Testing is Being Rewritten by Intelligence and Engineering is Leading the Shift
Software releases are accelerating and products are becoming more connected. Devices, platforms, assets and physical operations are generating more complexity than traditional testing models can absorb.
At the same time, GenAI is disrupting the economics of quality. Unit testing, interface testing, integration testing, module testing, regression planning and reporting can now be automated with far greater speed and scale. Enterprises no longer need more manual testing effort. They need smarter assurance systems that reduce cost while improving coverage, traceability and release confidence.
HCLTech helps enterprises build intelligence into the testing lifecycle. We combine AI-led automation, engineering-domain expertise, reusable IP, cost-optimized internal toolsets, global labs and more than 10,000 testing engineers and automation testers. Together, these capabilities help validate software, embedded systems, devices and physical environments with greater speed, precision and cost control.
IPs and solutions
HCLTech-owned labs
Global customers
Locations
Testing engineers and automation testers
Years of engineering expertise
Patents granted
Engineering Intelligence into Every Layer of Testing
HCLTech does not treat AI as an automation add-on. We embed intelligence across the quality lifecycle—from test planning and design to execution, automation, triage, reporting and continuous learning.
Our strength is applying AI where engineering complexity, domain context, real-world environments, regulatory pressure and cost control matter. That includes software, enterprise applications, embedded systems, connected devices, edge environments, robotics, silicon, mechanical systems and physical operations.
Core propositions
- AI for testing
Use AI automation to plan, generate, optimize, select, execute, analyze and improve tests across the software and product lifecycle. - Testing AI
Validate AI applications, copilots, models and agents for accuracy, robustness, performance, governance and production readiness. - Testing AI-enabled products
Assure embedded intelligence, connected products and physical interactions through device automation, lab testing, hardware simulation and engineering-grade validation.
From Simulation to Real-World Impact: AI-led Testing Transformation across Software, Embedded and Physical Systems
HCLTech helps enterprises reduce testing effort, improve coverage and lower the lifecycle cost of quality through intelligent automation, domain-led engineering and built-in AI across the STLC.
Web applications and SDKs
Automate functional, regression and cross-platform validation.
Web services
Automate testing across connected devices, mobile apps and embedded systems.
Device automation
Automate testing across connected devices, mobile applications, embedded systems and device-led experiences.
Windows applications
Industrialize testing for desktop applications and platform-specific workflows.
Database automation
Validate data flows, database operations and backend systems.
Cloud operations
Support cloud-based testing, environment validation and remote execution.
Compatibility and interoperability
Validate cross-browser, cross-device, cross-platform and cross-system performance.
Hardware simulation
Use simulated environments to reduce dependency on scarce physical devices.
Agentic AI
Addressing skill gaps using purpose-built AI Agents; repetitive testing and workflow actions; A2A and integration across different applications
Security and performance
Automate repetitive testing, reporting and workflow actions.
Wir denken, dass diese Themen Sie interessieren könnten
Quality Intelligence from Requirement to Release—with Human Control Where It Matters
HCLTech’s assurance loop embeds AI across the STLC while keeping expert review in the loop for protocol, compliance, defect, checklist and release decisions.
Plan
Generate test cases, scrub test assets and map traceability across requirements, code, protocols and release evidence.
Design
Provision test data, service virtualization and test environments to reduce wait time and improve execution readiness.
Operate
Generate or update tests, select and execute the right scenarios, automate defect and result reporting, run regression and smoke testing, and trigger human review where required.
Execute
Automate regression, smoke, exploratory, execution, triage and bug logging workflows.
Automate
Support compliance testing, device testing, HIL/SIL/MIL validation, log analysis, script development and connected-device testing across BLE, NFC, BT, wireless and wired environments.
Report
Compile test reports, perform root-cause analysis and generate real-time quality insights for faster decisions.
Learn
Feed defects, telemetry, production behavior and expert decisions back into test design, automation assets and quality dashboards.
Human-in-the-loop governance
AI accelerates the heavy lifting. Human experts retain control where judgment matters — protocol review, checklist approval, test engine setup, defect validation, report approval and final release confidence.
Real-World Impact across Digital Platforms, Products and Physical Engineering
HCLTech turns intelligent test automation into measurable business, engineering and cost outcomes—from faster digital releases to smarter validation of complex products and physical systems.
