Contextual signals
Evaluate tone together with what was said
Use acoustic and conversational context to identify possible frustration, urgency, confusion, satisfaction, or high intent.
Monitor / Conversation signals
Detect Conversation Signals Respond With Context
Detect customer emotion and urgency so teams know when a conversation needs care, escalation, or recovery.
Emotion signalsEscalation triggersQuality review
Connect sentiment detection to your existing tools
Voice agents
Contact center
Help desks
CRM
QA workflows
Notifications
From signal to response
Detect carefully, respond proportionately, review continuously.
Choose meaningful signals, combine them with context, define safe actions, and compare predictions with human-reviewed conversations.
- 01
Choose useful signals
Define which emotional or urgency patterns matter for the workflow.
- 02
Set context rules
Combine signals with intent, phrases, customer status, and call history.
- 03
Define the response
Route, notify, flag, or continue based on the strength and risk.
- 04
Review accuracy
Sample the underlying calls and tune thresholds with human reviewers.
Inside a sentiment signal
Tone, language, and context combine before a workflow reacts.
Sentiment is most useful as evidence. Conversation changes, customer context, and calibrated thresholds work together to support the right human response.
Timely escalation
Turn a signal into an appropriate response
Combine sentiment with intent, account context, and business rules before prioritizing a call or inviting a human teammate.
Quality learning
Find the moments worth reviewing
Focus quality review on calls with meaningful changes and compare the underlying evidence to improve prompts, coaching, and service design.
Conversation signal
Context-Aware Sentiment Detection
Send meaningful signals into routing, QA, and support workflows.
Plan your integrationSentiment Detection exampleEscalation suggested
- 1CustomerI have already called twice and still do not have an update.
- 2Sentiment DetectionFrustration signal increased after repeated-contact mention.
- 3Connected actionPriority support route prepared
Tone, language, and conversation history combine before any alert, escalation, or review workflow begins.
Use cases
Where sentiment detection helps your team.
Service recovery
Identify calls that may need faster help or a supervisor response.
Earlier interventionQuality assurance
Prioritize reviews around frustration, confusion, or major tone changes.
Focused QA effortSales coaching
Review moments where interest rose, objections appeared, or confidence fell.
Better coaching contextSentiment Detection at a glance
The details your team can evaluate.
Live
conversation signals
Flag
calls for focused review
Trend
changes over time
Signal engine
Context turns emotion into a calibrated signal.
Tone, language, and conversation history combine before any alert, escalation, or review workflow begins.
Contextual signals
Evaluate tone together with what was said
Use acoustic and conversational context to identify possible frustration, urgency, confusion, satisfaction, or high intent.
Signal core
Frequently asked questions
What teams ask about sentiment accuracy.
A practical overview of sentiment detection, setup, and how your team stays in control.
Does sentiment detection know exactly how a caller feels?
No. Sentiment is a probabilistic signal, not a certain reading of a person's internal state. It should support human judgment and workflow rules rather than make high-impact decisions by itself.
Can sentiment trigger a live transfer?
It can contribute to an escalation rule, ideally alongside conversation content, intent, customer context, and clear thresholds to reduce unnecessary transfers.
How should accuracy be evaluated?
Use representative calls, human-reviewed labels, different languages and call conditions, and error analysis. Review false positives and false negatives for each intended workflow.
Can sentiment be compared over time?
Yes. Teams can aggregate configured signals by workflow or period, then inspect the relevant calls to understand what changed and whether the trend is meaningful.
Start building
Add context-aware sentiment signals to one customer workflow.
Start with one sentiment detection workflow, connect the tools it needs, and expand from real results.
✓ Emotion signals✓ Escalation triggers✓ Quality review