Welcome to our September update! As we continue to evolve the Qyrus platform, our focus remains squarely on enhancing your productivity and empowering your team to achieve more, faster. We believe in removing friction from the testing lifecycle, and this month’s updates are a direct reflection of that commitment.
We are excited to introduce powerful new capabilities centered around dramatic workflow acceleration, intelligent AI-driven assistance, and seamless CI/CD integration. From features that eliminate repetitive tasks to an AI co-pilot that can fix your scripts on the fly, every enhancement is designed to save you valuable time and make your testing efforts more intuitive and powerful.
New Feature
Build Faster, Not from Scratch: Now Clone Your Web Testing Functions!
The Challenge:
Users often need to create functions (e.g. File Uploads, Global Software Quality Assurance) that are very similar to ones they have already built. Previously, this required repetitive manual effort to recreate these similar functions from scratch, step by step, which was inefficient and time-consuming.
The Fix:
We have now introduced a “Clone” option for functions for project set-up in Web Testing. With a single click, users can create an exact copy of any existing function, which they can then rename and modify as needed.
How will it help?
This feature directly addresses the need for efficiency in test creation. It saves significant time and effort by allowing you to quickly duplicate complex, existing functions instead of recreating them. This allows you to build out your function library much faster and focus on tweaking the logic for new scenarios rather than on repetitive setup.
Improvement
Fix It Right the First Time: Introducing Detailed Error Handling!
The Challenge:
Previously, when users encountered an error during a test, the error messages could sometimes be generic. This lack of specific guidance increased the chances of making mistakes again when re-entering information, leading to a frustrating trial-and-error process.
The Fix:
We have implemented a more detailed and intelligent error handling system within Web Testing. Now, when the system detects an error, it will provide a clear, specific, and actionable message (e.g. “Test Scrip 3, No data table for parameterization step”) that pinpoints exactly what is wrong and often suggests how to correct it.
How will it help?
This enhancement provides immediate, clear guidance that helps you fix issues faster. It ensures consistency in your configurations and reduces manual errors by preventing guesswork. This ultimately speeds up project setup and improves your overall workflow efficiency, allowing you to build tests with greater confidence and speed.
New Feature
Take Control of Your Pipeline: Stop Executions on Demand!
The Challenge:
Previously, once a test execution was triggered in Test Orchestration, there was no way to stop it before it got completed. This lack of control meant that if a long-running suite was started by mistake, or if a low-priority job was tying up resources when a critical test needed to run, users had no choice but to wait.
The Fix:
We have now introduced a “Stop Execution” feature in Test Orchestration. Users will now see an option on any in-progress execution that allows them to immediately terminate the test run.
How will it help?
This feature gives you crucial, real-time control over your testing pipeline. You can now instantly:
Correct Mistakes: Immediately stop an execution that was triggered with the wrong configuration or data.
Prioritize with Agility: Free up valuable execution resources from a lower-priority task to run a more urgent, high-priority test.
This leads to more efficient use of your resources, prevents wasted time on incorrect runs, and provides the flexibility needed to manage a dynamic testing schedule.
Improvement
Set It Once: Unified Environment Selection for Test Orchestration!
The Challenge:
In the Service TO (Test Orchestration) section, users were required to select the environment individually for each script within a test. This process was time-consuming and repetitive, especially for tests containing a large number of scripts that all needed to run on the same environment. This also created an inconsistent experience, as other parts of the platform already offered a more efficient, test-level selection method.
The Fix:
We have updated the behavior in Service TO to align with user expectations and improve efficiency. You can now make a single environment selection at the test level, and this choice will automatically apply to all scripts contained within that test.
How will it help?
This enhancement significantly streamlines the test setup process. It eliminates unnecessary manual work by removing the need to select the same environment repeatedly for each script. This not only saves you a considerable amount of time, especially with large tests, but also provides a more consistent, intuitive, and user-friendly experience across the entire Test Orchestration module.
Improvement
Recorder Now Intelligently Fixes and Completes Your Tests!
