Global Fast-Food Chain Cuts Regression Time by 50% Leveraging Coforge’s Advanced AI-Driven Test Automation

Challenges

• Quality engineering goals not defined
• Lack of standardized Agile processes
• No robust, reusable automation framework
• Under-utilized/fragmented tool ecosystem; limited integrations
• Absence of dashboards for real-time QA visibility
• Complex application landscape (camera, vehicle detection, voice assistants, POS, 3rd-party delivery)
• Low collaboration across a multi-vendor environment
• Need to assess QA processes for AOT & GMA

Solution

Coforge performed a comprehensive assessment and executed a phased uplift of QE processes, tooling, and automation—embedding governance, observability, and AI-assisted resilience:

• Assessed QE processes & practices end-to-end across Agile lifecycle, test automation, and QA governance; mapped team setup, capacity, and utilization; prioritized quick wins for near-term value.
• Implemented persona-based dashboards for real-time QA visibility; baselined a metrics framework and compliance score to drive outcomes and accountability.
• Assessed and implemented automation for AOT, NPOS, and GMA; evaluated AOT integration feasibility (camera, vehicle detection, voice assistants, POS) and flagged process gaps blocking automation.
• Co-created a Quality Assurance & Test Framework with client stakeholders, aligning ways of working across vendors and markets.
• Reviewed the tool ecosystem; recommended an integrated, modern toolchain including Python with Robot Framework and Microsoft Azure Speech (STT/TTS) for voice scenarios.
• Stabilized the proprietary Selenium/Appium-based framework for GMA; customized it for market nuances to scale coverage.
• Increased automation coverage across applications; introduced AI-driven locator self-healing to cut script maintenance.
• Conducted a focused assessment of QA processes for DMB CMS; defined a globally standardized, componentized menu-board framework configurable by market (layout, positioning, selections, product mix).
• Enabled content analytics with proactive alerting for faster issue detection.

The Impact

• ~50% regression cycle-time reduction
• ~90% automation coverage supporting 16 dialects
• 7,000+ automated test cases
• Support across 5 markets on both Android and iOS
• Offshore lab set-up with 40+ devices and 2 POS stores
• Daily build smoke support for rapid defect identification