experience the May Power-Ups?
This month’s Qyrus updates are all about putting more power, intelligence, and efficiency directly into your hands. From harnessing AI to generate complex web code to gaining sharper insights from mobile visual tests, scheduling your desktop workflows, and boosting the output of our AI test generators – every enhancement is designed with your success in mind. We’re dedicated to providing a platform that adapts to your needs, streamlines your processes, and helps you deliver quality software faster than ever before.
Excited to see these May power-ups in action? There’s no better way to understand the impact Qyrus can have on your testing journey than by experiencing it firsthand.
We’re constantly building, innovating, and looking for ways to make your testing life easier. Stay tuned for more exciting updates from Qyrus!
One of North America’s leading Coca-Cola bottlers manages a massive logistics network, operating more than 10 state-of-the-art manufacturing plants and over 70 warehouses. Their complex business processes—spanning sales, distribution, finance, and warehouse management—rely on SAP S/4HANA as the central ERP, connected to over 30 satellite systems for functions like last-mile delivery.
Before partnering with Qyrus, the company’s quality assurance process was a fragmented and manual effort that struggled to keep pace. Testing across their SAP desktop, internal web portals, and mobile delivery apps was siloed, slow, and inconsistent.
Qyrus provided a single, unified platform to automate their business-critical workflows from end to end. The results were immediate and dramatic. The bottler successfully automated over 500 test scripts, covering more than 19,000 individual steps across 40+ applications. This strategic shift slashed overall test execution time from over 10,020 minutes down to just 1,186 minutes—an 88% reduction that turned their quality process into a strategic accelerator.
The High Cost of Disconnected Quality
Before implementing Qyrus, the bottler’s quality assurance environment faced significant operational challenges that created friction and risk. The core issue was a testing process that could not match the integrated nature of their business. This disconnect led to several critical pain points.
Fragmented and Slow Manual Testing: Functional testing was performed manually across SAP GUI, internal web portals, and mobile delivery applications. This approach resulted in slow regression cycles and inconsistent test coverage across platforms.
Lack of End-to-End Confidence: There was limited integration between the desktop SAP modules and the mobile Last Mile Delivery workflows. This gap prevented true end-to-end testing, reducing confidence that a complete business journey would work correctly in production.
Burdensome Evidence Collection: Gathering evidence for audits and defect analysis was a manual, time-consuming process. This practice significantly slowed down both compliance checks and the ability to triage and fix bugs quickly.
Operational Drain on Experts: Frequent change requests continuously increased the testing burden. As a result, critical subject matter experts (SMEs) were constantly pulled away from their primary operational duties to participate in tedious test cycles.
The client needed a single platform that could automate their real business journeys across SAP, web, and mobile while producing audit-ready evidence on demand.
Connecting the Dots: A Unified Automation Strategy
Qyrus replaced the client’s fragmented tools with a single, centralized platform designed to mirror their real-world business journeys. Instead of testing applications in isolation, the bottler could now execute complete, end-to-end workflows that spanned their entire technology ecosystem, including SAP, Greenmile, WinSmart, VendSmart, BY, and Osapiens LMD. This was made possible by leveraging several key features of the Qyrus platform.
Codeless SAP Automation: Using the Desktop Recorder for SAP, the team quickly captured and automated critical SAP GUI flows without writing any code. Processes like order creation, delivery planning, and route allocation were automated and then reused across multiple tests with parameterized data, saving countless hours of scripting and maintenance.
End-to-End Test Orchestration: Qyrus connected individual scripts across SAP, web, desktop, and mobile into a single, cohesive workflow. Built-in waits ensured that backend updates from one system, like a shipment creation in SAP, were correctly synchronized before the next step began in another system, such as a mobile delivery app.
Dynamic Data Handling: The automation scripts were built to be resilient. The platform captured critical data like shipment IDs, driver assignments, and warehouse keys at runtime. This approach eliminated brittle, hard-coded values and enabled robust, data-driven test runs.
One-Click Audit and Evidence Trails: Every test step was automatically documented with screenshots and compiled into detailed PDF reports. This feature was used extensively for faster defect analysis, end-user training, and providing auditors with clear, irrefutable evidence of system validation.
This unified approach finally gave the client a true, top-down view of their quality, allowing them to test the way their business actually operates.
Speed, Scale, and Unshakable Confidence
The implementation of Qyrus delivered immediate, measurable results that fundamentally transformed the bottler’s quality assurance process. The automation initiative achieved a scale and speed that was previously impossible with manual testing, leading to significant gains in efficiency, risk reduction, and operational governance.
The most significant outcome was a dramatic 88% reduction in test execution time. A full regression cycle that once took over 10,020 minutes (more than 166 hours) to complete manually now finishes in just 1,186 minutes (under 20 hours) with automation.
This newfound speed was applied across a massive scope:
The client successfully automated over 500 test scripts.
These scripts encompassed more than 19,000 individual steps.
The automation suite provided coverage for over 40 distinct SAP, mobile, and web applications, including critical systems for route optimization, delivery, and warehouse management.
Beyond speed, the centralized execution and one-click PDF reports provided full traceability for every process. This comprehensive evidence proved invaluable not only for audit preparedness but also for end-user training, ultimately reducing time, effort, and operational risk across all platforms.
Beyond Automation: A Future-Proof Quality Partnership
With the foundation of a highly successful automation suite now in place, the bottler is looking to the future. As of mid-2025, with over 500 test cases and 19,000 steps automated, the client’s immediate goal is to complete the remaining functional automation by December 2025 through a fixed-price engagement. The objective is to establish a steady-state model where a fully automated regression suite is maintained without new scripting costs, seamlessly integrating script maintenance, and the addition of new test cases under their existing managed services.
Building on that foundation, the long-term vision is to evolve the partnership by leveraging AI to increase testing speed and intelligence. The client envisions a future state that includes:
AI-Driven Test Selection: Using AI to automatically select the most relevant test cases to run based on specific code and configuration changes.
Intelligent Impact Analysis: Applying AI to analyze the potential impact of changes across SAP and other connected applications.
AI-Assisted Test Creation: Generating new test cases automatically from support tickets and business process documentation.
Autonomous Continuous Testing: Implementing AI for autonomous test healing and the automatic triage of flaky tests.
Smarter Regression Cycles: Receiving AI-powered recommendations on when to run a full regression versus more targeted, modular testing.
By embedding Qyrus deeply into their release cycles, the client aims to reduce risk, accelerate delivery, and strengthen quality governance across every product touchpoint. Ultimately, they see Qyrus not just as a testing tool, but as an end-to-end quality platform capable of supporting their enterprise agility for years to come.