The Challenge:
Test scripts, whether created manually or generated by AI, can sometimes be imperfect. They might contain incorrect or outdated locators, or they might be missing crucial steps needed to achieve the test’s objective. When these scripts were executed, they would simply fail, forcing the user into a difficult and time-consuming manual process of debugging, finding the broken locators, and identifying the missing logic.
The Fix:
We have introduced Context Based Execution, a powerful new AI-driven capability in Qyrus Recorder. Now, you can provide your high-level objective along with a potentially flawed test script. The AI engine (QTP) will then intelligently:
Heal incorrect locators by finding the correct elements on the page.
Add relevant missing steps by understanding the logical gaps in your test flow.
Proceed to complete the execution successfully using the corrected and completed script.
How will it help?
This feature acts as an AI co-pilot, dramatically accelerating your test creation and maintenance efforts.
Massively Reduce Maintenance: It goes beyond simple self-healing by fixing entire test flows, saving countless hours you would have spent debugging.
Create Tests Faster: You can start with an imperfect or incomplete script and let the AI intelligently correct and complete it, turning rough drafts into robust tests.
Increase Test Reliability: By fixing issues on the fly, it makes your test executions far more resilient to minor application changes or script errors.
Empower Your Team: It lowers the technical barrier for creating successful automated tests, allowing every team member to be more productive.
Improvement
Record Like a Human: Copy/Paste, TAB & ENTER Now Captured!
The Challenge: Previously, the Qyrus Recorder did not capture several common user actions when filling out web forms. Pasting text into a field was not recorded as a clean input, and crucial keyboard navigation like pressing TAB to move between fields or ENTER to submit a form was ignored. This forced users to manually add these steps after the recording was finished, which was time-consuming and made the recording process less intuitive.
The Fix:
We have significantly enhanced the Qyrus Recorder to make the recording experience more natural and complete. The recorder now automatically captures:
Copy & Paste: When you paste text into an input field, it is now recorded as a clean SET operation.
Keyboard Actions: Pressing the TAB and ENTER keys are now recognized and recorded as distinct steps in your script.
How will it help?
This update will save you a tremendous amount of time, especially when recording interactions with login pages or other large forms. You can now record the workflow exactly as you would perform it manually—pasting long values, tabbing between fields, and hitting enter to submit. This eliminates the need for numerous manual clicks and post-recording edits, creating a more accurate and complete test script from the very beginning and streamlining your entire automation workflow.
Improvement
At-a-Glance Clarity: qAPI Functional Reports Get a Major Upgrade!
The Challenge:
Previously, our qAPI functional reports had two main areas for improvement. First, an API test executed without any assertions could be ambiguously reported, not clearly indicating that no actual validation occurred. Second, users had to click into a detailed report to see the crucial HTTP status code of an API response, making it difficult to quickly assess results from the main overview page.
The Fix:
We have introduced two significant improvements to the functional reports page:
New “No Test Cases” Status: A new status, “No Test Cases,” will now be displayed for any API test that is run without any assertions.
New “Status Code” Column: We’ve added a “Status Code” column that provides an at-a-glance view of the API response. It includes a tooltip explaining the code’s meaning and uses a smart icon to indicate when an execution contains multiple APIs with the same or different status codes.
How will it help?
These enhancements provide you with richer, more actionable reports.
The “No Test Cases” status encourages better testing practices by clearly highlighting tests that need validation criteria to be meaningful.
The “Status Code” column saves you valuable time by providing critical response information directly on the main reports page, allowing for faster analysis and quicker identification of potential issues without needing to dig into detailed reports.
New Feature
From Complex to Clear: AI-Generated Summaries for Your API Workflows!
The Challenge:
Complex, multi-step API workflows, especially those created by automated features like Automap, can be difficult to understand at a glance. When a team member creates a new workflow, others in the workspace might have to manually analyze each step to grasp its overall purpose and logic, which can hinder collaboration and slow down reviews.
The Fix:
We have introduced a new AI Summary feature for qAPI workflows. This powerful feature automatically generates a concise, human-readable summary that explains the purpose and flow of the operations within a workflow. This summary provides an immediate, high-level overview of the test asset.
