AI-Driven Test Automation Framework

Led the design and development of an AI-powered test automation framework that transformed how front-end and API testing was executed. The framework integrated Playwright (TypeScript) for web UI testing and Pytest (Python) for GraphQL API validation, ensuring seamless coverage across layers.

Using Cline and GitHub Copilot, the system generated intelligent test scripts automatically from user stories and API specifications, significantly cutting down authoring time.
To enhance observability, Sandal implemented Grafana-Prometheus alerting to monitor test stability and detect regression trends in CI pipelines.

Additionally, the framework incorporated visual anomaly detection using AI models to verify React-based dashboards — ensuring that graphical widgets and performance metrics remained consistent after each release.
This initiative resulted in a 35% reduction in manual QA effort and established a reusable model for other teams.

Key Achievements:
Built a fully autonomous Playwright framework with modular plugin support.
Introduced AI-based visual validation, improving UI accuracy.
Integrated coverage-based prioritization to target high-value test cases.
Enhanced system reliability via Kafka, AWS, and Airflow fault testing.