Experience Your Own Transformation
The challenges of manual testing across SAP and modern applications are universal, but the solution is simple. Qyrus provided this client with the speed and end-to-end confidence needed to thrive.
You’ve built a powerful mobile app. Your team has poured months into coding, designing, and refining it. Then, the launch day reviews arrive: “Crashes on my Samsung.” “The layout is broken on my Pixel tablet.” “Doesn’t work on the latest iOS.” Sounds familiar?
Welcome to the chaotic world of mobile fragmentation that hampers mobile testing efforts.
As of 2024, an incredible 4.88 billion people use a smartphone, making up over 60% of the world’s population. With more than 7.2 billion active smartphone subscriptions globally, the mobile ecosystem isn’t just a market—it’s the primary way society connects, works, and plays.
This massive market is incredibly diverse, creating a complex matrix of operating systems, screen sizes, and hardware that developers must account for. Without a scalable way to test across this landscape, you risk releasing an app that is broken for huge segments of your audience.
This is where a mobile device farm enters the picture. No matter how much we talk about AI automating the testing processes, testing range of devices and versions is still a challenge.
A mobile device farm (or device cloud) is a centralized collection of real, physical mobile devices used for testing apps and websites. It is the definitive solution to fragmentation, providing your QA and development teams with remote access to a diverse inventory of iPhones, iPads, and Android devices including Tabs for comprehensive app testing. This allows you to create a controlled, consistent, and scalable environment for testing your app’s functionality, performance, and usability on the actual hardware your customers use.
This guide will walk you through everything you need to know. We’ll cover what a device farm is, why it’s a competitive necessity for both manual tests and automated tests, the different models you can choose from, and what the future holds for this transformative technology.
Why So Many Bugs? Taming Mobile Device Fragmentation
The core reason mobile device farms exist is to solve a single, massive problem: device fragmentation. This term describes the vast and ever-expanding diversity within the mobile ecosystem, creating a complex web of variables that every app must navigate to function correctly. Without a strategy to manage this complexity, companies risk launching apps that fail for huge portions of their user base, leading to negative reviews, high user churn, and lasting brand damage.
Let’s break down the main dimensions of this challenge.
Hardware Diversity
The market is saturated with thousands of unique device models from dozens of manufacturers. Each phone or tablet comes with a different combination of screen size, pixel density, resolution, processor (CPU), graphics chip (GPU), and memory (RAM). An animation that runs smoothly on a high-end flagship might cause a budget device to stutter and crash. A layout that looks perfect on a 6.1-inch screen could be unusable on a larger tablet. Effective app testing must account for this incredible hardware variety.
Operating System (OS) Proliferation
As of August 2025, Android holds the highest market share at 73.93% among mobile operating systems, followed by iOS (25.68%). While the world runs on Android and iOS, simplicity is deceptive. At any given time, there are numerous active versions of each OS in the wild, and users don’t always update immediately. The issue is especially challenging for Android devices, where manufacturers like Samsung apply their own custom software “skins” (like One UI) on top of the core operating system. These custom layers can introduce unique behaviors and compatibility issues that don’t exist on “stock” Android, creating another critical variable for your testing process.
This is the chaotic environment your app is released into. A mobile device farm provides the arsenal of physical devices needed to ensure your app delivers a flawless experience, no matter what hardware or OS version your customers use.
Can’t I Just Use an Emulator? Why Real Physical Devices Win
In the world of app development, emulators and simulators—software that mimics mobile device hardware—are common tools. They are useful for quick, early-stage checks directly from a developer’s computer. But when it comes to ensuring quality, relying on them exclusively is a high-risk gamble.
Emulators cannot fully replicate the complex interactions of physical hardware, firmware, and the operating system. Testing on the actual physical devices your customers use is the only way to get a true picture of your app’s performance and stability. In fact, a 2024 industry survey found that only 19% of testing teams rely solely on virtual devices. The overwhelming majority depend on real-device testing for a simple reason: it finds more bugs.
What Emulators and Simulators Get Wrong
Software can only pretend to be hardware. This gap means emulators often miss critical issues related to real-world performance. They struggle to replicate the nuances of:
CPU and Memory Constraints: An emulator running on a powerful developer machine doesn’t accurately reflect how an app performs on a device with limited processing power and RAM.
Battery Drain: You can’t test an app’s impact on battery life without a real battery. This is a crucial factor for user satisfaction that emulators are blind to.
Hardware Interactions: Features that rely on cameras, sensors, or Bluetooth connections behave differently on real hardware than in a simulated environment.
Network Interruptions: Real devices constantly deal with fluctuating network conditions and interruptions from calls or texts—scenarios that emulators cannot authentically reproduce.
Using a device cloud with real hardware allows teams to catch significantly more app crashes simply by simulating these true user conditions.
When to Use Emulators (and When Not To)
Emulators have their place. They are great for developers who need to quickly check a new UI element or run a basic functional check early in the coding process.
However, for any serious QA effort—including performance testing, regression testing, and final pre-release validation—they are insufficient. For that, you need a mobile device farm.
Public, Private, or Hybrid? How to Choose Your Device Farm Model
Once you decide to use a mobile device farm, the next step is choosing the right model. This is a key strategic decision that balances your organization’s specific needs for security, cost, control, and scale. Let’s look at the three main options.
Public Cloud Device Farms
Public cloud farms are services managed by third-party vendors like Qyrus that provide on-demand access to a large, shared pool of thousands of real mobile devices.
Pros: This model requires no upfront hardware investment and eliminates maintenance overhead, as the vendor handles everything. You get immediate access to the latest devices and can easily scale your app testing efforts up or down as needed.
Cons: Because the infrastructure is shared, some organizations have data privacy concerns, although top vendors use rigorous data-wiping protocols. You are also dependent on internet connectivity, and you might encounter queues for specific popular devices during peak times.
Private (On-Premise) Device Farms
A private farm is an infrastructure that you build, own, and operate entirely within your own facilities. This model gives you absolute control over the testing environment.
Pros: This is the most secure option, as all testing happens behind your corporate firewall, making it ideal for highly regulated industries. You have complete control over device configurations and there are no recurring subscription fees after the initial setup.
Cons: The drawbacks are significant. This approach requires a massive initial capital investment for hardware and ongoing operational costs for maintenance, updates, and repairs. Scaling a private farm is a slow and expensive manual process, making it difficult to keep pace with the market.
Hybrid Device Farms
As the name suggests, a hybrid model is a strategic compromise that combines elements of both public and private farms. An organization might maintain a small private lab for its most sensitive manual tests while using a public cloud for large-scale automated tests and broader device coverage. This approach offers a compelling balance of security and flexibility.