Reduction in test automation effort
Increase in project margins
Reduction in field defects
Incremental test coverage
Cycle-time reduction
Test-cost reduction
Improvement in time-to-market
Next-generation myocardial protection technology is transforming how surgeons safeguard the heart during complex cardiac procedures
Read more
Discover how multi‑vendor O‑RAN radio interoperability was accelerated at scale using a fully virtualized lab environment—enabling faster validation, compliance, and time to market.
Learn more
Standardizing complex liquid cooling portfolios with a scalable, natural-refrigerant engineering platform
Learn more
This case study explores how HCLTech empowered the client to reimagine camera photography experience and expand their market reach.
Learn more
This case study examines the collaboration between HCLTech and the client in designing and deploying a state-of-the-art system.
Learn more
This initiative focused on enhancing software capabilities among professionals by introducing structured learning in Windows and Cloud technologies.
Read moreGenAI in Test Automation across Industries
HCLTech is applying GenAI in live testing engagements across medical, industrial, automotive, telecom and storage environments.
Medical device manufacturers
GenAI test case generation for embedded medical devices. Paid PoC delivered and successfully moved to the clients.
Medical imaging and diagnostic companies
Delivered GenAI-based test design and automated BDD feature generation.
Data storage solutions providers
Delivered a complete AI-driven test automation ecosystem to generate, validate, execute and monitor tests from specifications.
Automotive and telecom engagements
GenAI-enabled MIL/SIL testing, L2VPN/L3VPN AI-driven testing and real network testing are progressing across active client programs.
Trends and Insights
The purpose of this whitepaper is to automate visual testing using AI and CV innovations, enhancing UI design validation and reducing manual effort.
The whitepaper proposes a solution that leverages GenAI and RAG techniques to automate this process, thereby streamlining the software development and testing lifecycle
Explores an automated Azure security and compliance framework that detects misconfigurations, enforces governance, reduces risk and improves operational efficiency.
Discover how Gemini-powered AI and response libraries accelerate customer support, ensuring faster responses, consistent communication, governance and improved customer satisfaction.
Discover how visual intelligence enables resilient, scalable UI automation by overcoming locator fragility in modern, dynamic interfaces.
Ready to Build Quality that Adapts as Fast as Your Products?
Engineer intelligent test automation from requirement to release and from software to devices, embedded systems, cloud operations and physical environments.
Find what inspires and drives you
Frequently Asked Questions about Our Test Automation Solutions
AI-led test automation uses AI, analytics, reusable frameworks and automation platforms to accelerate test planning, generation, execution, reporting, defect analysis and continuous improvement.
HCLTech embeds AI across the quality lifecycle, combining reusable IP, domain expertise, HCLTech-owned labs and more than 10,000 testing engineers and automation testers to support assurance across software, devices, embedded systems and physical environments.
No. HCLTech positions AI as built-in intelligence across the STLC — helping enterprises plan, design, execute, automate, report and continuously improve testing outcomes.
HCLTech supports web applications, SDKs, web services, device automation, Windows applications, database automation, cloud operations, compatibility and interoperability testing, hardware simulation and BOT-led automation.
Core HCLTech Test Automation solutions include Agentic quality orchestration, GenAI-based UI automation, GenAI-based no-code automation framework, Electronic device automation testing, No-code automation accelerator, Telecom test automation platform, Change-based testing, Log analysis tool, Cybersecurity automation framework.
HCLTech reduces TCO through cost-optimized internal toolsets, reusable automation assets, AI-generated test assets, smart execution, self-healing automation, reduced manual effort and lower maintenance cost.
A platform that plans, generates, automates, selects, executes and learns across the software testing lifecycle.
It is a testing solution for hardware, embedded systems and application black-box testing.
HCLTech supports device automation, protocol validation, HIL/SIL/MIL testing, lab-based validation, hardware simulation, sensor and actuator testing, and connected-device testing across wireless and wired environments.
HCLTech validates AI systems for functional outcomes, accuracy, robustness, latency, observability, risk, safety, governance and responsible behavior.
Outcomes can include reduced automation effort, improved project margins, lower field defects, increased test coverage, reduced cycle time, lower test cost and improved time-to-market.
Enterprises can begin with a quality and automation assessment to identify current testing challenges, use-case priorities, tool maturity, cost drivers and opportunities to scale AI-led automation across applications, devices and operations.