How will it help?
This feature significantly improves collaboration and understanding within your workspace.
Instant Clarity: It makes it easy for any team member to quickly understand what a workflow does without dissecting it.
AI Transparency: It works perfectly with features like Automap, providing a clear explanation of what the AI has built.
Faster Reviews: Peer reviews are more efficient, as the context is clear from the start.
Auto-Documentation: The summary acts as instant documentation, ensuring the purpose of your test assets is always well-understood.
New Feature
Power Up Your Pipeline: Trigger qAPI Functional Tests Directly from Jenkins!
The Challenge:
Previously, users who rely on Jenkins for their CI/CD pipelines lacked a simple, native way to trigger their qAPI functional tests. Integrating these tests required complex workarounds like custom API scripts, creating a disconnect between the build/deployment process in Jenkins and the API testing process in Qyrus, and hindering true end-to-end automation. The Fix:
We have now released a dedicated Jenkins plugin for qAPI. This plugin provides a simple and configurable build step that allows users to easily select and trigger their qAPI functional tests directly from within any Jenkins pipeline job.
How will it help?
This plugin provides seamless CI/CD integration, enabling true Continuous Testing. You can now:
Fully Automate Testing: Automatically trigger your API functional tests as a standard part of your build and deployment process.
Get Faster Feedback: Immediately validate your services post-deployment to catch issues earlier in the development cycle.
Eliminate Manual Work: Remove the need for brittle, custom scripts, saving significant time for your DevOps and development teams.
Ready to Accelerate Your Testing with August’s Upgrades?
We are dedicated to evolving Qyrus into a platform that not only anticipates your needs but also provides practical, powerful solutions that help you release top-quality software with greater speed and confidence.
Curious to see how these August enhancements can benefit your team? There’s no better way to understand the impact of Qyrus than to see it for yourself.
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.
Qyrus SEER Infographic: The Velocity Gap
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.
Qyrus SEER Infographic: The AI Skills Gap
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.
Qyrus SEER Infographic: The SEER Framework
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.
Qyrus SEER Infographic: The Old Way vs. The SEER Way
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 intelligentagentic 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.
Welcome to our August update! At Qyrus, we are driven by the goal of making every aspect of your testing journey more efficient, powerful, and intuitive. This August, we’ve delivered a host of significant upgrades with a special focus on overhauling the entire API testing experience, creating more powerful and resilient test automation, and enhancing overall platform reliability. From simplifying how you create and preview APIs to making your automated tests smarter and more robust, these updates are designed to remove friction and accelerate your path to delivering quality.
New Feature
Power Up Your Iterations: Introducing Nested Loops for Web Testing!
The Challenge:
Previously, users could not place one loop inside another, which made it difficult to automate complex scenarios requiring nested iterations. For example, testing every available size (inner loop) for every T-shirt style in a list (outer loop) would require complicated test structures or manual duplication of steps, which was inefficient and hard to maintain.
The Fix:
We have now introduced support for one-level nested loops in Web Testing. This allows users to place one loop directly inside another loop, enabling a more powerful and intuitive way to structure tests that need to iterate through multiple, related data sets.
How will it help?
This feature significantly enhances your ability to automate complex test scenarios. It helps you:
Automate Complex Scenarios: Easily handle tests that involve multiple, dependent data sets, like checking all links within each section of a webpage.
Save Time: Avoid duplicating test steps by creating elegant, nested loop structures that are more efficient to build and maintain.
Ensure Better Test Coverage: Systematically test all combinations between two sets of data, leading to more thorough and comprehensive test coverage with less effort.
Improvement
Resilient Loops: Gather All Results, Even with Failures!
The Challenge:
Previously, if a single step failed within a loop iteration, the entire loop would stop executing. This was problematic for data-driven tests where the goal is to process an entire dataset and see results for every item, as a single failure would prevent subsequent iterations from running and leave you with an incomplete report.
