Jigesh is an Engineering Manager specializing in Quality Assurance, with extensive experience in the eLearning and Healthcare industries. He has developed numerous reusable testing tools, frameworks, and templates, significantly enhancing testing efficiency. Currently, he provides innovative testing solutions that improve quality for both US and global clients. Jigesh has played a pivotal role in test advisory, management, planning, and execution, and has led offshore testing efforts. His expertise also extends to Performance Engineering, SQL optimization, system resource monitoring, and the implementation of Generative AI technologies in testing processes, achieving a 20% increase in overall efficiency.

In today’s world, the creation of Test Cases and Automation Test Scripts using tools like ChatGPT or AWS Bedrock has become commonplace. However, these efforts often stay within the immediate context of the testing session or the specific area of the application that is shared during the conversation. For instance, when providing details about a User Story, the generated test cases are typically specific to the given content. Imagine extending this capability to generate test cases or automation scripts based not only on current information but also leveraging past releases data and other interconnected areas that may be indirectly impacted. This is where the integration of Vector Database with GenAI APIs comes into play. This integration not only facilitates the generation of contextually rich test cases\scripts but also enables the storage of data for training and storing in the database for future use.
Talk „Elevate your GenAI driven Testing with long term memory using vector database“ aims to provide insights into leveraging GenAI APIs with Vector Database to generate both components as well as End-to-End test cases based on provided User Story details and past learnings. It will demonstrate how the integration establishes context through User Story to Test Case Mapping, resulting in the generation of comprehensive End-to-End Test Cases. Beyond functional test cases, the presentation will deep dive into the generation of comprehensive automation scripts using these test cases. It will also showcase how you can customize the generation of automation script as per your automation framework with vector embeddings.