Expert Insight: Secure Tunnels Changed the Game
A primary barrier to using public clouds was the inability to test apps on internal servers behind a firewall. This has been solved by secure tunneling technology. Features like “Local Testing” create an encrypted tunnel from the remote device in the public cloud directly into your company’s internal network. This allows a public device to safely act as if it’s on your local network, making public clouds a secure and viable option for most enterprises.
Quick Decision Guide: Which Model is Right for You?
You need a Public Farm if: You prioritize speed, scalability, and broad device coverage. This model is highly effective for startups and small-to-medium businesses (SMBs) who need to minimize upfront investment while maximizing flexibility.
You need a Private Farm if: You operate under strict data security and compliance regulations (e.g., in finance or healthcare) and have the significant capital required for the initial investment.
You need a Hybrid Farm if: You’re a large enterprise that needs a balance of maximum security for core, data-sensitive apps and the scalability of the cloud for general regression testing.
6 Must-Have Features of a Modern Mobile Device Farm
Getting access to devices is just the first step. The true power of a modern mobile device farm comes from the software and capabilities that turn that hardware into an accelerated testing platform. These features are what separate a simple device library from a tool that delivers a significant return on investment.
Here are five essential features to look for.
1. Parallel Testing
This is the ability to run your test suites on hundreds of device and OS combinations at the same time. A regression suite that might take days to run one-by-one can be finished in minutes. This massive parallelization provides an exponential boost in testing throughput, allowing your team to get feedback faster and release more frequently.
2. Rich Debugging Artifacts
A failed test should provide more than just a “fail” status. Leading platforms provide a rich suite of diagnostic artifacts for every single test run. This includes full video recordings, pixel-perfect screenshots, detailed device logs (like logcat for Android), and even network traffic logs. This wealth of data allows developers to quickly find the root cause of a bug, dramatically reducing the time it takes to fix it.
3. Seamless CI/CD Integration
Modern device farms are built to integrate directly into Continuous Integration/Continuous Deployment (CI/CD) pipelines like Jenkins or GitLab CI. This allows automated tests on real devices to become a standard part of your development process. With every code change, tests can be triggered automatically, giving developers immediate feedback on the impact of their work and catching bugs within minutes of their introduction.
4. Real-World Condition Simulation
Great testing goes beyond the app itself; it validates performance in the user’s environment. Modern device farms allow you to simulate a wide range of real-world conditions. This includes testing on different network types (3G, 4G, 5G), simulating poor or spotty connectivity, and setting the device’s GPS location to test geo-specific features. This is essential for ensuring your app is responsive and reliable for all users, everywhere.
5. Broad Automation Framework Support
Your device farm must work with your tools. Look for a platform with comprehensive support for major mobile automation frameworks, especially the industry-standard test framework, Appium. Support for native frameworks like Espresso (Android) and XCUITest (iOS) is also critical. This flexibility ensures that your automation engineers can write and execute scripts efficiently without being locked into a proprietary system.
6. Cross Platform Testing Support
Modern businesses often perform end-to-end testing of their business processes across various platforms such as mobile, web and desktop. Device farms should seamlessly support such testing requirements with session persistence while moving from one platform to another.
Qyrus Device Farm: Go Beyond Access, Accelerate Your Testing
Access to real devices is the foundation, but the best platforms provide powerful tools that accelerate the entire testing process. The Qyrus Device Farm is an all-in-one platform designed to streamline your workflows and supercharge both manual tests and automated tests on real hardware. It delivers on all the “must-have” features and introduces unique tools to solve some of the biggest challenges in mobile QA.
Our platform is built around three core pillars:
Comprehensive Device Access: Test your applications on a diverse set of real hardware, including the smartphones and tablets your customers use, ensuring your app works flawlessly in their hands.
Powerful Manual Testing: Interactively test your app on a remote device in real-time. Qyrus gives you full control to simulate user interactions, identify usability issues, and explore every feature just as a user would.
Seamless Appium Automation: Automate your test suites using the industry-standard Appium test framework. Qyrus enables you to run your scripted automated tests in parallel to catch regressions early and often, integrating perfectly with your CI/CD pipeline.
Bridge Manual and Automated Testing with Element Explorer
A major bottleneck in mobile automation is accurately identifying UI elements to create stable test scripts. The Qyrus Element Explorer is a powerful feature designed to eliminate this problem.
How it Works: During a live manual test session, you can activate the Element Explorer to interactively inspect your application’s UI. By simply clicking on any element on the screen—a button, a text field, an image—you can instantly see its properties (IDs, classes, text, XPath) and generate reliable Appium locators.
The Benefit: This dramatically accelerates the creation of automation scripts. It saves countless hours of manual inspection, reduces script failures caused by incorrect locators, and makes your entire automation effort more robust and efficient.
Simulate Real-World Scenarios with Advanced Features
Qyrus allows you to validate your app’s performance under complex, real-world conditions with a suite of advanced features:
Network Reshaping: Simulate different network profiles and poor connectivity to ensure your app remains responsive and handles offline states gracefully.
Interrupt Testing: Validate that your application correctly handles interruptions from incoming phone calls or SMS messages without crashing or losing user data.
Biometrics Bypass: Test workflows that require fingerprint or facial recognition by simulating successful and failed authentication attempts, ensuring your secure processes are working correctly.
Test Orchestration: Qyrus device farm is integrated into its Test Orchestration module that performs end-to-end business process testing across web, mobile, desktop and APIs.
Ready to accelerate your Appium automation and empower your manual testing? Explore the Qyrus Device Farm and see these features in action today.
The Future of Mobile Testing: What’s Next for Device Farms?
The mobile device farm is not a static technology. It’s rapidly evolving from a passive pool of hardware into an “intelligent testing cloud”. Several powerful trends are reshaping the future of mobile testing, pushing these platforms to become more predictive, automated, and deeply integrated into the development process.
AI and Machine Learning Integration
Artificial Intelligence (AI) and Machine Learning (ML) are transforming device farms from simple infrastructure into proactive quality engineering platforms. This shift is most visible in how modern platforms now automate the most time-consuming parts of the testing lifecycle.
AI-Powered Test Generation and Maintenance: A major cost of automation is the manual effort required to create and maintain test scripts. Qyrus directly addresses this with Rover, a reinforcement learning bot that automatically traverses your mobile application. Rover explores the app on its own, visually testing UI elements and discovering different navigational paths and user journeys. As it works, it generates a complete flowchart of the application’s structure. From this recorded journey, testers can instantly build and export mobile test scripts, dramatically accelerating the test creation process.
Self-Healing Tests: As developers change the UI, traditional test scripts often break because element locators become outdated. AI-driven tools like Qyrus Healer can intelligently identify an element, like a login button, even if its underlying code has changed. This “self-healing” capability dramatically reduces the brittleness of test scripts and lowers the ongoing maintenance burden.