The Fix:
We have introduced a “Continue on Failure” option for loops in Web Testing. When this setting is enabled, a failure in one iteration will be logged in the report, but it will not halt the execution. The loop will proceed to the next iteration until all have been attempted.
How will it help?
This feature makes your automated tests more resilient and your results more comprehensive. It ensures that all iterations of your loop will run even if some fail, which is crucial for testing with dynamic data sets. This allows for complete, uninterrupted automation and provides a full execution report detailing the success or failure of every single iteration, giving you a complete picture of your test outcomes.
New Feature
Rock-Solid iOS Recordings: Video Service Upgraded for High-Volume Testing!
The Challenge:
Our iOS video recording service could become unstable under sustained, high usage. When a large number of parallel sessions were run (e.g., 500+ recordings over a few days), the service would sometimes stop accepting new recording requests. This resulted in situations where test reports were generated without the crucial corresponding video recording, hindering debugging and analysis.
The Fix:
Instead of relying on temporary server restarts, we have permanently addressed the root cause by re-architecting and optimizing the iOS video recording service. This enhancement ensures the service can now robustly handle a high volume of concurrent recording requests without degrading.
How will it help?
This update delivers significantly improved reliability and stability for iOS video recordings in Device Farm. You can now run numerous parallel test sessions with the confidence that a video recording will be successfully generated for each one, even during periods of peak usage. This ensures you always have the complete visual artifacts you need for thorough debugging and analysis.
Improvement
Reliable iOS Manual Sessions with Improved Connectivity
The Challenge:
Users attempting to start a manual testing session with an iOS device would sometimes encounter errors that prevented the session from launching successfully. These failures were often caused by underlying connectivity issues between our servers and the physical iOS devices in our device farm.
The Fix:
We have implemented and deployed key configuration changes on our backend servers to specifically address and resolve these connectivity problems. These adjustments create a more stable and robust connection pathway to our iOS devices.
How will it help?
This fix significantly improves the reliability of initiating manual sessions for iOS devices. You should now experience fewer session creation failures, allowing you to start your manual testing sessions more quickly and dependably, leading to a smoother and more efficient testing experience.
Improvement
API Previews, Unblocked: Seamlessly Preview APIs & Generate Assertions!
The Challenge:
Previously, users were unable to preview all their APIs directly within the platform. Technical limitations, particularly Cross-Origin Resource Sharing (CORS) issues, could often prevent a seamless preview experience, especially when attempting to check APIs from a local environment. This made it difficult to quickly inspect responses and validate endpoints before building out full test cases.
The Fix:
We have implemented new logic that enhances the API preview functionality, specifically enabling seamless previews from a local environment to our CloudClient. This change effectively resolves the underlying CORS issues. As part of this improvement, users can also now generate Nova assertions directly from the previewed API response.
How will it help?
This update provides a much smoother and more powerful API test design workflow. Users can now reliably preview all APIs without being blocked by CORS errors, allowing for quick and easy inspection of responses. The ability to generate Nova assertions directly from this preview dramatically accelerates test creation, reducing manual effort and helping you build comprehensive API validation steps faster than ever before.
New Feature
Effortless API Setup: Introducing the New, Intuitive qAPI Form!
The Challenge:
The previous form for manually entering API details could sometimes be complex or less than intuitive, especially for users who were not deeply technical. This could slow down the process of adding new APIs to the platform and might have presented a barrier for team members like manual testers or business analysts.
The Fix:
We have completely redesigned the form where users enter API details in qAPI. The new design streamlines the entire process from start to finish, with a strong focus on making it more intuitive and user-friendly for everyone.
How will it help?
This revamp significantly improves the user experience for manually creating APIs. The new, intuitive layout guides users through the process more clearly, making it faster and easier to add and configure APIs. This is especially beneficial for non-technical users, as it lowers the barrier to entry and empowers more team members to participate in setting up API tests, reducing errors and saving time.
Improvement
Enhanced API Versatility: Full Support for x-www-form-urlencoded
The Challenge:
Previously, our API testing capabilities did not include native support for the x-www-form-urlencoded body type. This is a common data format used by web applications, especially for submitting form data. Users who needed to test APIs that required this specific content type had to rely on custom workarounds or external tools, creating an efficiency gap in their workflow.
