LLM Evaluation and Quality Optimization of an Enterprise AI Assistant
Responsible for systematically evaluating and optimizing an LLM-based AI chatbot for company-wide knowledge access. Focus areas included model alignment, factual accuracy, output consistency, and scalable quality improvement. Key Responsibilities: Designed structured evaluation criteria to assess factual accuracy, relevance, coherence, and source validity. Identified and classified hallucinations and logical inconsistencies. Developed curated test cases to enable reproducible quality measurement. Analyzed large-scale chat logs for error clustering and pattern detection. Iterative prompt optimization. Created high-quality corrective responses as training and reference material. Evaluated usability and transparency mechanisms from an end-user perspective.