Predictive Analytics: By analyzing historical test results and code changes, AI platforms can predict which areas of an application are at the highest risk of containing new bugs. This allows QA teams to move away from testing everything all the time and instead focus their limited resources on the most critical and fragile parts of the application, increasing efficiency.
Preparing for the 5G Paradigm Shift
The global deployment of 5G networks introduces a new set of testing challenges that device farms are uniquely positioned to solve. Testing for 5G readiness involves more than just speed checks; it requires validating:
Ultra-low latency for responsive apps like cloud gaming and AR.
Battery consumption under the strain of high data throughput.
Seamless network fallback to ensure an app functions gracefully when it moves from a 5G network to 4G or Wi-Fi.
Addressing Novel Form Factors like Foldables
The introduction of foldable smartphones has created a new frontier for mobile app testing. These devices present a unique challenge that cannot be tested on traditional hardware. The most critical aspect is ensuring “app continuity,” where an application seamlessly transitions its UI and state as the device is folded and unfolded, without crashing or losing user data. Device farms are already adding these complex devices to their inventories to meet this growing need.
Your Next Steps in Mobile App Testing
The takeaway is clear: in today’s mobile-first world, a mobile device farm is a competitive necessity. It is the definitive market solution for overcoming the immense challenge of device fragmentation and is foundational to delivering the high-quality, reliable, and performant mobile applications your users demand.
As you move forward, remember that the right solution—whether public, private, or hybrid—depends on your organization’s unique balance of speed, security, and budget.
Ultimately, the future of quality assurance lies not just in accessing devices, but in leveraging intelligent platforms that provide powerful tools. Features like advanced element explorers for automation and sophisticated real-world simulations are what truly accelerate and enhance the entire testing lifecycle, turning a good app into a great one.
Welcome to the final chapter of our five-part series on Agentic Orchestration. We’ve journeyed through the entire SEER framework—from the ‘Eyes and Ears’ of Sense, to the ‘Brain’ of Evaluate, and the ‘Muscle’ of Execute. If you’re just joining us, we invite you to start from the beginning to see how this transformative approach is reshaping the future of QA.
The Final Verdict: From Raw Data to Decisive Action with Agentic Orchestration
The tests have run. The agents have completed their mission. But in modern quality assurance, a simple “pass/fail” is no longer enough. The most critical part of the process is answering the question: “What did we learn, and what do we do next?” This is the final, crucial step where the entire value of the testing process is realized.
For too long, teams have been trapped by the failure of traditional test reporting. They face a flood of raw data—endless logs, fragmented dashboards from multiple tools, and noisy results that create more confusion than clarity. This data overload forces engineers to spend valuable time manually triaging issues instead of innovating. It’s a process that delivers data, but not decisions.
Welcome to the ‘Report’ stage, the intelligence layer of the Qyrus SEER framework. This is where we close the loop. Here, Agentic AI Orchestration moves beyond simple reporting and transforms raw test outcomes into strategic business intelligence. We will show you how the system delivers true Test Reporting & Test Insights that empower your team to act with speed and confidence.
Decoding the Data: Meet SEER’s Reporting Agents
To deliver true Test Reporting & Test Insights, the Qyrus SEER framework relies on a specialized unit of Single Use Agents (SUAs). These agents work in concert to sift through the raw outcomes from the execution stage, analyze the results, and present a clear, intelligent picture of your application’s quality. They are the analysts and translators of the operation.
The AI Analyst: Eval
At the heart of the reporting process is Eval. This sophisticated agent intelligently evaluates the outputs from all the tests, including those from complex AI models within your application.
Eval goes far beyond a simple pass/fail; it provides a deeper, more contextual analysis of the results, ensuring you understand the nuances of the test outcome. It’s the expert analyst that finds the signal in the noise.
The Mission Control Dashboard: AnalytiQ
AnalytiQ is the agent that brings everything together. It aggregates the logs and metrics from the entire execution squad—TestPilot, Rover, API Builder, and more—into a single, comprehensive dashboard. This provides your entire team, from developers to business leaders, with a centralized, single source of truth for quality, tracking trends and stability over time.
The Conversational Specialist: BotMetrics
Showcasing the platform’s flexibility, specialized agents like BotMetrics can be deployed for unique reporting needs. BotMetrics provides an expert, AI-driven evaluation of a chatbot’s conversational skills, analyzing interactions and providing recommendations to enhance the user experience. This demonstrates how Agentic AI Orchestration can provide deep insights for any component of your digital ecosystem.
The Assembly Line of Intelligence: How SEER Crafts Your Test Insights
Generating a truly valuable report is a deliberate, multi-step process. Agentic AI Orchestration doesn’t just dump raw data into a folder; it guides the results through a sophisticated assembly line of analysis to ensure the final output is concise, relevant, and immediately actionable. This is how the system produces world-class Test Reporting & Test Insights.
Step 1: Consolidate Test Coverage: Before analyzing failures, the system first confirms success. It automatically cross-checks the completed test runs with the specific components and user stories that were impacted by the initial change. This crucial first step ensures that the test scope was complete, providing immediate confidence that you tested everything that mattered.
Step 2: Perform AI-Driven Risk Assessment: Next, the agents evaluate the severity and potential business impact of any defects or anomalies that were found. They intelligently prioritize issues, categorizing them into high, medium, and low severity so your team knows exactly where to focus their attention first. This moves the conversation from “what broke?” to “what is the most critical thing to fix right now?”
Step 3: Deliver Instant, Actionable Feedback: Finally, the system delivers the verdict. A concise API Testing Report, a summary of UI validation, or a list of prioritized defects is sent instantly to the right stakeholders through automated notifications on Slack, email, or via updates to Jira tickets. The feedback loop that used to take days of manual triage is now closed in minutes.
Closing the Loop: The Transformative Benefits of Agentic Reporting
This intelligent reporting workflow does more than just save time; it creates a virtuous cycle of continuous improvement that fundamentally enhances your entire quality assurance process. The benefits of this Agentic AI Orchestration extend far beyond a simple dashboard, providing a clear competitive advantage.
Actionable Insights, Not Data Dumps: The system provides a deeper understanding of software quality by delivering insights that empower your team, not overwhelm them. Specialized agents like Eval intelligently assess outputs to provide smarter, more contextual results. This transforms your Test Reporting & Test Insights from a reactive log of what happened into a proactive guide for what to do next.
Predictive Analytics for Proactive Quality: By analyzing historical test results, defect trends, and risk profiles stored in the Context DB, the framework begins to predict potential failures before they happen. It identifies patterns and high-risk areas in your application. This allows your team to shift from a reactive to a proactive stance, optimizing test strategies to address issues long before they can impact your customers.
