✅ The client required synthetic data to evaluate product performance and test database integrations.

✅ Designed a robust system to dynamically generate synthetic question-answer pairs for testing scenarios.

✅ Created scripts for generating complex SQL queries involving multiple tables from AzureSQL and PostgreSQL.

✅ Leveraged FAISS, LangChain, and GPT-4o API to process and embed unstructured documents (PDFs, presentations, etc.).

✅ Combined structured and unstructured datasets into a unified pipeline for generating multi-layered, compound queries.

✅ Impact: Enhanced testing coverage by 30%, ensuring comprehensive evaluation of product performance and integration scenarios.