Test Automation Using AI

Test Automation Using AI

Transform your Testing with AI-Powered Automation

Talk to our Experts

Automating businesses today has become an integral part of growth for enterprises. At Tx, we have developed AI-based test automation frameworks like Tx-Automate and analytics-based reporting dashboards like Tx-Insights. It uses AI/ML algorithms and intelligent automation to generate test automation code, build manual test cases from user stories, generate insightful analytics in dashboard, and make the test processes faster and smarter.

The need for Test Automation
using AI

  • Increased test life cycle 
  • Complexity of Modern Applications
  • High Frequency of Releases
  • Continuous Improvement
  • Improved Accuracy and Consistency
  • Enhanced Test Coverage
  • Efficient Resource Utilization
  • Rapid Feedback Loop
  • Self-Healing Tests
  • Cost Savings
  • Scalability Issues
need for Test Automation using AI

Business Benefits

Get In Touch
  • Reduced Time to Market
  • Improved Software Quality
  • Cost Efficiency
  • Enhanced Test Coverage
  • Better Resource Allocation
  • Increased Productivity
  • Improved Scalability
  • Faster Feedback Loop
  • Reduced Human Error
  • Data-Driven Insights

Why Choose Tx?

Automated Code Generation
Automated Code Generation

Tx-Automate, our in-house accelerator, as an AI engine analyzes the manual test cases and generates test scripts automatically, supporting multiple programming languages including Java, C#, JavaScript, and Python. Using AI, it specifically reduces automation development effort, enhances accuracy, and significantly accelerates the scripting process.

DevOps
Manual Test Case Generation

Tx-Automate generates manual test cases, examining the user stories and expanding them into human-readable test cases. This feature aids in ensuring detailed test coverage and encourages collaboration between manual and automation testing teams. 

software testing and QA testingxperts
Advanced Error Resolution using AI Reporting

Leveraging AI algorithms, Tx-Automate provides intelligent insights and suggestions for issue resolution by analyzing test reports. It identifies patterns, root causes, and potential solutions, thereby expediting the debugging and issue resolution process.

API and Microservices Testing practice
Manual Test Case Generation using Tx-GPT

We use AI to generate manual test cases from requirements and user stories, ensuring thorough coverage and enhancing collaboration between development and QA teams.

Next-gen Tools and Technologies
Integration with Third-Party Tools

We help businesses integrate with third-party tools like test management, defect management, CI integration, cloud service providers and code quality and code coverage analysis tools. 

automation testing using AI

How Tx Stands Out in Offering Test Automation Using AI

Invested in R&D for decades, and being an innovation-based organization, our TCoE has developed modular, integrated, compatible and reusable test automation assets. Tx-Automate integrates into your delivery pipelines seamlessly, delivering significant scripting effort savings.

Our team of experts help you transform your digital assurance process with Tx-Automate, featuring AI-Powered automated code generation in Java, C#, JavaScript, and Python, saving costs and delivering effective automated test results.

Speak to an expert

In your line of work, we know every minute matters.


    Recent Insights

    February 10, 2026

    BLOG

    Enterprise Cloud Migration Strategy: A Step-by-Step Roadmap for Regulated Industries

    This enterprise cloud migration strategy blog shares a step-by-step roadmap for compliance-heavy environments. It covers cloud migration strategy types, planning for cloud data migration, phased execution, and cloud migration best practices to reduce risk, improve audit readiness, and optimize performance and costs after migration.

    Read More

    February 9, 2026

    BLOG

    Modern QE for Digital Banking: Addressing Advanced Challenges with AI

    The blog discusses why digital banking needs AI-driven quality engineering to improve reliability, security, and compliance through predictive defect detection, self-healing automation, and synthetic test data, supported by CI/CD pipelines and observability to reduce outages, fraud risk, and release delays.

    Read More

    February 3, 2026

    BLOG

    QE Strategies for Financial Services: From Release Quality to Runtime Trust in Fraud Prevention

    Financial fraud now emerges at runtime, not release. This blog explores how AI-driven Quality Engineering enables real-time validation, behavioral analysis, and proactive fraud prevention for modern financial services.

    Read More

    February 2, 2026

    BLOG

    Why TCoE Programs Struggle to Deliver Measurable Business Value

    Many Test Center of Excellence programs fail not because of tools or budgets, but due to unclear ownership, over-standardization, and misaligned execution models. This blog breaks down where TCoEs lose momentum, why tool-first approaches stall, and how enterprises can build scalable, business-aligned TCoEs that deliver sustained value.

    Read More

    January 28, 2026

    BLOG

    AI Agent Evaluation: What Accuracy Alone Can’t Tell You

    Read More