Nalluri Vinay Kumar

Customer Conversation Analysis for Airlines

• Goal: Enhance customer service by analyzing conversations between customers and airline representatives.
• Approach: Utilized LLMs to summarize conversations, classify categories, identify customer concerns, and pinpoint areas for improvement.
• Outcome: Delivered actionable insights to improve service quality and address customer issues effectively.

Noise Reduction in Customer Conversations

• Goal: Improve data quality by reducing noise and optimizing token usage for LLMs.
• Approach: Identified and removed irrelevant sentences from conversations, improving data relevance.
• Outcome: Increased processing efficiency, accuracy of insights, and reduced computational costs.

Sentiment and Risk Analysis for Customer Interactions

• Goal: Analyze customer interactions to classify sentiment, travel categories, and assess risks.
• Approach: Applied sentiment analysis and risk assessment to categorize feedback and evaluate key risks.
• Outcome: Provided valuable insights for improved decision-making and customer service strategies.