Qyrus Named a Leader in The Forrester Wave™: Autonomous Testing Platforms, Q4 2025 – Read More

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APIs are no longer just powering applications — they’re powering AI agents. Gartner’s new Market Overview for API and MCP Testing Tools sizes this market at $582 million in 2026, forecasting growth to approximately $760 million by 2029 as enterprises scale AI agent and Model Context Protocol (MCP) integrations. Qyrus is listed among the example vendors profiled in the report. 

What’s Inside the Report 

  • Why Gartner sees AI agents and MCP as new integration surfaces that traditional API testing wasn’t built to validate 
  • The four vendor categories shaping this market — pure-play API testing, software testing platforms, API management, and open source — and the trade-offs of each 
  • Gartner’s mandatory and optional capability set for evaluating tools, including protocol coverage, contract testing, service virtualization, and AI-assisted test generation 
  • A directory of example vendors in the space, including Qyrus 

Why This Matters for Your Team 

Gartner’s research notes that MCP adoption is outpacing the maturity of commercial testing capabilities — only 14% of software engineering leaders say they haven’t incorporated MCP into their architecture at all. That gap is exactly where unified platforms need to prove themselves: supporting REST, GraphQL, and SOAP testing today while building out validation for MCP servers and agent-driven workflows. 

Qyrus platform takes the same unified approach — functional, process, and performance testing for REST, SOAP, and GraphQL APIs, backed by AI-assisted test generation (Nova AI) and no-code test building — so teams aren’t stitching together separate tools as MCP and agent testing requirements mature. 

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

SAP ECC’s December 2027 mainstream maintenance deadline has turned S/4HANA migration from a long-range IT initiative into a boardroom forcing function. Extended maintenance may buy time through 2030, but it adds cost without reducing the custom-code debt, integration risk, and testing bottlenecks that make large SAP transformations fail. 

That is the risk this whitepaper addresses. It shows why SAP modernization programs stall, where defects hide across custom ABAP, Z-objects, integrations, data migration, and regression cycles, and how Qyrus unifies application intelligence with autonomous testing to help enterprises prove every critical process before cutover. 

What this whitepaper holds 

Why SAP modernization is now a timing risk, not just a technology project 

Understand how the 2027 maintenance sunset, extended-maintenance premiums, and realistic 18–36 month enterprise migration timelines compress the decision window for CIOs, CTOs, SAP leaders, and transformation sponsors. 

The two blind spots that make S/4HANA programs overrun 

See why unseen dependency risk and manual regression testing create the same failure loop: teams migrate what they do not fully understand, then test only what they remember to test. The whitepaper explains how undocumented ABAP, custom objects, RFCs, IDocs, BAPIs, Fiori journeys, APIs, and adjacent legacy systems create hidden production risk. 

A 25-point transformation minefield mapped to Qyrus capability 

Explore the recurring technical and operational failure points that slow SAP programs, including custom-code testing, data migration validation, hybrid landscape integration, regression bottlenecks, test-data provisioning, Fiori and mobile gaps, environment drift, security role testing, and executive readiness visibility. 

How QModernize and QAssure work as one closed loop 

Learn how QModernize builds a live dependency knowledge graph and scopes what to retain, refactor, or retire, while QAssure auto-generates and self-heals regression suites across SAP GUI, Fiori, APIs, web, mobile, and data layers. Together, they connect discovery, remediation, validation, and continuous run-state intelligence. 

What measurable impact looks like in practice 

  • Up to ~88% reduction in testing effort from a Qyrus production engagement. 
  • Regression cycles compressed from days to hours through AI-powered, impact-based automation. 
  • Testing effort targeted directly at the 40–60% program-cost drain associated with validation, regression, UAT, and hypercare. 
  • Continuous governance visibility across remediation progress, test coverage, integration health, self-healing rates, defect leakage, and cutover readiness. 

By the end of this whitepaper, you’ll understand 

  • Why waiting until 2027 creates a migration timeline that may already be too compressed for complex SAP estates. 
  • How undocumented dependencies and manual regression interact to create avoidable go-live risk. 
  • Which 25 friction points QA leaders, architects, SAP teams, and SIs must account for before migration execution. 
  • How a unified QModernize + QAssure engagement reduces risk without replacing the SI or disrupting existing governance tools. 
  • What low-friction next step fits your role: a 2–4 week readiness assessment for decision-makers or a 30-day pilot for QA teams. 

