Top 9 Continuous Testing Service Providers Powering Agile Delivery

Testing

July 8, 2025

Agile software development may be fast, but without continuous testing, it won’t go far. As enterprises move to next-gen application development and maintenance (ADM), quality assurance must evolve from a post-delivery function into a fully embedded, intelligent process. That’s where continuous testing plays a defining role.

Today’s continuous testing is not a separate QA phase. It is an always-on, AI-supported capability that works across software development, operations, and infrastructure. From microservices and CI/CD pipeline testing to ERP and SaaS workloads, testing must be continuous, automated, and orchestrated at scale.

According to ISG Provider Lens™ Next-Gen ADM Services US 2024 report, organizations are prioritizing continuous testing to accelerate release cycles, reduce production issues, and improve performance predictability. This shift is especially critical as GenAI adoption, observability tooling, and SRE-led engineering become core to ADM success.

This blog explores how continuous testing has changed, what role AI in software testing plays, and which nine providers stand out in delivering testing at the speed and complexity of modern software development.

What Continuous Testing Means Today

Continuous testing is not just about running automated scripts. It is about embedding a testing mindset, infrastructure, and toolchain across every phase of the CI/CD pipeline.

Key features of modern continuous testing include:

End-to-end test coverage: functional, performance, security, and compliance
Shift-left and shift-right testing: proactively identify issues early and simulate behavior under real-world conditions
AI/ML integration: automate test creation, defect prediction, and root cause analysis
Test orchestration platform-led automation: centralize and manage tests across microservices, APIs, and containerized architectures
DevSecOps alignment: embed security testing as code, not as a separate phase

This approach is transforming how enterprises think about quality, not as a final measure, but as a continuous signal of release readiness for every software development increment.

Why Continuous Testing Is Now Critical

Software environments have become too complex, fast-paced, and interconnected for traditional QA to keep up. Several structural changes are driving the widespread adoption of continuous testing:

Agile Application Development Demands Real-time QA
Development teams now release every week, not every quarter. Traditional QA phases that come after development simply cannot support this pace.

GenAI Accelerates Testing at Scale
AI is being used to write test cases, identify risk areas, and auto-resolve test failures. For example, LLMs trained on test libraries can now generate scenario-based coverage in minutes.

Cloud-native Systems Require Elastic Testing
Testing microservices across dynamic, container-based environments needs scalable infrastructure and real-time orchestration that adapts to changing states.

Security and Compliance Are Always-On
Continuous compliance testing is now standard in BFSI and healthcare, where policy violations cannot wait for post-deployment reviews.

What Sets the Top Continuous Testing Service Providers Apart

In evaluating continuous testing service providers, enterprises should look beyond automation skills and assess the provider’s ability to integrate, scale, and adapt. Key differentiators include:

AI-driven test orchestration platforms that manage volume and complexity
Frameworks and accelerators tailored to ERP, SaaS, and industry-specific systems
Native integration into CI/CD and observability platforms
Shift-left capabilities for early test coverage, and shift-right for production assurance
Flexibility in pricing, that is, POD models, subscription-based, or outcome-linked, aligned with software development velocity

Best Continuous Testing Companies for Next-Gen ADM

The report identifies these companies, listed alphabetically, as Leaders in continuous testing for their maturity in test automation, performance engineering, and GenAI alignment:

Apexon
Apexon delivers continuous QA through AI-led, end-to-end testing embedded across the software lifecycle. Its GenAI accelerator unifies user story generation, test development, and requirement coverage. Focused on speed and quality, Apexon’s continuous testingimproves productivity in digital-first sectors like retail and healthcare.
Birlasoft
Birlasoft focuses its continuous testing on enterprise platforms like SAP, Oracle, and Salesforce, supported by proprietary frameworks like TruAUT and TruABOV. With over 15 Testing CoEs and AI-powered automation, it ensures quality across ERP and SaaS workloads with strong alignment to Agile application development.
Cigniti
Cigniti’s BlueSwan™ platform powers continuous testing with AI, ML, and test automation components like Verita and Velocita. Through specialized CoEs and test automation tools, it enables DevOps QA, performance testing, and regulatory compliance across sectors including medical devices, retail, and BFSI.
Eviden (Atos Group)
Eviden integrates AI in software testingthrough its scriptless test frameworks and QA bots, supporting continuous validation in regulated environments. With strong SAP automation and GenAI partnerships, its solutions embed testing into CI/CD cycles and deliver test orchestration platform capabilities for high-assurance domains.
Hexaware
Hexaware delivers continuous testing through its AI-powered Tensai® for Autonomous Testing platform, which supports autonomous validation across functional and non-functional domains. The modules within the Tensai® for Autonomous Testing suite cover multichannel automation, big data validation, service virtualization, and performance engineering. Its strong adoption of GenAI and flexible pricing models underlines its software development expertise.
Persistent Systems
Persistent’s domain-specific continuous testing spans from LIMS to financial messaging systems. Its application development and maintenanceclients benefit from GenAI-driven quality engineering, covering shift-left automation, test data management, and real-time insights. With over 200 frameworks and deep CI/CD integration, Persistent ensures precise, scalable testing.
Qualitest
Qualitest stands out for its advanced AI in software testingcapabilities, particularly through its Qualisense accelerator and Qualigen for SAP automation. Its continuous testing solutions integrate AR/VR, blockchain, and IoT, while enabling full-lifecycle test automation that accelerates delivery, especially in regulated industries like pharma and BFSI.
Tech Mahindra
Tech Mahindra combines CI/CD pipeline testingwith AI-led platforms like MAGiX and CONPASS to drive performance assurance, automation, and predictive insights. Its continuous testing services are embedded with DevSecOps and observability, enabling early defect detection, faster time-to-market, and reliable deployments across verticals like telecom and healthcare.
UST
UST offers scalable continuous testingthrough its AI-based NoSkript™ platform, which automates the full test lifecycle. Its domain-driven testing accelerates quality across BFSI, healthcare, and telecom. UST’s global delivery and AI-based tools improve productivity, reduce rework, and deliver real-time decision support across QA functions.