A Learning Loop for Continuous Improvement: This is the most powerful benefit of the entire framework. The system creates a continuous feedback loop. Every test outcome, coverage gap, and updated risk analysis is fed back into the Context DB, enriching the system’s knowledge base. This new knowledge makes the entire Qyrus SEER framework smarter and more efficient with every single test run, ensuring your QA process constantly evolves and adapts.
From Theory to Bottom Line: The Tangible ROI of Agentic Orchestration
AI in testing has officially reached its tipping point. Industry studies confirm that this is no longer a future concept but a present-day reality. A remarkable 68% to 71% of organizations now report that they have integrated or are utilizing Generative AI in their operations to advance Quality Engineering. The industry has spoken, and the move toward AI-driven quality is accelerating.
However, adopting AI is only the first step. The true measure of success lies in the tangible results it delivers. This is where the Qyrus SEER framework moves beyond the hype, translating the power of Agentic AI Orchestration into a measurable test automation ROI that transforms your bottom line.
Unprecedented Speed and Efficiency: By eliminating manual hand-offs and orchestrating targeted tests with specialized agents, the Qyrus platform dramatically accelerates the entire testing cycle. This allows organizations to shorten release timelines and increase developer productivity. Teams leveraging this intelligent automation see a 50-70% reduction in overall testing time. This translates directly to a faster time-to-market for new features, giving your business a significant competitive advantage.
Drastically Reduced Costs and Reallocated Talent: The autonomous, agent-driven nature of the SEER framework directly attacks the largest hidden costs in most QA organizations: maintenance and tool sprawl. By deploying the Healer agent to automatically fix broken scripts, organizations reduce the time and effort spent on test script maintenance by a staggering 65-70%. This frees your most valuable and expensive engineering talent from low-value repair work, allowing you to reallocate their expertise toward innovation and complex quality challenges.
Enhanced Quality and Deployment Confidence: Speed and cost savings are meaningless without quality. By intelligently analyzing changes and deploying agents like Rover and TestGenerator+ to explore untested paths, the Qyrus platform improves the effectiveness of your testing. AI-driven test generation can improve test coverage by up to 85%, ensuring that more of your application is validated before release. This smarter approach also leads to a 25-30% improvement in defect detection rates, catching more critical bugs before they impact your customers.
Conclusion: The SEER Saga—A New Era of Autonomous Quality
Our journey through the Qyrus SEER framework is now complete. We’ve seen how Agentic AI Orchestration builds a truly autonomous system, moving intelligently from one stage to the next. It begins with the “Eyes and Ears” of the Sense stage, which detects every change in your development ecosystem. It then moves to the “Brain” of the Evaluate stage, where it analyzes the impact and crafts a perfect testing strategy. Next, the “Muscle” of the Execute stage unleashes a squad of agents to perform the work with speed and precision.
Finally, we arrive at the “Voice” of the Report stage. This is where the system closes the loop, transforming raw data into the critical insights that drive your business forward. This is far more than just a new set of tools; it’s a fundamental paradigm shift that transforms QA from a bottleneck into a strategic accelerator. It’s how you can finally achieve faster releases, comprehensive coverage, and a significant reduction in costs, all while delivering higher-quality software.
Ready to Explore Qyrus’ Autonomous SEER Framework? Contact us today!
Welcome to the fourth chapter of our Agentic Orchestration series. So far, we’ve seen how the Qyrus SEER framework uses its ‘Eyes and Ears’ to Sense changes and its ‘Brain’ to Evaluate the impact. Now, it’s time to put that intelligence into action. In this post, we’ll explore the ‘Muscle’ of the operation: the powerful test execution stage. If you’re new to the series, we recommend starting with Part 1 to understand the full journey.
How the Qyrus SEER Framework Redefines Test Execution
The Test Strategy is set. The impact analysis is complete. In the last stage of our journey, the ‘Evaluate stage’ in the Qyrus SEER framework acted as the strategic brain, crafting the perfect testing plan. Now, it’s time to unleash the hounds. Welcome to the ‘Execute’ stage—where intelligent plans transform into decisive, autonomous action.
In today’s hyper-productive environment, where AI assistants contribute to as much as 25% of new code, development teams operate at an unprecedented speed. Yet, QA often struggles to keep up, creating a “velocity gap” where traditional testing becomes the new bottleneck. It’s a critical business problem. To solve it, you need more than just automation; you need intelligent agentic orchestration.
This is where the SEER framework truly shines. It doesn’t just run a script. It conducts a sophisticated team of specialized Single Use Agents (SUAs), launching an intelligent and targeted attack on quality. This is the dawn of true autonomous test execution, an approach that transforms QA from a siloed cost center into a strategic business accelerator.
Unleashing the Test Agents: A Multi-Agent Attack on Quality
The Qyrus SEER framework’s brilliance lies in its refusal to use a one-size-fits-all approach. Instead of a single, monolithic tool, SEER acts as a mission controller for its agentic orchestration, deploying a squad of highly specialized Single Use Agents (SUAs) to execute the perfect test, every time. This isn’t just automation; this is a coordinated, multi-agent attack on quality.
The UI Specialist – TestPilot: When the user interface needs validation, SEER deploys TestPilot. This agent acts as your AI co-pilot, creating and executing functional tests across both web and mobile platforms. It simulates real user interactions with precision, ensuring your application’s UI testing is thorough and that the front-end experience is not just functional, but flawless.
The Backend Enforcer – API Builder: For the core logic of your application, API Builder gets the call. This powerful agent executes deep-level API testing to validate your backend services, microservices, and complex integration points. It can even instantly virtualize APIs based on user requirements, allowing for robust and isolated testing that isn’t dependent on other systems being available.
The Autonomous Explorer – Rover: What about the bugs you didn’t think to look for? SEER deploys Rover, an autonomous AI scout that explores your application to uncover hidden bugs and untested pathways that scripted tests would inevitably miss. Rover’s exploratory work is a crucial part of our AI test execution, ensuring comprehensive coverage and building a deep confidence in your release.
The Maintenance Expert – Healer: Perhaps the most revolutionary agent in the squad is Healer. Traditional test automation’s greatest weakness is maintenance; scripts are brittle and break when an application’s UI changes. Healer solves this problem. When a test fails due to a legitimate application update, this agent automatically analyzes the change and updates the test script, delivering true self-healing tests. It single-handedly eliminates the endless cycle of fixing broken tests.
Behind the Curtain: The Technology Driving Autonomous Execution
This squad of intelligent agents doesn’t operate in a vacuum. They are powered by a robust and scalable engine room designed for one purpose: speed. The Qyrus SEER framework integrates deeply into your development ecosystem to make autonomous test execution a seamless reality.
