SentimentCoreAI
Detect user sentiment in every service conversation.
Reads sentiment in user messages across every channel and quietly alerts service managers before frustration escalates into a breach.
- Turns incoming user messages into a real-time sentiment score (-1 to +1) on every ticket.
- Breaks sentiment into six sub-dimensions such as anger, impatience, and disappointment.
- Triggers a silent escalation to the service manager when the trend line starts to deteriorate.
- Surfaces the score and sub-dimensions inline on the ticket so agents see emotional context at a glance.
From signal to outcome
Channel-agnostic trigger
It runs on every new message whether it arrives by email, self-service portal, chat, or a call transcript.
Context-weighted scoring
The model weighs the message against past interactions and the user profile to produce an accurate sentiment score.
Inline sentiment badge
The score and its sub-dimensions appear as a badge alongside the ticket conversation for the assigned agent.
Silent escalation
If the sentiment curve breaks, the service manager is alerted privately while the user sees nothing change.
The situation
At Birikim Holding, Selin Yildiz opened INC-2847, the third recurring mail-server incident, and her follow-up messages stacked critical phrases like "for the third time" and "the customer queue is growing."
The outcome
SentimentCoreAI caught the sentiment trend break within 7 minutes and sent a silent alert to the service manager. The team posted an interim response within 12 minutes, and CSAT on this incident stayed above 4.1.
Common questions
No. The score and sub-dimensions are visible only to assigned agents and service managers as an inline badge, and escalations are sent privately so the user experience is never affected.
See SentimentCoreAI in your workflow.
Book a demo and we'll show SentimentCoreAI working inside the platform — on your real tickets and data.