Sentiment Analysis
Sentiment analysis lets your AI agent detect frustration, urgency, and satisfaction - adjusting responses and escalating when needed.
The AI capability of detecting emotional tone in text - identifying whether a customer message is positive, negative, neutral, frustrated, or urgent - enabling appropriate response adjustments and escalation decisions.
Emotion Detection
Detect positive, negative, neutral, frustrated, and urgent tones in customer messages.
Frustration Escalation
When negative sentiment is detected, the agent adjusts tone and can escalate to a human team member.
Satisfaction Tracking
Track sentiment across conversations to monitor overall customer satisfaction trends.
Tone Adjustment
The agent adapts its response tone - more empathetic for frustrated customers, more efficient for urgent requests.
Trend Analysis
Identify sentiment patterns by time, channel, product, or agent - revealing systemic issues.
Conversation Tagging
Auto-tag conversations by sentiment for quality review and team coaching.
FAQ
Does it work in Arabic?
Yes. Sentiment analysis works across Arabic and English messages, including Gulf Arabic expressions.
Can it detect sarcasm?
Modern models handle many forms of sarcasm, but edge cases exist. When uncertain, the agent defaults to neutral treatment.
How does it handle mixed sentiment?
If a message contains both positive and negative elements, the agent identifies the dominant sentiment and flags the concern.
Respond to how customers feel
Deploy sentiment-aware AI agents.