100% Auditability Achieved in Retail Testing with UiPath & Gen AI 

Banner image

Client Overview

New features and updates increased the number of scenarios to test, and traditional testing couldn’t handle continuous retail updates, complex user journeys, and seasonal traffic surges.

A global retail enterprise was trying to release faster while still relying on manual test design, scripting, triaging, and reporting. Testing started taking longer, and the gaps widened from one release to the next.

Every Update Added More Pressure on Validation

Requirements for testing came in different formats, and QA engineers had to build test cases manually. Whenever there is a failure, teams step in to find out the root cause manually.

This made the entire process heavily dependent on manual effort, which led to slower validation and an increased risk of missed issues.
01

Unstructured Requirements

Requirements were inconsistent and required manual interpretation before testing could begin.

02

Manual Test Creation

The process was slow and inconsistent because test cases had to be written from scratch.

03

Skill-Heavy Scripting

Test script creation required specialized expertise, which limited speed and scalability.

04

Reactive Issue Analysis

Failures were addressed only after they occurred. Teams had to manually investigate issues, trace dependencies, and identify root causes.

Taking a Different Approach to Testing

Indium started by understanding how inputs moved through the system and the outcomes they produced. The goal was to remove friction at each stage and build a setup that remained consistent even as conditions changed. They simplified information processing, streamlined action triggers, and improved issue identification.

Organizing Inputs

Organizing Inputs

The first step was to structure incoming information. It could then be used directly without repeated clarification or manual effort.

Connecting the Flow

Connecting the Flow

Each stage was aligned into a continuous process to reduce delays caused by handoffs and disconnected steps.

Reducing Effort Across Stages

Reducing Effort Across Stages

The focus was on lowering manual effort across the process, and it did not depend on constant human involvement.

Improving Issue Visibility

Improving Issue Visibility

Issues needed to be identified faster and with more clarity. Resolution did not rely on long investigation cycles.

Building for Consistency

Building for Consistency

The approach ensured stable outcomes across different scenarios without variation caused by manual execution.

Rebuilding Testing with UiPath and Gen AI

The system was built to take raw inputs, convert them into structured outputs, and execute them without delays or manual handoffs. Each step was designed to reduce effort, improve traceability, and ensure faster turnaround from input to resolution.

Requirements Made Actionable

Raw requirement documents were converted into structured formats using UiPath & Gen AI. Every input could be directly used without manual interpretation, with consistency maintained across all requirements.

01

Test Cases Created Instantly

Requirements were translated into complete, traceable, step-level test cases without manual effort. Each case stayed linked to its source, with full coverage and clarity built in.

02

Scripts Generated in Minutes

UiPath’s low-code automation builder and Gen AI code assist were used to generate scripts automatically. Tasks that earlier took days were completed within minutes, with minimal dependency on specialized skills.

03

Root Causes Identified Automatically

Failures were analyzed using UiPath AI to identify root causes, highlight broken elements, and detect environment or data problems. Issues were understood quickly without extended investigation cycles.

04

The Outcome of Removing Manual Dependency

A self-sustaining system handled continuous updates, complex journeys, and high-traffic periods without delays. Once inputs were structured and execution was aligned, results stayed consistent and issues did not pile up.

0 %

Less Effort in End-to-End Testing

Manual effort across the testing lifecycle was reduced, and key steps were handled automatically without manual involvement.

0 %

Auditability Across the Process

Every step, from input to execution, was tracked and recorded through AI-driven reporting.

0 ×

Increase in Team Productivity

With no bottlenecks slowing down validation, teams were able to move faster and focus on higher-value work instead of repetitive tasks.

No Loose Ends Left in the Process

The entire flow now runs from input to outcome without breaks. Each step connects directly to the next, with full traceability in place, which removes the need to revisit or rework anything later.

Even as updates roll out and user journeys become more complex, the process runs without intervention. Issues are addressed within the flow itself, and nothing is left pending or pushed to later stages.

About Indium

Indium is an Al-driven digital engineering company that helps enterprises build, scale, and innovate with cutting-edge technology. We specialize in custom solutions, ensuring every engagement is tailored to business needs with a relentless customer-first approach. Our expertise spans Generative Al, Product Engineering, Intelligent Automation, Data & Al, Quality Engineering, and Gaming, delivering high-impact solutions that drive real business impact.

With 5,000+ associates globally, we partner with Fortune 500, Global 2000, and leading technology firms across Financial Services, Healthcare, Manufacturing, Retail, and Technology-driving impact in North America, India, the UK, Singapore, Australia, and Japan to keep businesses ahead in an Al-first world.