First, Qyrus plugs directly into your existing workflow through flawless continuous integration. The moment a developer merges a pull request or a new build is ready, the entire execution process is triggered automatically within your CI/CD pipeline, whether it’s Jenkins, Azure DevOps, or another provider. This eliminates manual hand-offs and ensures that testing is no longer a separate phase, but an integrated part of development itself.
Next, Qyrus shatters the linear testing bottleneck with massive parallel testing. Instead of running tests one by one, our platform dynamically allocates resources, spinning up clean, temporary environments to run hundreds of tests simultaneously across a secure and scalable browser and device farm. It’s the difference between a single-lane road and a 100-lane superhighway. This is how we transform test runs that used to take hours into a process that delivers feedback in minutes.
The Bottom Line: Measuring the Massive ROI of Agentic Orchestration
A sophisticated platform is only as good as the results it delivers, and this is where the Qyrus SEER framework truly changes the game. By replacing slow, manual processes and brittle scripts with an autonomous team of agents, this approach delivers a powerful and measurable test automation ROI. This isn’t about incremental improvements; it’s about a fundamental transformation of speed, cost, and quality.
Slash Testing Time and Accelerate Delivery: By orchestrating parallel testing across a scalable cloud infrastructure, Qyrus shatters the testing bottleneck. This allows organizations to shorten release cycles and dramatically increase developer productivity. Teams that embrace this model see a staggering 50-70% reduction in overall testing time. What once took an entire night of regression testing now delivers feedback in minutes, giving your business a significant competitive advantage.
Eliminate Maintenance Costs and Reallocate Talent: The Healer agent directly attacks the single largest hidden cost in most QA organizations: script maintenance. By automatically fixing broken tests, Healer allows organizations to reduce the time and effort spent on test script maintenance by an incredible 65-70%. This frees your most valuable engineers from low-value repair work, allowing you to reallocate their expertise toward innovation and complex quality challenges that truly move the needle.
Enhance Quality and Deploy with Bulletproof Confidence: Speed is meaningless without quality. By intelligently deploying agents like Rover to explore untested paths, the Qyrus SEER framework dramatically improves the effectiveness of your testing. This smarter approach leads to a 25-30% improvement in defect detection rates, catching critical bugs long before they can impact your customers. This allows your teams to release with absolute confidence, knowing that quality and speed are finally working in perfect harmony.
Conclusion: The Dawn of Autonomous, Self-Healing QA
The Qyrus ‘Execute’ stage fundamentally redefines what it means to run tests. It transforms the process from a slow, brittle, and high-maintenance chore into a dynamic, intelligent, and self-healing workflow. This is where the true power of agentic orchestration comes to life. No longer are you just running scripts; you are deploying a coordinated squad of autonomous agents that execute, explore, and even repair tests with a level of speed and efficiency that was previously unimaginable.
This is the engine of modern quality assurance—an engine that provides the instant, trustworthy feedback necessary to thrive in a high-velocity, CI/CD-driven world.
But the mission isn’t over yet. Our autonomous agents have completed their tasks and gathered a wealth of data. So, how do we translate those raw results into strategic business intelligence?
In the final part of our series, we will dive into the ‘Report’ stage. We’ll explore how the Qyrus SEER framework synthesizes the outcomes from its multi-agent attack into clear, actionable insights that empower developers, inform stakeholders, and complete the virtuous cycle of intelligent, autonomous testing.
Ready to Explore Qyrus’ Autonomous Test Execution? Contact us today!
APIs are no longer just pipes connecting systems. They’re the backbone of digital business. And as AI continues to dominate conversations in every industry, one thing is becoming clear: there’s no AI without APIs. That’s exactly why we’re heading to API Days London next month.
This year’s theme hits close to home: “No AI Without API Management.” Over three days, the conference will dig into how API-first architecture, scalability, security, and AI-enhanced management are shaping the way modern businesses build intelligent systems. For the qAPI team, powered by Qyrus, where API testing and quality assurance meet real-world AI workflows, it’s the perfect place to learn, share, and connect.
Why We’re Excited About API Days London
API Days is a tech event where the global API community shows up. You’ll see product owners, API architects, developers, and QA leaders all tackling the same challenges: how do we make APIs faster, safer, smarter, and ready for AI-driven environments?
The sessions are designed to go beyond theory. Think hands-on workshops, real-world case studies, and discussions that don’t just tell you what’s possible but show you how to do it. For us, it’s a chance to explore how API management ties directly into quality engineering, and how testing practices need to evolve if businesses want to stay competitive in an AI-first world.
Our qAPI team is especially excited to jump into the tracks focused on scaling, governance, and AI-driven API strategies. We’re looking forward to coming back with fresh ideas on how to embed API-centered QA into AI workflows because if APIs are powering intelligent systems, they need the same intelligent approach to testing.
Two Sessions You Can’t Miss with Raoul Kumar
We’re proud that Raoul Kumar, our Director of Platform Development & Success at Qyrus and qAPI, will be taking the stage not once, but twice.
📍 COMMERCIAL 2 📅 September 22, 2025 ⏰ 4:05 – 4:55 PM Workshop: Test APIs in the Cloud — No Code. Just Chrome.
This hands-on session strips API testing back to its essentials. Forget complicated frameworks or clunky setups, Raoul will walk you through how to run tests directly from your browser. No code, no hassle. Just Chrome and the cloud. You’ll see how this approach makes testing simpler for both devs and QA teams while fitting seamlessly into modern CI/CD pipelines.
And that’s just the start.
📍 COMMERCIAL 2 📅 September 24, 2025 ⏰ 9:30 AM – 9:55 AM Keynote: The Future of API Testing: No Code, Just Cloud and Chrome
In this keynote, Raoul will zoom out from the technical details to talk about the bigger picture: how QA needs to evolve in the age of AI and why APIs are at the center of it all. Expect to hear about the challenges enterprises are facing, the opportunities no-code brings to the table, and how qAPI, Powered by Qyrus, is helping organizations future-proof their API testing strategy.
Come Meet Us at the qAPI (powered by Qyrus) Booth
Of course, we’re not just speaking, we’re setting up camp on the show floor too. Swing by the qAPI/Qyrus booth to meet our team, see live demos of our platform, and chat about your QA challenges.
And because no conference is complete without some fun, we’ll also be running a raffle with special prizes throughout the event. Stop in, say hi, and you just might walk away with more than new API testing ideas.
Why This Matters for You
If you’re working in product, development, or QA, you know the pressure. Release cycles are shrinking. Expectations are rising. And AI is amplifying both the opportunity and the complexity of building great digital experiences. That’s why events like API Days London are so important.