The Fix:
We have now added native support for the application/x-www-form-urlencoded body type within our API testing service. Users can now select this option and easily build their request using key-value pairs, just as they would with a standard web form.
How will it help?
This enhancement significantly expands the range of APIs you can test directly on our platform. It simplifies the process of testing endpoints that mimic web form submissions, eliminating the need for complex workarounds. This makes our API testing tool more versatile and ensures you can cover a broader spectrum of your application’s endpoints with ease and efficiency.
New Feature
From API to IDE: C# HttpClient Code Snippets Now Available!
The Challenge:
Previously, while our code snippet feature supported various languages, it lacked an option for C# developers using the standard HttpClient library. This meant C# developers had to manually translate the API requests they designed or tested on our platform into the necessary C# code, a process that could be time-consuming and prone to manual error.
The Fix:
We are expanding our code snippet generation capabilities with the addition of a new target: C# (HttpClient). Now, with a single click, users can instantly generate the C# code required to execute their configured API request using this popular library.
How will it help?
This feature provides a significant productivity boost for C# and .NET developers. It eliminates the need to write boilerplate HttpClient code for API requests, saving time and reducing the chance of transcription errors. Developers can now quickly generate and integrate tested API calls directly into their applications, streamlining the workflow from API design and testing to implementation.
Improvement
QAPI – under— Your Test Results, Delivered: Email Reports for Scheduled Executions!
The Challenge:
Previously, after scheduling a test execution, users had to manually return to the platform to check its status and retrieve the report once it was finished. There was no automated notification system to inform them of a successful completion or, more critically, if a test failed to start due to issues like an insufficient Virtual User Balance (VUB).
The Fix:
We have implemented an automated email notification system for all scheduled test executions. Now, when a scheduled test completes successfully, users will automatically receive an email with a downloadable report attached. Additionally, if a test fails to run because of an insufficient Virtual user balance, a specific alert email will be sent to notify the user of the issue.
How will it help?
This feature makes monitoring your scheduled tests effortless and proactive. You no longer need to manually check on test progress; results are delivered directly to your inbox for easy access and sharing. The immediate failure alerts for VUB issues are crucial for quickly resolving resource problems and ensuring your testing schedule proceeds without interruption, saving time and preventing missed test runs.
Ready to Accelerate Your Testing with August’s Upgrades?
We are dedicated to evolving Qyrus into a platform that not only anticipates your needs but also provides practical, powerful solutions that help you release top-quality software with greater speed and confidence.
Curious to see how these August enhancements can benefit your team? There’s no better way to understand the impact of Qyrus than to see it for yourself.
Save the Date 📅 September 3–5, 2025 📍 Santa Clara, CA
Get ready, Santa Clara!Qyrus is hitting the floor at API World 2025 from September 3–5, and we’re bringing the full power of our qAPI solution to the world’s largest API and microservices conference.
API World is where developers, architects, and enterprise teams come to learn, build, and connect. From sessions on API lifecycle best practices to deep dives into AI integration and API security, this year’s event is packed with insights, innovation, and action.
You’ll find the Qyrus team at Booth #400, led by Raoul Kumar, Director of Platforms for both Qyrus and qAPI. We’ll be showcasing how Qyrus delivers faster, smarter, and more scalable API testing and monitoring with automation, AI, and real-time visibility built into the platform.
Whether you’re launching a new API or scaling microservices across teams, we’ll show you how to test with confidence, cut down on debugging, and reduce release cycles.
Live platform walkthroughs
Real-time test case generation
Intelligent monitoring in action
Come see what next-gen API quality looks like, and how Qyrus is leading the charge.
Save the date and swing by Booth #400 at API World 2025, Santa Clara Convention Center. We’re ready to talk about testing, transformation, and what’s next in APIs.
Tired of automation that adds complexity without catching the critical defects that matter? It’s time to move beyond brittle scripts and firefighting. This whitepaper provides a strategic framework for orchestrating a truly intelligent quality process, turning your QA team from a bottleneck into a business accelerator.
