LLM Applications Data Training and Evaluation – Fundly
Implemented AI-based financial recommendations utilizing LLM APIs to provide users with budgeting and savings advice. Collaborated on prompt design and evaluation of generated content for accuracy and user impact. Designed validation logic to filter outputs for relevance and effectiveness. • Worked with Claude Sonnet 4.5 for LLM-driven financial recommendation workflows.• Designed testing frameworks to evaluate AI-generated advice for financial applications.• Labeled, rated, and improved AI output data for better budgeting decisions.• Gathered user data feedback to continually refine and improve LLM models.