Optimizing Virtual Assistants with Intent Classification Annotations

Client's Challenge & Our Solution

A global virtual assistant provider needed high-quality intent classification to enhance the accuracy of its AI in understanding user commands and queries. Their challenge was managing a multilingual dataset with nuanced intents across diverse domains like travel, e-commerce, and customer support.

FutureBeeAI delivered over 100,000 annotated text and audio datasets across 12 languages, accurately classifying intents into categories such as booking, purchasing, inquiries, and troubleshooting. We customized our annotation process to meet the client’s domain-specific requirements and utilized our advanced annotation platform for seamless integration with their AI training pipelines.

Outcome & Features:

Supplied over 100,000 multilingual datasets with domain-specific intent classification.

Enhanced virtual assistant accuracy enabling better understanding of diverse user intents.

Completed the task within 9 weeks of timeline