The Automation Blind Spot: Why Are Critical Defects Still Slipping Through?
You’ve invested in automation. You’ve adopted AI tools. Yet, your team is still walking a difficult tightrope between the demand for unprecedented speed and the mandate for quality. The modern development lifecycle—an explosion of code changes from developers and AI assistants—creates a widening chasm between the pressure to accelerate and the need to protect the end-user experience.
This challenge is intensified by a very real talent bottleneck and the complexities of legacy system integration. The result? A reactive, late-cycle testing model that is fundamentally broken.
Exponential Costs: A defect found in production is exponentially more disruptive and expensive to fix than one caught in design.
Resource Drain: Developer time is diverted from innovation to firefighting emergency patches.
Business Risk: Customer churn and brand reputation are directly at risk with every escaped defect.
If this sounds familiar, it’s because incremental improvements are no longer enough. It’s time for a fundamental shift in strategy.
Assemble Your AI-Powered Quality Team
The answer isn’t more automation; it’s smarter, orchestrated automation. This whitepaper, The QA Leader’s Playbook, demonstrates how to move from a reactive testing posture to a proactive, predictive, and profitable one by augmenting your team with a suite of collaborative, intelligent agents.
The Transformative Impact of AI-Powered QA
80%
Reduction in Costly Production Defects
36%
Acceleration in Time-to-Market
20%
Decrease in Manual UAT Effort
Learn how to build a digital crew of AI colleagues, each with a distinct expertise, working tirelessly to handle the repetitive tasks and empower your engineers to focus on high-value, strategic problem-solving.
Inside the Whitepaper, You Will Discover:
The AI-Powered Team Blueprint: Meet our specialist agents—from TestGenerator to Healer—that form your new quality team.
The Shift-Left Framework in Practice: A step-by-step guide to embedding quality across the entire SDLC, from initial requirements to post-release maintenance.
The Unmistakable ROI: A breakdown of the Forrester TEI study results, showcasing a 213% ROI and a <6 month payback period driven by the Qyrus platform.
A Phased Adoption Roadmap: A clear, three-phase plan to de-risk your investment and guide your journey from a small pilot program to enterprise-wide AI orchestration.
Lead the Future of Quality
Adopting an AI-driven testing strategy is more than a solution to today’s challenges; it is a forward-thinking decision that future-proofs your entire quality assurance department.
Download your complimentary copy of The QA Leader’s Playbook and get the strategic framework needed to transform your QA function into a center of innovation.
Welcome to the third installment of our series on Agentic Orchestration. In our previous post, we explored the ‘Eyes and Ears’ of the operation—the Sense stage, which detects every change across the development ecosystem. But what happens next? In this chapter, we’re diving into the ‘Brain’ of the SEER framework: the intelligent Evaluate stage. If you’re just joining us, we recommend starting with Part 1 to grasp the foundational concepts.
How Qyrus Evaluates Change and Optimizes Testing
In software development, change is the only constant. But every change, no matter how small, introduces risk. How can you be confident that a minor code tweak won’t trigger a major application failure?
This is where the “Evaluate” stage of Qyrus’s SEER framework (Sense, Evaluate, Execute, Report) takes command. Building on the “Sense” stage which acts as the eyes and ears, the “Evaluate” stage is the strategic brain. It transforms raw data about changes into an intelligent, optimized testing strategy.
In this third installment, we’ll dissect how Qyrus performs its cognitive heavy lifting: analyzing the ripple effect of changes, generating the precise tests needed, and ensuring your testing efforts deliver maximum impact with minimum overhead.
Cognitive Crunch Time: From ‘What Changed?’ to ‘What Do We Do?’
The ‘Evaluate’ stage is where Qyrus flexes its AI muscle. Its primary goal is to answer the critical question that follows any detected change: “What is the smartest way to test this?” It achieves this through a sophisticated process of impact analysis, test creation, and strategy optimization.
