Intelligent testing automation
Transform your quality assurance practices with a structured suite of test automation services that use technologies like artificial intelligence (AI), machine learning (ML) and blockchain to help you standardise and scale your processes and make continuous improvements that reduce risk.
Accelerate your projects with smarter testing
Our intelligent test automation services help your organisation adopt scalable, intelligent automation practices to accelerate testing, reduce release risk and enable continuous quality. We offer everything from foundational automation to next-generation, AI-led and cognitive testing solutions.
By combining domain-led test engineering with AI/ML capabilities, we support modern delivery models with high reusability, faster feedback and lower maintenance overhead. From frameworks to robotic process automation (RPA) and smart contract testing, we deliver automation strategies that evolve with your technology landscape.
At NashTech, intelligent automation is not just about faster execution, it is about building smarter, resilient and future-ready test ecosystems. Our approach blends engineering depth, platform versatility and AI innovation to deliver sustainable automation value.
Solve your testing challenges
Legacy frameworks struggle with dynamic applications, leading to flakiness and high rework.
Manual script creation and lack of AI assistance slow down validation, especially in agile and CI/CD environments.
Smart contracts, ML models and hyper automation platforms are often excluded from test strategies.
Traditional tools require developer expertise, limiting contributions from quality assurance (QA) analysts and business testers.
Static scripts do not adapt to application changes or usage patterns, resulting in coverage gaps and inefficiencies.
Standardise, scale and innovate with intelligent test automation solutions
Development and implementation of automation frameworks across web, API and mobile layers. Includes test data automation and environment orchestration to streamline execution and ensure consistency.
Use of AI/ML to enhance automation with features like model validation, bias and drift detection, autonomous test generation and testbots. Visual and user experience (UX) testing ensures user interface (UI) consistency across platforms.
Incorporates advanced techniques such as self-healing automation, chaos testing for validation under failure conditions and RPA for regression-heavy workflows.
Automation of smart contract testing, focusing on logic validation, permission handling, transaction consistency and blockchain-specific error scenarios.
Empowerment of business users and functional testers through low-code and no-code tools to contribute to test automation without deep programming expertise.
See how our intelligent test automation could help you
Quality is not limited to being a testing function. It is also crucial to delivering scalable, reliable and accessible software. At NashTech, we approach quality strategically to reduce compliance risks and enable faster releases tailored for multiple channels.
Reusable frameworks for web, API, and mobile
Modular architecture ensures scalability and faster onboarding across delivery streams.
Autonomous test design and maintenance
Use of AI models to auto-generate test cases and self-correct scripts based on UI/API changes.
Blockchain smart contract testing
Programmatic validation of smart contracts with automated checks for logic flaws and security.
Lower automation maintenance costs
Self-healing and reusable assets reduce effort over time.
Better risk detection with intelligent insights
Observability integration and AI help detect root causes and prioritise testing.
Reusable frameworks for web, API, and mobile
Modular architecture ensures scalability and faster onboarding across delivery streams.
Autonomous test design and maintenance
Use of AI models to auto-generate test cases and self-correct scripts based on UI/API changes.
Blockchain smart contract testing
Programmatic validation of smart contracts with automated checks for logic flaws and security.
Lower automation maintenance costs
Self-healing and reusable assets reduce effort over time.
Better risk detection with intelligent insights
Observability integration and AI help detect root causes and prioritise testing.
Client outcomes
Discover how our intelligent test automation solutions delivered high quality outcomes for our clients
Case study: Robot Framework reduces testing time and effort for leading insurance broker
reduction in time and effort for testing
staff able to manage and execute automated tests
The collaboration between our onshore and offshore teams has not only improved the stats, figures and efficiency, but it has also changed the perception within the business.
Markerstudy Group, one of the largest insurance brokers in the UK, needed to improve the efficiency of its regression testing cycles. These cycles were long and required manual effort, impacting its ability to deliver software updates swiftly. NashTech developed an automated testing framework using Robot Framework, reducing testing time and effort by 90%. This allowed non-technical staff to manage and execute automated tests, freeing up the team for higher-value tasks.
Case study: Major retailer automates more than 1,500 test cases to improve system performance and accelerate release cycles
automation coverage increased testing efficiency
reduction in manual testing
increase in performance to support a 300% increase in user load
Loblaw Digital builds and operates the digital properties of Loblaw Companies Limited, a Canada-based retailer with 22 brands serving millions of customers. It partnered with NashTech to ensure the functional correctness and non-functional SLA adherence of newly developed multi-tenant platform services supporting multiple business lines. More than 1,500 test cases for both web and mobile applications were automated, significantly reducing production bugs and improving system performance, while reducing manual testing efforts and accelerating release cycles.
Case study: Healthcare pioneer accelerates release cycles
manual testing
testers on critical areas
NashTech has been an exceptional partner, significantly reducing our production bugs and improving system performance. Their automation expertise has greatly cut our manual testing efforts and accelerated our release cycles. Their adaptability and organisation are outstanding.
Philips Healthcare is a pioneer in the medical alerts category in North America and partnered with NashTech to accelerate the release cycles of healthcare applications and allow for quicker deployment of updates and new features. Manual testing was optimised by integrating human expertise with automation, focusing testers on critical areas like exploratory testing while automation managed repetitive tasks.
Case study: Global provider of payroll, HR and workforce management solutions automates testing of data pipelines to enhance its SDLC
increase in test coverage
reduction in regression testing cycle
decrease in feedback time
Ultimate Kronos Group (UKG) is a global provider of payroll, HR service delivery and workforce management solutions. It partnered with NashTech to improve efficiency by automating the testing of data pipelines, which has ensured broader test coverage and enabled the UKG IT team to identify issues earlier in the software development lifecycle (SDLC).
Frequently asked questions
Our solution integrates with your existing set up because our frameworks are CI/CD ready and support major tools like Jenkins, Azure DevOps, GitLab CI, and others.
We provide model validation, drift analysis, fairness checks and accuracy testing as part of our AI-powered automation.
We use self-healing locators and AI-based selectors to maintain tests across UI changes.
Yes, our LCNC solutions allow users to contribute without coding, with in-built governance and review workflows.
We support web, mobile (iOS/Android), APIs, blockchain platforms, RPA tools and LCNC platforms.
Our test solutions validate smart contract logic, edge cases, transaction states and access controls across blockchain networks.
This term refers to AI-assisted generation of test scenarios and data based on application models, requirement or usage logs.
Yes, we build RPA workflows that integrate with test pipelines for end-to-end regression and validation across applications.
We follow an automation-first mindset, embedding automation into every stage of the quality lifecycle from the outset. Our AI-integrated solutions leverage cognitive tools to accelerate test generation, improve coverage and detect defects earlier in the process.
Through future-ready accelerators – including self-healing frameworks, RPA and smart contract testing – we help organisations scale their automation for next-generation platforms and complex workflows.
Our vendor-neutral architectures enable seamless integration across tools and teams by promoting modular, scalable and tool-agnostic solutions. Backed by proven expertise across industries such as banking, healthcare, retail and manufacturing, we align test automation with your domain-specific priorities.
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