For us, it’s about connecting with peers who are asking the same questions we are: How do we embed testing into API-first, AI-driven ecosystems? How do we make quality a competitive advantage instead of a bottleneck? And how do we simplify testing so teams can actually move at the speed of innovation?
See You in London
We couldn’t be more excited for Apidays London 2025. Between Raoul’s workshop on September 22, his keynote on September 23 at 9:30 AM, and our booth filled with demos, raffles, and great conversations, we’re looking forward to connecting with as many of you as possible.
For us, the takeaway is simple: No AI without APIs. And no innovation without quality.
Software development has hit hyperdrive. Groundbreaking AI tools like Devin, GitHub Copilot, and Amazon Code Whisperer are transforming the SDLC landscape, with AI assistants now contributing to a substantial volume of code. But as engineering teams rocket forward, a critical question emerges: what about QA?
While development speeds accelerate, traditional quality assurance practices are struggling to keep up, creating a dangerous bottleneck in the delivery pipeline. Legacy methods, bogged down by time-consuming manual testing and automation scripts that demand up to 50% of an engineer’s time just for maintenance, simply cannot scale. This widening gap doesn’t just cause delays; it creates a massive test debt that threatens to derail your innovation engine.
The answer isn’t to hire more testers or to simply test more. The answer is to test smarter.
This is where a new paradigm, agentic orchestration, comes into play. We’d like to introduce you to Qyrus SEER, an intelligent, autonomous testing framework built on this principle. SEER is designed to close the gap permanently, leveraging a sophisticated AI orchestration model to ensure your quality assurance moves at the speed of modern development.
The QA Treadmill: Why Old Methods Fail in the New Era
Developers are not just coding faster; they are building in fundamentally new ways. At tech giants like Google and Microsoft, AI already writes between 20-40% of all new code, turning tasks that once took hours into scaffolds that take mere minutes. This has created a massive velocity gap, and traditional QA teams are caught on the wrong side of it, running faster just to stand still.
The Widening Gap: Is Your QA Keeping Pace?
AI is revolutionizing development, but traditional QA methods are struggling to keep up.
AI-Accelerated Development
67% of developers are using AI assistants, according to a survey.
At major tech companies, AI already accounts for 20-40% of new code.
Moving at unprecedented speed.
GAP
Traditional QA
35% of companies say manual testing is their most time-consuming activity.
Up to 50% of test engineering time is lost to script maintenance.
Running faster just to stand still.
The breakdown happens across three critical fronts:
The Manual Testing Bottleneck: The first casualty in this new race is manual testing. It’s an anchor in a sea of automation. When developers deploy AI-generated code with unprecedented speed, manual processes simply cannot keep up. It’s no surprise that 35% of companies identify manual testing as the single most time-consuming activity in their test cycles, making it a guaranteed chokepoint.
The Crushing Weight of Maintenance: For those who have embraced automation, a different nightmare emerges. Traditional, script-based automation is incredibly brittle. As AI-accelerated development causes applications to change more rapidly, the maintenance burden becomes unsustainable. Teams spend more time fixing old, broken tests than they do creating new ones to cover emerging features, trapping them in a reactive, inefficient cycle.
The Growing Skills Gap Crisis: Perhaps the most significant barrier is the human one. There’s a stark paradox in the industry: while a massive 82% of QA professionals recognize that AI skills will be critical in the coming years, a full 42% of today’s QA engineers lack the machine learning expertise needed to adopt these new tools. This crisis delays the implementation of effective agent orchestration, leaving teams without the internal champions required to lead the charge.
The AI Skills Gap: A House Divided
There’s a disconnect between acknowledging the need for AI skills and possessing them.
The Acknowledged Need
82%
Of QA professionals agree that AI skills will be critical for their careers in the next 3-5 years.
The Current Reality
42%
Of QA engineers currently lack the machine learning and AI expertise required for implementation.
Intelligent Agentic AI Orchestration: Meet the Conductor of Chaos
The old model is broken. So, what’s the solution? You can’t fight an AI-driven problem with manual-driven processes. You need to fight fire with fire.
This is where Qyrus SEER introduces a new paradigm. This isn’t just another tool to add to your stack; it is a fundamental shift in how quality is managed, built upon one of the most advanced AI agent orchestration frameworks available today. Think of SEER not as a single instrument, but as the conductor of your entire testing orchestra. It intelligently manages the end-to-end workflow, ensuring every component of your testing process performs in perfect harmony and at the right time. This is the future of testing, a trend underscored by the fact that 70% of organizations are on track to integrate AI for test creation, execution, and maintenance by 2025.
At its core, SEER’s power comes from a simple yet profound four-stage cycle:
Sense → Evaluate → Execute → Report
This framework dismantles the old, linear process of test-then-fix. Instead, it creates a dynamic, continuous feedback loop that intelligently responds to the rhythm of your development lifecycle. It’s a system designed not just to find bugs, but to anticipate needs and act on them with autonomous precision.
The SEER Framework: How Agentic Orchestration Works
A continuous, intelligent cycle that automates testing from end to end.
SENSE
Proactively monitors GitHub for code commits and Figma for design changes in real-time.
EVALUATE
Intelligently analyzes the impact of changes to identify affected APIs and UI components.
EXECUTE
Deploys the right testing agents (API Bots, UI Test Pilots) for a precision strike.
REPORT
Delivers actionable insights and integrates results directly into the development workflow.
Inside the Engine of Agentic AI Orchestration
SEER operates on a powerful, cyclical principle that transforms testing from a rigid, scheduled event into a fluid, intelligent response. This is the agentic orchestration framework in action, where each stage feeds into the next, creating a system that is constantly learning and adapting.
Sense: The Ever-Watchful Sentry
It all begins with listening. SEER plugs directly into the heart of your development ecosystem, acting as an ever-watchful sentry. It doesn’t wait to be told a change has occurred; it observes it in real-time. This includes:
Monitoring your repositories like GitHub for every code commit, merge, and pull request.
Observing design platforms such as Figma to detect UI and UX modifications as they happen.
This proactive monitoring means that the testing process is triggered by actual development activity, not by an arbitrary schedule. It’s the first step in aligning the pace of QA with the pace of development.
Evaluate: From Change to Actionable Insight
This is where the intelligence truly shines. Once SEER senses a change, it doesn’t just react; it analyzes the potential impact. It uses predictive intelligence to understand the blast radius of every modification, enabling it to pinpoint where defects are most likely to occur. For instance:
When a developer commits code, SEER parses the changes to identify precisely which APIs and backend services are affected.
When a designer updates a layout in Figma, SEER maps those visual changes to the corresponding user journeys and test scenarios.
This deep analysis is what sets AI agent orchestration frameworks apart. Instead of forcing your team to run a massive, time-consuming regression suite for a minor change, SEER eliminates the guesswork and focuses testing efforts only where they are needed most.