Think of it as a lead detective arriving at a scene. The “Sense” stage has reported a change. Now, the “Evaluate” stage meticulously examines the evidence, traces potential connections, and formulates a precise plan of action. This ensures your testing is always laser-focused on the highest-risk areas, saving time and dramatically improving coverage.
Inside the Brain: How Evaluation Unfolds
The evaluation process isn’t a single action but a coordinated symphony of specialized AI components. It begins with a trigger and flows through a logical sequence to produce a master test plan.
1. The Reasoning Layer: The Command Center
The Reasoning Layer is the control center of the ‘Evaluate’ stage, orchestrating logical decision-making upon receiving a trigger from the Watch Towers. It acts as the brain of the operation, directing the flow of information and coordinating the actions of the Thinking Agents.
Imagine a conductor leading an orchestra. The reasoning layer analyzes the incoming information about the changes, assesses their potential impact, and then delegates tasks to specialized “Thinking” agents. It determines which agent is best suited to analyze the change, generate relevant test cases, and optimize the testing strategy. This intelligent delegation of tasks ensures that the evaluation process is efficient, effective, and focused on the areas that matter most.
2. The Thinking Agents: A Squad of AI Specialists
These are the specialized AI-driven models, or Single Use Agents (SUAs), that perform specific tasks within the ‘Evaluate’ stage. They are experts in their respective domains, working together to analyze the impact of changes, generate relevant test cases, and optimize the testing strategy.
Think of them as specialized detectives, each with their own unique skills and expertise. Some are experts in analyzing code, others in understanding user flows, and yet others in generating test cases. This specialization ensures that every aspect of the change is thoroughly evaluated, and the most effective testing strategy is devised.
The thinking agents include:
Impact Analyzer: This agent acts as the forensic expert. Using static analysis, dependency graphs, and historical data, it maps out the potential ripple effect of a code change. It answers the question: “If this line of code changes, which other modules, components, or APIs could be affected?”
Test Generator: Leveraging Natural Language Processing (NLP), this agent functions as the strategist. It compares updated requirements and the impact analysis against existing tests. It then dynamically generates new, relevant test cases and refines existing ones to ensure complete coverage.
UXtract: This agent is the visual design expert. It meticulously extracts and interprets UI/UX changes, mapping differences between design files (like Figma versions) to specific user flows and test steps. This guarantees that visual integrity and accessibility are never compromised.
3. The Context DB: The System’s Long-Term Memory
The Context DB serves as the memory bank of the ‘Evaluate’ stage, a central data store containing historical test results, system configurations, defect trends, and traceability data. The SUAs use the data in the Context DB as one of the inputs for their reasoning.
Imagine a detective’s case files, filled with past experiences, insights, and knowledge. The Context DB provides the Thinking Agents with valuable context and information to make informed decisions. This historical data helps them analyze the impact of changes more accurately, generate more relevant test cases, and optimize the testing strategy for maximum effectiveness.
4. The Orchestration Layer: The Conductor of the Evaluation Symphony
This layer’s objective is to coordinate and validate decisions from the Thinking Agents. Its function is to serve as an orchestrator or “meta-controller” that confirms which test sets should be executed and in which sequence, applying business rules and testing policies.
Imagine a conductor leading an orchestra, ensuring that each musician plays their part in harmony with the others. The Orchestration Layer takes the recommendations from the Thinking Agents and creates a cohesive testing strategy. It ensures that the tests are executed in the right order, with the right resources, and in line with the overall testing policies and business rules. This coordination and validation ensure that the testing process is efficient, effective, and aligned with the organization’s goals.
The Payoff: Intelligent, Optimized, and Comprehensive Testing
The ‘Evaluate’ stage provides several benefits that greatly improve the testing process:
Intelligent Test Creation: By dynamically generating relevant test cases based on changes and requirements, the ‘Evaluate’ stage reduces the manual effort required to create and maintain tests. The Test Generator considers existing scenarios and suggests new ones, ensuring comprehensive test coverage. This AI test generator not only saves time but also ensures that your tests are always relevant and up to date.