The Rules Changed. Did Your QA? See Why UK Fintechs Are Making QA Central to Operational Resilience. 

In 2025, the FCA fined Monzo £21.1 million. Months earlier, it fined Nationwide £44.1 million. Neither penalty was for a defective feature — both were for governance and control infrastructure, including the systems meant to test and monitor operations, that failed to scale at the same pace as customer growth. 

That’s the paradox at the heart of UK fintech today. The market that pioneered Open Banking and built some of the world’s most admired digital-native banks is also the most heavily scrutinised retail financial market on earth. The FCA’s Consumer Duty, the PRA’s operational resilience rules, and the financial liability shift for Authorised Push Payment fraud all place a continuously rising bar on every firm that touches UK retail money — and none of it leaves room for testing practices built for a slower era. 

What this whitepaper holds 

Why QA is now a boardroom risk, not a release gate 

Testing has stopped being a final functional check before launch. It’s now the primary operational control UK regulators expect firms to evidence continuously. This whitepaper explains why QA has become central to operational resilience — and what happens when it isn’t. 

Five systemic pitfalls breaking UK fintech testing 

Explore the recurring failure patterns across UK banking, payments, and insurance technology, including: 

  • Consumer Duty’s outcomes-based testing problem 
  • Open Banking’s third-party integration blind spot 
  • the synthetic-data dilemma undermining AML and fraud models 
  • hyper-scale transaction volatility that static load testing can’t simulate 
  • the APP fraud liability shift demanding continuous, behavioural testing 

Why manual and scripted QA can’t close the gap 

See why testing built around manual effort or static automation scripts structurally cannot keep pace with the combination of UK regulatory intensity and fintech release velocity — and what’s replacing it. 

How a modular, agentic testing approach answers each gap 

Learn how Web, Mobile, API, and Data testing — unified by Test Orchestration and elevated by Qyrus SEER, an autonomous agentic testing framework — give UK fintechs continuous, evidence-backed test coverage across every regulated customer journey. 

What measurable impact looks like in practice 

The whitepaper includes five UK banking case studies and an independent Forrester study, with outcome metrics such as: 

  • 213% ROI with payback in under 6 months (Forrester TEI™) 
  • 90%+ test coverage achieved across multiple UK banking engagements 
  • Test execution cut from 2 days to 9 minutes in one regulated UK bank 
  • 150% increase in testing efficiency through real-device, real-browser automation 

By the end of this whitepaper, you’ll have a clearer understanding of: 

  • where UK fintech QA risk is really coming from 
  • why Consumer Duty and operational resilience rules have changed what “good testing” means 
  • what a modular, AI-powered, agentic testing strategy looks like in practice 
  • how five UK banks and fintechs turned testing from a bottleneck into a competitive advantage 
  • how to move from periodic QA to continuous, autonomous quality assurance 

Because UK regulatory scrutiny isn’t going to ease up — but your testing can get a lot smarter. 

This whitepaper gives you a practical look at how to build testing for the realities of Consumer Duty, operational resilience, Open Banking, and APP fraud liability — without slowing down the releases your business depends on. 

Discover how agentic, AI-powered SAP testing helps enterprises reduce upgrade risk, accelerate validation, and eliminate testing debt — from Transport Request to go-live. 

In 2026 SAP landscapes are moving faster than traditional QA can handle. With S/4HANA Cloud releases, bi-weekly hotfixes, Fiori automation challenges, integration complexity, and rising compliance demands, testing has become one of the biggest risk factors in enterprise transformation. 

What this whitepaper holds 

Why SAP QA is now a business continuity issue 

SAP updates no longer affect just IT. When testing fails, businesses face downtime, broken workflows, delayed operations, and costly hyper-care cycles. This whitepaper explains why quality assurance has become central to enterprise resilience. 

The six biggest reasons SAP updates fail 

Explore the major fracture points in modern SAP testing, including: 

  • mandatory cloud release pressure 
  • custom code and configuration conflicts 
  • brittle Fiori automation 
  • test data and compliance bottlenecks 
  • integration blind spots 
  • the business–IT skills divide 

Why traditional testing approaches are no longer enough 

See why manual testing, legacy automation, and late-stage regression models are too slow, too fragile, and too expensive for modern SAP environments. 