The Hexaware Approach

Hexaware’s platform-led approach, driven by its Tensai^® for Autonomous Testing platform, emphasizes not just test automation but autonomous orchestration for modern software development programs. Tensai^® for Autonomous Testing:

Enables unified management of functional, performance, and non-functional tests, with AI-assisted scheduling, remediation, and prioritization.
Provides multichannel test automation, including mobile, web, and voice.
Handles large-scale data and ETL testing with schema validation and data masking.
Virtualizes services for faster testing of dependent systems.
Embeds performance engineering across the life cycle, using synthetic traffic and AI simulations.

A leading continuous testing services provider, the company’s approach to outcome-based pricing, especially POD and subscription options, gives clients financial clarity and flexibility. For example, a global financial services firm used Hexaware’s Tensai® for Autonomous Testing platform to cut regression testing time by 40%, integrating it with its CI/CD toolchain to support weekly releases without quality compromises.

How Industries Are Using Continuous Testing

Continuous testing is not one-size-fits-all. Different industries adopt it to meet distinct business needs. Take these examples. continuous regulatory updates and API-first architectures require continuous testing to validate compliance, security, and uptime across all channels in the banking industry. Electronic health records, patient portals, and telemedicine applications must meet HIPAA standards—testing is embedded to ensure data integrity and patient safety. Smart factories rely on IoT and edge software. continuous testing ensures interoperability, data flow integrity, and real-time analytics across systems.

Addressing the Top Continuous Testing Challenges

Modern ADM and software development environments face several testing challenges, which continuous testing providers are actively solving:

Tool sprawl: integrated orchestration platforms consolidate toolchains across QA teams
Incomplete coverage: AI generates test scenarios automatically, ensuring edge cases aren’t missed
Security blind spots: vulnerability scans are embedded in CI/CD pipelines, catching risks early
Lack of outcome focus: continuous testing now links testing effort directly to business outcomes—fewer defects, better releases, faster cycles.

What the Future Holds for Continuous Testing

Looking ahead, continuous testing will evolve from a supporting function to a core ADM intelligence layer. Emerging trends include:

LLM-driven test case generation using business documentation and user stories
Autonomous TestOps, merging observability and testing data for self-healing QA environments
SLA-backed coverage models, where vendors commit to defect escape rate thresholds
Industry-specific test kits, enabling faster onboarding in regulated or niche sectors

Continuous Testing: The Backbone of Scalable ADM

In a world where release velocity is a competitive edge, Continuous Testing is no longer optional. It’s the backbone of resilient, scalable, and intelligent software delivery. Organizations that embed QA into every layer of their development and operations processes not only avoid downtime but also release faster, adapt better, and innovate with confidence. The ISG-recognized providers leading this space aren’t offering testing as a service. They’re delivering testing as a platform.

Looking to scale application quality without slowing delivery? Let’s talk.

About the Author

Nidhi Alexander

Chief Marketing Officer

Nidhi Alexander is the Chief Marketing Officer at Hexaware, responsible for developing and building the brand and driving growth across its suite of technology services and platforms. She is responsible for brand, content, digital marketing, social media, corporate initiatives, industry analyst relations, media relations, market research, field marketing, and demand generation across channels.

Nidhi has been anchoring market influencer relationships globally for Hexaware before taking over the marketing function. Within two years, she completely transformed Hexaware’s position across rankings from the industry analyst community. She has also helped build a strong sales channel via advisor-led deals for Hexaware.

A recognized and accomplished marketing professional known for breakthrough results, Nidhi brings in diverse experience across brand building, analyst and advisor relations, field marketing, academic relations, employer branding, journalism, and television production over the last two and half decades.

Before Hexaware, she was in leadership positions in firms like Infosys and Mindtree. She is a recipient of the Chairman’s award at Infosys, Mindtree, and Polaris. She started her career in journalism with Star Television (News Corp) and was associated with several award-winning news and current affairs programs like Focus Asia, National Geographic Today, Star Talk, and Prime Minister’s Speak.

Nidhi holds a degree in English Literature from Jesus and Mary College, Delhi University, and a Masters in English Journalism from the Indian Institute of Mass Communication, Delhi. She currently resides in Bridgewater, New Jersey, with her husband and two children.

FAQs

Next-Gen Application Development and Maintenance (ADM) refers to modern practices and methodologies that enhance software development and maintenance processes. This includes leveraging Agile frameworks, integrating DevOps practices, utilizing AI and automation, and focusing on business outcomes rather than just technical deliverables.

Traditional ADM often relies on lengthy development cycles and rigid processes, whereas Next-Gen ADM emphasizes agility, rapid deployment, and continuous feedback. It promotes cross-functional teams, automated testing, and iterative development to quickly adapt to changing business needs.

Key benefits include faster time-to-market, improved product quality, enhanced collaboration between teams, better alignment with business objectives, and increased ability to respond to market changes. Additionally, automation and AI can significantly reduce manual effort, leading to cost savings.

AI plays a crucial role in Next-Gen ADM by automating repetitive tasks, enhancing decision-making through data analysis, and providing tools for intelligent testing and observability. AI-driven insights can improve project management and help teams optimize their workflows.

Organizations can ensure success by promoting a culture of collaboration, investing in upskilling their workforce in Agile and DevOps practices, leveraging the right tools and technologies, and defining clear business outcomes to measure project success.