Text Classification & Sentiment Analysis
Uses NLP models to tag, classify, and interpret documents, chats, or reviews—extracting themes, tone, and emotion for insight generation, alerts, and content-level analysis
Key features
Classify text and analyze sentiment to uncover insights, improve engagement, and enable smarter decision-making in customer-focused solutions:
Sentiment Analysis
Analyze customer sentiment in text automatically
Measure emotions in reviews, feedback, and conversations to guide engagement and service strategies
Topic Classification
Categorize text into relevant topics instantly
Organize textual data effectively by categorizing it into relevant subjects for easier analysis
Multilingual Support
Analyze text across multiple global languages
Expand insights globally with sentiment analysis that supports multiple languages and dialects
Real-Time Processing
Perform sentiment analysis on text streams live
Enable timely decisions by analyzing text sentiment instantly as conversations or streams occur
Custom Models
Train sentiment models on domain-specific data
Improve accuracy by building models tuned to specialized industry or organizational data
Visualization Tools
Display sentiment trends with interactive dashboards
Communicate results clearly with dashboards that visualize text classification and sentiment outputs