How Qyrus enables shift-left SAP quality engineering 

Learn how Qyrus starts earlier than conventional testing tools — validating changes at the Transport Request level before they move downstream into broader landscapes. 

Discover how Agentic Regression Suite (ARS) and DataChain reduce test maintenance, accelerate automation, and solve one of the biggest SAP QA bottlenecks: test data preparation. 

What measurable impact looks like in practice 

The whitepaper also includes a real-world case study and outcome metrics such as: 

  • 88% reduction in test effort 
  • 50% faster test execution 
  • 60x reduction in test data effort 
  • 35% lower testing costs 

 

By the end of this whitepaper, you’ll have a clearer understanding of: 

  • where SAP testing risk is really coming from 
  • why existing QA models struggle under modern release cycles 
  • what an AI-first, agentic testing strategy looks like 
  • how to reduce effort without sacrificing coverage 
  • how to move from reactive QA to continuous quality engineering

Because SAP release cycles won’t slow down — but your testing can get smarter. 

Our whitepaper will give you a practical look at how to improve SAP QA with a platform designed for the realities of S/4HANA Cloud, Fiori, integration-heavy landscapes, and compliance-driven test environments. 

A data breach at a financial institution costs an average of $6.08 million, a figure 22% higher than in any other industry. Over 50% of members will switch financial institutions after a single poor digital experience, while over 80% of regression testing remains completely manual.  

This whitepaper is for QA directors, IT leaders, and application teams who have felt that gap. It shows, through published case study outcomes and an independent Forrester ROI study, how a unified, AI-powered platform closes them.  

Core Insights & Feature Deep-Dive 

What’s Inside the Whitepaper? 

This whitepaper maps the specific fracture points in credit union and regulated financial QA environments and names the limitations of the incumbent testing platform tools.  

Key Business Insights: 

  • 213% ROI Achieved: See the breakdown of an independent study showing a $1M net present value for top banking institutions.  
  • Sub-6-Month Payback Period: Learn how the platform pays for itself quickly through massive operational and quality efficiency gains today.  
  • $6.08M Data Breach Cost: Discover how automated testing reduces the frequency of costly defects.  
  • 80%+ Manual Testing Reduced: See how teams successfully transitioned slow manual regression suites into automation.  

Master the Qyrus Orchestration Toolkit 

Learn how to leverage specialized single-use agents that bridge the gap between legacy point solutions and true continuous automated validation:  

  • TestPilot Execution Agent: Instantly creates and executes tests from any live digital banking platform application screen autonomously.  
  • TestGenerator Tool: Converts user requirements and PDF specifications into automated, deep financial testing scenarios easily.  
  • Healer Script Automation: Automatically self-heals broken test scripts when monthly upgrades modify underlying digital banking UI components completely.  
  • Echo Synthetic Data: Generates realistic financial test data on demand that is parameterized and privacy-safe.  
  • API Builder Engine: Virtualizes APIs before live environments are available to enable early core integration pipeline testing.  
  • Rover Explorer Tool: Autonomously explores complex banking applications to identify unexpected anomalies or paths.

Ready to Eliminate Quality Failures? 

Fill out the form to download your copy of the guide and protect your critical banking member trust. 

As featured in The Forrester Total Economic Impact Study. 

“The real power of Qyrus is that we have this extremely broad testing capability in one tool, run in the cloud, and reusable across our teams.”  

— Executive Lead at Shawbrook Bank. 

Enterprise retailers are running $6.3 trillion worth of digital commerce on software quality models that were designed for a world of annual releases and monolithic applications. That world is gone. The gap between how retailers test their platforms and how customers experience them is no longer a technical problem — it is a revenue problem. 

This whitepaper maps the exact cost of that gap, and the three-layered path to closing it — from AI-powered full-spectrum testing across Web, Mobile, API, Data, and SAP, through to fully autonomous quality with the SEER framework. With Forrester TEI data, retail-specific scenarios, and a 12-month implementation roadmap included.

What’s Inside the Whitepaper? 

This is not a product brochure. It is a board-ready business case, built from Forrester TEI data, retail-specific failure scenarios, and a concrete implementation roadmap — designed to be shared with your CIO, CFO, and the engineering leaders who will execute the strategy. 

