Intent Tagging for Customer Chat Analysis

Client's Challenge & Our Solution

A global telecommunications company aimed to develop an AI-driven customer support system capable of understanding customer intents, such as billing inquiries, technical support, complaints, and plan upgrades. The challenge was to label 20000 multilingual customer chat transcripts (English, Spanish, French, Hindi, Arabic, and Tagalog) with intent tags across 15 categories, ensuring high precision for effective model training.

FutureBeeAI delivered a complete solution by cleaning and organizing the transcripts for annotation. Our team of expert annotators with domain-specific knowledge tagged each chat transcript with its corresponding intent. We also ensured cultural and linguistic nuances were incorporated to achieve high contextual accuracy.

Outcome & Features:

Provided a 20000 labeled chat dataset across 6 languages, enabling precise intent classification.

Labeled with 15 intent categories, including billing, complaints, and technical queries.

Completed the project in 8 weeks, delivering expected accuracy and aligning with the client’s AI model goals.