Optimized Test Execution: The stage prioritizes and sequences tests for maximum efficiency. This ensures that the most important tests are run first, allowing for faster feedback and quicker identification of critical defects. With test optimization, you can be confident that your testing efforts are focused on the areas that matter most.
Comprehensive Impact Analysis: The Impact Analyzer identifies affected components, ensuring complete test coverage. This helps to focus testing efforts on the areas most likely to be impacted by a change, reducing the risk of overlooking critical issues. Impact analysis ensures that no stone is left unturned in your quest for quality software.
By combining intelligent test generation, optimized test execution, and comprehensive impact analysis, the ‘Evaluate’ stage empowers teams to achieve unparalleled efficiency and effectiveness in their AI-driven testing efforts. It’s like having a team of expert testers and strategists working tirelessly behind the scenes, ensuring that your testing process is always one step ahead. With Qyrus SEER, you can say goodbye to guesswork and embrace a data-driven approach to testing, where every decision is backed by intelligent insights and optimized for maximum impact.
Conclusion: Evaluate to Elevate
The ‘Evaluate’ stage is the strategic heart of the Qyrus SEER framework, transforming raw change data into an actionable intelligence blueprint. It’s how we move from reactive testing to a predictive, optimized, and truly AI-driven strategy.
But a brilliant strategy is only as good as its execution. In the next part of our series, we’ll explore the ‘Execute’ stage, where this carefully crafted plan is put into action. Stay tuned to see how Qyrus orchestrates a fleet of agents to seamlessly run tests, gather results, and bring you one step closer to fully autonomous testing.
Qyrus, a leading AI-powered test automation platform, has been recognized in the latest Forrester report, “The Autonomous Testing Platforms Landscape, Q3 2025”.
Autonomous Testing Platforms (ATPs) leverage AI-driven test automation to accelerate time to value, mitigate strategic risk, enhance governance quality, and promote democratized testing and cross-team collaboration. The report emphasizes that organizations must choose from a diverse range of vendors to realize these advantages.
Forrester defines ATPs as “Platforms that combine traditional automation with AI and genAI agents to continuously perform increasingly autonomous testing tasks”. These platforms are capable of generating and executing a broad spectrum of functional and nonfunctional end-to-end tests across various products and applications, including those infused with AI, ensuring comprehensive and adaptive quality validation.
At Qyrus, we proactively embrace critical industry trends like AI and GenAI to best serve our customers. Our inclusion in Forrester’s “The Autonomous Testing Platforms Landscape, Q3 2025” reflects our commitment to leveraging cutting-edge technology for customer success and satisfaction, particularly as the market evolves towards increasingly autonomous and intelligent testing solutions.
At Qyrus, our suite of AI agents, including TestPilot, TestGenerator, TestGenerator+, Rover, Eval, API Builder, Echo, and Healer, are designed to transform the testing lifecycle. These agents automate critical tasks such as test creation, exploration, data generation, and self-healing, directly from URLs, application screens, or even JIRA tickets. This empowers teams to achieve greater efficiency and ensure superior software quality through intelligent, autonomous testing.
Explore This Research To:
Understand Forrester’s perspective on the value of ATPs: Learn how autonomous testing platforms can accelerate time to value through AI-driven test automation, reduce strategic risk, increase the quality of governance, and democratize testing and cross-team collaboration.
Discover why Qyrus is recognized in the Autonomous Testing Platforms Landscape: Gain insights into Qyrus’s focus, deployment models, and impact within the ATP market.
Learn about the key benefits ATPs offer product and application testers: Understand how ATPs help accelerate time to value by leveraging AI, reduce strategic risk through intelligent test orchestration, and democratize testing with no-code/low-code interfaces and natural language test authoring.
Gain insights into the evolving market dynamics and future of autonomous testing: Understand the shift from traditional scripting to AI-driven, agentic, and intent-based testing, and the challenges buyers face in this transforming market
Forrester, The Autonomous Testing Platforms Landscape, Q3 2025, Diego Lo Giudice with Chris Gardner, Angela Lozada, Kara Hartig, July 25, 2025.