  • How distributed commerce architecture creates invisible, revenue-destroying failure points — and why traditional QA misses every one of them. 
  • The three structural gaps in legacy QA: maintenance debt, siloed channel testing, and synthetic load tests that don’t reflect peak-season reality. 
  • Full-spectrum AI testing across Web, Mobile, API, Data, and SAP — progressing to omnichannel orchestration and SEER autonomous testing. 
  • 3× faster test cycles, 80% maintenance reduction, and 200%+ ROI — what the numbers say and how to use them with your CFO. 
  • Why headless commerce creates seam failures that traditional UI testing never catches — and how contract testing closes the gap. 
  • A phased implementation plan with clear KPI targets at each stage — built to deliver measurable ROI before the transformation is complete. 

What the world’s most resilient retailers do differently.  

These are the six quality engineering principles that separate retailers who dominate peak season from those who post apology banners on their homepage. 

  • Test generation happens in the same sprint as feature development — not the next one. AI tools like NOVA generate test scripts from requirements, so QA is never the bottleneck before release. 
  • Validate complete customer transactions — mobile cart to web checkout, loyalty points earned in-app to POS redemption in-store. Siloed channel testing misses every cross-system failure that customers actually experience. 
  • Your payment gateway, logistics API, and tax engine all update on their own schedules. Contract testing catches schema drift before it becomes a checkout outage — without triggering real financial transactions. 
  • Stale inventory counts, mismatched pricing records, and broken personalization pipelines are not back-office problems. They are customer-facing failures. Validate data pipelines with the same rigor as your UI. 
  • Continuously run synthetic tests of your core purchase journey 24/7 — not just in the run-up to peak. Golden Path monitoring catches regression the moment it is introduced, not after it reaches customers during Black Friday. 
  • Self-healing test automation is the end-state — not a nice-to-have. Autonomous frameworks like SEER eliminate the maintenance tax entirely, freeing QA teams to focus on coverage expansion rather than script repair. 

Every millisecond of latency, every broken API, and every disjointed cross-channel moment is a direct withdrawal from your brand’s equity. The retailers who will lead the next decade are those who treat quality engineering as a capital investment in growth — not a checkbox before release. 

Poor software quality imposes a staggering $2.41 trillion tax on the U.S. economy every year. For most organizations, this isn’t just an abstract figure—it manifests as a direct drain on innovation, with developers spending up to 50% of their time fixing bugs instead of creating new value.

Stop letting fragmented tools and siloed processes slow your release cycles. Download our comprehensive whitepaper to discover how Qyrus Test Orchestration enables teams to validate complex, end-to-end user journeys while achieving more than 200% Return on Investment. 

What’s Inside the Whitepaper? 

This guide explores the rise of Orchestrated Testing Platforms and provides a technical roadmap for engineering leaders to eliminate the “hidden debt” in their engineering budgets. 

Key Business Insights: 

  • Sub-6-Month Payback: Learn how the platform pays for itself in less than half a year through massive productivity gains. 
  • $557,000 in Cost Avoidance: Discover how proactive testing reduces the frequency of costly production downtime. 
  • 90% Automation Levels: See how teams successfully transitioned manual regression suites into repeatable, automated processes. 

 Master the Qyrus Orchestration Toolkit 

Learn how to leverage the six core technical features that bridge the gap between fragmented automation efforts and true end-to-end quality: 

  • Multi-Protocol Workflow Creation: Seamlessly combine Web, Mobile, API, and Desktop scripts in a single, unified execution flow. 
  • Visual Node-Based Design: Empower your entire team with a codeless, drag-and-drop interface for defining complex logic. 
  • Data Propagation: Create realistic test scenarios by using output data from one test as the direct input for another. 
  • Workflow Organization: Eliminate “asset chaos” with a centralized, hierarchical folder structure for all testing assets. 
  • Flexible Scheduling: Set up one-time or recurring execution patterns (daily, weekly, or monthly) to ensure continuous validation. 
  • Centralized Reporting: Gain a single-pane-of-glass view of execution data, historical trends, and pass/fail rates. 

Ready to Break the Bottleneck? 

Fill out the form to receive your copy of the whitepaper and start your journey toward high-velocity quality. 

As featured in the Forrester Total Economic Impact™ Study.  

“The beauty of Qyrus is that you can build a scenario and string add-in components of all three [mobile, web, and API] to create an end-to-end scenario.”

