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Case Studies

Case Study 1: How AI-Driven Testing Cut Release Time by 66% for a Global E-Commerce Platform
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Client Snapshot

A leading global e-commerce company serving millions of daily users faced mounting pressure to release faster, reduce QA costs, and maintain quality across both web and mobile platforms.

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The Challenge

Their QA process was slowing the business down:

  • Manual regression testing dragged on for 2–3 weeks per release.

  • Fragile automation scripts broke with every UI change.

  • Cross-platform inconsistencies slipped through, especially on mobile.

  • Production defects during high-traffic periods led to revenue losses.

The team was stuck — fast features meant bugs; solid testing meant delays.

 

The Solution: AI-Powered Visual & Cross-Platform Test Automation

We deployed a layered, intelligent automation strategy combining visual validation, dynamic test generation, and cross-platform resilience:

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Selector-Free Visual Testing

  • Eggplant’s image-based approach validated the UI across platforms without relying on brittle selectors.

 

Cross-Browser Automation That Just Works

  • Playwright handled browser testing with built-in wait strategies, auto-retry logic, and parallel execution to cut test time.

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AI-Driven Test Generation & Maintenance

  • Model Context Protocol (MCP) agents continuously analyzed application state and user flows.

  • Tests adapted in real time to UI and logic changes — no human intervention needed.

 

Smarter Visual QA

  • Eggplant's AI detected subtle UI anomalies humans missed, boosting UI regression coverage.

 
Self-Healing Test Logic

  • The AI agents reduced false positives by 80% by auto-updating test paths as the app evolved.

 

Technical Breakdown

  • MCP agents: Constantly monitor and update tests based on app state.

  • Playwright: Enables high-speed, cross-browser automation with smart execution.

  • Eggplant: Delivers visual validation across web and mobile interfaces.

  • AI Layer: Handles test maintenance, reducing human involvement and errors.

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The Results
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                       Metric                                   Before                                  After​

​​           Manual Test Effort                                    2–3 weeks                           70% reduction

           Release Cadence                                       Bi-weekly                                    Daily

           Test Coverage                                          Inconsistent             95%+ with dynamic adaptation

        Production Defects (6 mo.)                              Frequent                             40% decrease

      Test Maintenance Overhead                              High                                85% reduction

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Improvements were visible within 4 weeks. The entire rollout was complete in 8.

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Case Study 2: How a Tier-1 Bank Achieved 98% Audit Pass Rates with AI-Powered Compliance QA
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Client Snapshot

A Tier-1 European bank needed to maintain rapid digital release cycles while providing end-to-end compliance with Basel III, GDPR, and KYC regulations.

The stakes were high: regulatory scrutiny, reputational risk, and potential multi-million-euro fines.

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The Challenge

Manual compliance testing had become a bottleneck — and a liability:

  • 5-week test cycles delayed releases and drained QA bandwidth

  • Audit prep involved days of manual traceability documentation

  • Compliance blind spots increased the risk of fines and reputational fallout

  • Edge cases frequently went untested under high release pressure

 

The QA team needed to scale compliance validation without compromising speed or coverage.

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The Solution: Compliance QA Pack (AI-Powered)

We delivered an enterprise-ready, AI-powered QA framework purpose-built for regulatory compliance — turning weeks of manual effort into intelligent, automated validation.

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Technical Implementation
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Automated Regulatory Validation

  • NLP models trained on 15,000+ regulatory documents mapped application logic to rules in Basel III, GDPR, and KYC

  • Integrated with core systems: Temenos T24, GRC tools, and SWIFT interfaces

  • Real-time validation engine achieved 94% rule-matching accuracy

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Risk-Based Testing with AI Prioritization

  • ML algorithms analyzed 3 years of audit data to score scenarios by risk impact

  • Decision trees prioritized critical compliance paths (e.g., onboarding, KYC, transaction flows)

  • Bayesian models predicted failure risk across 200+ regulatory checkpoints

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Audit-Ready Evidence Packs

  • Blockchain-backed logs ensured tamper-proof audit trails

  • Seamless Jira/Xray integration auto-generated traceability matrices

  • Digitally signed PDF reports included timestamped execution logs for regulators

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AI-Powered Scenario Simulation

  • Synthetic data (via GANs) mimicked real-world customer behaviors and transactions

  • Monte Carlo simulations validated system behavior under stress (e.g., liquidity limits, data breaches)

  • Edge-case detection flagged risky compliance gaps before release

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Implementation Timeline

12-week phased roll-out with measurable gains by Week 8.

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The Results

 

                                      Metric                                       Before                                              After

              Compliance Test Duration                                  5 weeks                              1 week (80% faster)

                        Audit Pass Rate                                      73%                               98% across 3 audit cycles 

                  Compliance Ops Cost                                  High                                          45% reduction

             Critical Findings per Audit                                 12                                                         1

                     False Positive Rate                                    35%                                                    8%

 

"Our compliance QA went from reactive firefighting to proactive risk management. We caught 15 potential GDPR violations before they reached production."
— Compliance Director, Major European Bank​​

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