This 1 hour briefing will help you understand how Wipro's IntelliAssure offering helps for industry Transformation through AI & Consulting Excellence.
About this Professional Service offer:
In this 1 hour briefing, we will cover how IntelliAssure as a comprehensive platform is designed to streamline and enhance the Software Testing Life Cycle (STLC) with its suite of plug-and-play solutions. We will cover how it offers a range of tools and features that accelerate testing activities, improve efficiency, and ensure high-quality software delivery. By integrating seamlessly with existing tools and workflows, how IntelliAssure empowers teams to optimize their testing processes and achieve faster time-to-market. All these utilities compliment the tools available in the market.
Below are the tools listed under the IntelliAssure umbrella:
Test Asset Optimiser (TAO) helps manage growing regression test suites by using NLP to detect and merge duplicate test cases without losing coverage. This reduces suite size by up to 30% and cuts maintenance effort by 60–80%, leading to significant cost savings
Automation Failure Analysis (AFA) reduces the high manual effort involved in analyzing frequent automation script failures. It uses historical log data to predict failure categories across multiple formats, enabling faster diagnosis. With 80–95% accuracy and seamless integration, AFA cuts analysis effort by up to 50%.
Self-Heal works on Selenium and Playwright, it addresses the high maintenance effort caused by UI changes like locator updates in automation scripts. It automatically adapts and fixes scripts using rule-based logic and large language models (LLMs), reducing maintenance, improving stability, and accelerating release cycles.
PDF Validator automates the tedious and error-prone task of manual PDF content validation. It uses pixel/text comparison and rule-based analysis to detect even subtle changes, offering customizable rules and achieving up to 95% effort savings. Pdf validator uses LLM like GPT 4O for content validation.
Enterprise Dashboard solves the problem of fragmented data and inconsistent reporting by offering a real-time, unified view of project metrics. It provides a 360-degree perspective covering green metrics, performance, test execution, and defect trends. This eliminates manual data collation, enhances collaboration, and supports standardized reporting through reusable templates. Enterprise dashboard is built on Microsoft Azure Database for PostgreSQL with TimescaleDB, Power BI.
API Test Accelerator streamlines the slow and error-prone process of manual API test script creation. It auto-generates scripts from Swagger or Postman definitions and uses GenAI for ongoing maintenance, resulting in 60% faster automation, fewer errors, and consistently up-to-date test coverage.
Business Assurance improves visibility into end-to-end transactions across integrated environments. It monitors and analyzes business processes through centralized dashboards and root cause analysis, enabling faster issue identification and more effective monitoring. Application uses InfluxDB, Azure Monitor for providing transaction visibility
Test Data Management simplifies the challenge of managing reliable test data for automation. It reserves unique data for each script and generates synthetic data when needed, improving reliability, supporting parallel execution, and making maintenance easier.
Smart Data Validator tackles data mismatches and traceability issues after migration or ETL processes. It validates data across sources at scale, auto-generates queries, and integrates with CI/CD pipelines—enabling faster, more complete validation with no coding required, while ensuring privacy compliance.
Observability as Code Accelerator enhances operational visibility in complex environments by embedding observability elements—such as logs, metrics, traces, and alerts—directly into the code. Built on Azure Monitor, this enables proactive monitoring, accelerates issue detection by up to 30%, and supports scalable, agile DevOps practices
AI-Powered Chaos Engineering Accelerator brings intelligence to chaos testing in Kubernetes environments. Built on GPT 4O, It simulates failures using AI to uncover hidden issues and optimize recovery strategies, resulting in 30% better system resilience, 25% faster recovery, and reduced downtime.
Agentic AI-Powered Load Testing Accelerator overcomes the inefficiencies of manual load testing by using autonomous, AI-driven scaling and auto-teardown. It delivers 80% faster test cycles, 60% cost savings, and twice the accuracy in capacity insights.
Test Environment Manager addresses delays and errors caused by manual environment setup and tracking. It automates provisioning, configuration, and monitoring of test environments—reducing setup time, improving reliability, and enabling centralized control.
Please connect with us for more details.