Designed the architecture and development framework for an Al feedback agent capable of providing contextual, actionable insights across various domains. Leveraged advanced natural language processing (NLP) techniques, domain-specific knowledge bases, and dynamic user profiling to ensure personalized, high-quality feedback delivery with response speed increased by 40%
Optimized prompt designs to ensure clarity, relevance, and adaptability, enhancing user engagement and satisfaction that led to $15,000 in subscription revenue
Deployed a swarm of Al agents to deliver valuable user feedback across various formats, including NPS (Net Promoter Score), CSAT (Customer Satisfaction), and MCQ (Multiple Choice Questions). Engineered scalable solutions to automate and personalize feedback delivery, driving improved user insights and decision-making processes with service reliability increased by 50%