This is like giving your company a super-listening ear that reads all customer comments, reviews, and survey answers and tells you, in plain language, how people feel and why they’re happy or upset.
Companies drown in unstructured customer feedback (reviews, chats, surveys, social posts) and can’t manually read it all to understand emotions, root causes, and trends. This tool centralizes and analyzes that feedback automatically so teams can improve products, service, and marketing based on real customer sentiment.
Domain-specific sentiment and emotion taxonomy, proprietary labeled feedback data, and integration into customer experience/VoC workflows create stickiness and improve model performance over time.
Hybrid
Vector Search
Medium (Integration logic)
Handling and storing large volumes of unstructured text feedback while keeping inference latency low and costs manageable across many channels and languages.
Early Majority
Focus on deep sentiment and emotion detection on unstructured customer feedback across multiple consumer touchpoints, likely with more granular emotion labels and out-of-the-box, business-ready insights rather than generic text analytics.