— CTO of a Digital Bank.

Does your “QA Department” consist of your Lead Developer hoping nothing breaks on Friday?

Growing businesses face a brutal reality: you must release features immediately to survive, yet a single critical bug could cost you your biggest client. You don’t have the luxury of massive QA departments or endless release cycles. Instead, your developers often double as testers, creating a dangerous friction where speed cannibalizes quality.

This whitepaper outlines a “force multiplier” strategy for lean teams. It moves beyond theory to show how AI agents act as the dedicated QA staff you can’t afford to hire, allowing a small squad to deliver enterprise-grade reliability.

What You'll Learn in This Whitepaper
  • The “Force Multiplier” Strategy: How to use AI agents as “fractional experts” that allow a 5-person team to output the quality of a 50-person department.
  • Escaping the “Fix-It-Later” Trap: Why the traditional “test-last” model is bankrupting your innovation budget—and how to shift left without slowing down.
  • The ROI of Autonomous Quality: How to achieve a payback period of less than 6 months and get $2 of work for every $1 spent on intelligent automation.
  • Leveling the Playing Field: How SMBs are using agentic orchestration to bypass legacy integration headaches and compete directly with enterprise giants.
  • Founders & CTOs: Who need to scale their product’s user base 10x without hiring 10x more QA staff.

  • Engineering Leads: Who are tired of wasting their best developers’ time on manual regression testing and script maintenance.

  • Product Managers: Who want to stop choosing between meeting a launch deadline and ensuring a bug-free release.

Sneak Peek: The Cost of Waiting

The market isn’t waiting for you to hire more testers. With the AI testing market projected to grow at an 18.7% CAGR, your competitors are already automating the mundane.

“Investing in AI-powered quality is no longer just an option; it is a critical business imperative. Companies that invest now in intelligent test design and self-healing automation will unlock faster releases and superior products, while laggards risk technical debt and market irrelevance.”

Stop trading speed for quality. Download the blueprint to autonomous, self-healing testing.

The Velocity Gap in BFSI Software Quality

Why Traditional QA Fails Modern Finance

The BFSI sector faces immense pressure to deliver rapid digital transformation, but outdated, manual QA has become a bottleneck. AI accelerates innovation but introduces unpredictable behaviors that legacy approaches can’t handle. Fragmented toolchains and slow, error-prone testing expose banks to security risks, costly inefficiencies, and customer churn.

Download this whitepaper to learn how to:
  • Address non-determinism in AI-powered financial systems
  • Move from reactive bug-finding to proactive trust engineering
  • Integrate holistic, automated testing across web, mobile, and APIs
  • Quantify the bottom-line impact of engineered software quality
  • Core principles of Trust Engineering for BFSI institutions
  • Qyrus platform’s role in enabling unified, intelligent, and automated QA.
  • Case study: 200% ROI for a leading UK bank using agentic QA.
  • Strategies to protect customer data, enhance user experience, and reduce manual testing effort.

Driving the Future of Quality Engineering

Empowering enterprises to accelerate testing with AI-native autonomy

We are proud to announce that Qyrus has been recognized as a Leader in The Forrester Wave™: Autonomous Testing Platforms, Q4 2025. As enterprises face the need for faster, more autonomous testing to keep pace with AI-infused application development, we believe this recognition shows our commitment to delivering a robust, AI-powered SaaS platform at scale.

How Qyrus Stacks Up

In this evaluation, Qyrus received the highest scores possible (5.0) in the following criteria:

  • Testing AI Across Different Dimensions
  • Testing RAG Pipelines
  • Level of Autonomous Testing
  • Roadmap
  • Pricing Flexibility and transparency
  • Testing Agentic Tool Calling
 

The report evaluated 15 top providers in the market.

Here is what the Forrester report had to say about Qyrus in its vendor profile:

  • Qyrus suits enterprises seeking advanced AI-driven testing, multiagent orchestration, and robust validation of GenAI outputs at speed and scale.
  • Qyrus excels in AI testing dimensions, using heuristics and LLM to judge faithfulness, relevance, and coverage.
  • Its Sense to Evaluate to Execute to Report (SEER) orchestration framework and excellent agentic tool calling result in an above-par
    score for autonomous testing.

From Vision to Validation: Hear from Our Leaders

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. For more information, read about Forrester’s objectivity here .