sentiment-analytics
Our Sentiment Analytics engine uses AI to analyze tone, emotion, and intent across voice and text interactions. Whether in customer service, collections, or sales calls, understanding sentiment helps teams respond with empathy, flag escalations early, and personalize the customer experience in real-time.
What It Does
Real-Time Sentiment Detection (positive, neutral, negative)
Real-Time Sentiment Detection (positive, neutral, negative)Multi-Channel Campaign Orchestration
Voice + Text Intelligence
Voice + Text Intelligence
Tone & Emotion Layering (frustration, happiness, sarcasm, etc.)
Tone & Emotion Layering (frustration, happiness, sarcasm, etc.)
Conversation-Level Sentiment Scoring
Conversation-Level Sentiment Scoring
Trigger Alerts & Escalations on emotion spikes
Trigger Alerts & Escalations on emotion spikes
Insights You Can Extract
Agent Empathy Score
Risky Call Trends
Churn Prediction Flags
Service Quality Heatmaps
Campaign Effectiveness by Tone
Use Cases
Contact Centers – real-time feedback and QA
Debt Collections – flag aggressive/sensitive exchanges
E-commerce Support – personalize responses
Surveys & Feedback – beyond ratings, understand emotion
Training – assess agent empathy and soft skills
How It Works
01.
Voice input is transcribed via ASR
02.
Language model analyzes each sentence
03.
Emotional polarity and intensity are scored
04.
Visual dashboard & API outputs returned instantly
Sample Metrics
Metric
Description
Sentiment Polarity
Positive / Neutral / Negative per turn
Emotional Intensity
Level of anger, joy, sadness, etc.
Escalation Flag
Triggered when emotion exceeds threshold
Agent Tone Matching
Measures how well agents mirror sentiment