Execute: The Precision Strike
Armed with a clear understanding of the impact, SEER launches a precision strike. It orchestrates and deploys the exact testing agents required to validate the specific change. This is adaptive automation at its best.
For backend changes, it can deploy API Bots to conduct targeted tests on the impacted services.
For frontend modifications, it uses the Qyrus Test Pilot (QTP) to execute UI tests that reflect the new designs.
Crucially, these are not brittle, old-fashioned scripts. SEER’s execution is built on modern AI principles, where tests can automatically adapt to UI changes without human intervention, solving one of the biggest maintenance challenges in test automation.
Report: Closing the Loop with Clarity
The final stage is to deliver feedback that is both rapid and insightful. SEER generates clear, concise reports that detail test outcomes, code coverage, and performance metrics. But it doesn’t just send an email. It integrates these results directly into your CI/CD pipeline and development workflows, creating a seamless, continuous feedback loop. This ensures developers and stakeholders get the information they need instantly, allowing them to make confident decisions and accelerate the entire release cycle.
The Old Way vs. The SEER Way
Feature
Traditional QA (The Bottleneck)
Qyrus SEER (Agentic Orchestration)
Trigger
Manual start or fixed schedules
Real-time, triggered by code commits & design changes
Scope
Run entire regression suite; “test everything” approach
Intelligent impact analysis; tests only what’s affected
Maintenance
High; brittle scripts constantly break (up to 50% of engineer’s time)
Low; self-healing and adaptive automation
Feedback Loop
Slow; often takes hours or days
Rapid; real-time insights integrated into the CI/CD pipeline
Effort
High manual effort, high maintenance
Low manual effort, autonomous operation
Outcome
Slow releases, test debt, missed bugs
Accelerated releases, high confidence, improved coverage
The SEER Payoff: Unlocking Speed, Confidence, and Quality
Adopting a new framework is not just about better technology; it’s about achieving better outcomes. By implementing an intelligent agentic orchestration system like SEER, you move your team from a state of constant reaction to one of confident control. The benefits are not just theoretical; they are measurable.
Reclaim Your Time with Adaptive Automation
Imagine freeing your most skilled engineers from the soul-crushing task of constantly fixing broken test scripts. SEER’s ability to adapt to changes in your application’s code and UI without manual intervention directly combats maintenance overhead. This is not a small improvement. Organizations that implement this level of intelligent automation see a staggering 65-70% decrease in the effort required for test script maintenance. That is time your team gets back to focusing on innovation and complex quality challenges.
Enhance Coverage and Boost Confidence
True test coverage isn’t about running thousands of tests; it’s about running the right tests. SEER’s intelligent evaluation engine ensures your testing is laser-focused on the areas impacted by change. This smarter approach dramatically improves quality and boosts confidence in every deployment. The results speak for themselves, with teams achieving up to an 85% improvement in test coverage using AI-generated test cases and a 25-30% improvement in defect detection rates. You catch more critical bugs with less redundant effort.
Accelerate Your Entire Delivery Pipeline
When QA is no longer a bottleneck, the entire development lifecycle accelerates. SEER’s rapid feedback loop provides the insights your team needs in minutes, not days. This radical acceleration allows you to shrink release cycles and improve developer productivity. Companies leveraging intelligent automation are achieving a 50-70% reduction in overall testing time. This is the power of true agent orchestration—it doesn’t just make testing faster; it makes your entire business more agile.
Riding the AI Wave: Why Agentic Orchestration Is No Longer Optional
The move towards intelligent testing isn’t happening in a vacuum; it’s part of a massive, industry-wide transformation. The numbers paint a clear picture: the AI in testing market is experiencing explosive growth, with analysts forecasting a compound annual growth rate of nearly 19%. AI-powered testing is rapidly moving from an exploratory technology to a mainstream necessity. This isn’t a future trend—it’s the reality of today.
The AI Testing Market at a Glance
Market Indicator
Projection
Implication for Your Business
Market Growth (CAGR)
~19%
The industry is rapidly shifting; waiting means falling behind.
AI Tool Adoption by 2027
80% of Enterprises
AI-augmented testing will soon be the industry standard.
Current Tester Adoption
78% of testers have already adopted AI in some form.
Your team members are ready for more powerful tools.
Primary Driver
Need for Continuous Testing in DevOps/Agile
AI orchestration is essential to keep pace with modern CI/CD.
This wave is fueled by the relentless demands of modern software delivery. Agile and DevOps methodologies require a state of continuous testing that older tools simply cannot support. Modern CI/CD pipelines are increasingly embedding AI-powered tools to automate test creation and execution, enabling the speed and quality the market demands. Organizations are no longer asking if they should adopt AI in testing, but how quickly they can integrate it.
The trajectory is clear: the industry is moving beyond simple augmentation and toward fully autonomous solutions. Research predicts that by 2027, a remarkable 80% of enterprises will have AI-augmented testing tools. The future of quality assurance lies in sophisticated ai agent orchestration frameworks that can manage the entire testing lifecycle with minimal human intervention. Adopting a solution like SEER is not just about keeping up; it’s about positioning your organization for the next evolution of software development.
Your Next Move: Evolve or Become the Bottleneck
Quality assurance is at a crossroads. The evidence is undeniable: traditional testing methods cannot survive the speed and complexity of AI-enhanced software development. Sticking with the old ways is no longer a strategy; it’s a choice to become the bottleneck that slows down your entire organization.
Qyrus SEER offers a clear path forward. This isn’t about replacing human insight but augmenting it with powerful, intelligent automation. True AI orchestration frees your skilled QA professionals from the frustrating tasks of script maintenance and manual regression, allowing them to focus on what they do best: ensuring deep, contextual quality. By embracing this strategic shift, organizations are already achieving 50-70% improvements in testing efficiency and 25-30% better defect detection rates.
The window for competitive advantage is narrowing. The question is no longer if your organization should adopt AI in testing, but how quickly you can transform your practices to lead the pack.
Stop letting your testing pipeline be a bottleneck. Join our waitlist and be an early tester and discover how Qyrus SEER can bring intelligent, autonomous orchestration to your team.
Jerin Mathew
Manager
Jerin Mathew M M is a seasoned professional currently serving as a Content Manager at Qyrus. He possesses over 10 years of experience in content writing and editing, primarily within the international business and technology sectors. Prior to his current role, he worked as a Content Manager at Tookitaki Technologies, leading corporate and marketing communications. His background includes significant tenures as a Senior Copy Editor at The Economic Times and a Correspondent for the International Business Times UK. Jerin is skilled in digital marketing trends, SEO management, and crafting analytical, research-backed content.
