Intelligent AI assistant for contact center agents to boost productivity.
Overview
Agent AI provides real-time assistance to human agents:
- Suggested responses based on conversation context.
- Automated call and chat summaries.
- Knowledge base search integration.
- Next-best-action recommendations.
How It Works
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ā Live Conversation ā
ā ā
ā Customer: āI received the wrong item in my order ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā¬āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā
ā ā¼
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ā Agent AI Engine ā
ā ā
ā āāāāāāāāāāāāāāā āāāāāāāāāāāāāāā āāāāāāāāāāāāāāā ā
ā ā Context ā ā Knowledge ā ā Response ā ā
ā ā Analysis ā ā Search ā ā Generation ā ā
ā āāāāāāāāāāāāāāā āāāāāāāāāāāāāāā āāāāāāāāāāāāāāā ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā¬āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā
ā ā¼
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ā Agent Desktop Widget ā
ā ā
ā Suggested Response: ā
ā āI apologize for the inconvenience. I can help you with a ā
ā replacement or refund. Let me pull up your order details.ā ā
ā ā
ā Relevant Knowledge: ā
ā ā¢ Wrong Item Policy (confidence: 95%) ā
ā ā¢ Return Process Guide (confidence: 87%) ā
ā ā
ā Recommended Actions: ā
ā [Create Return] [Issue Refund] [Escalate to Supervisor] ā
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Features
Real-Time Suggestions
Contextual response suggestions during conversations:
| Feature | Description |
|---|
| Auto-suggest | Suggestions appear as customer speaks |
| One-click use | Insert suggestion with single click |
| Edit before send | Modify suggestions as needed |
| Learn from edits | System improves from agent modifications |
Suggestions:
trigger: continuous
display_count: 3
confidence_threshold: 0.7
sources:
- knowledge_base
- canned_responses
- conversation_history
tone: professional
Automated Summaries
Generate conversation summaries automatically:
| Summary Type | When Generated |
|---|
| Real-time | Updated as conversation progresses |
| After-call | Complete summary at interaction end |
| Disposition | Structured outcome summary |
Auto-Summary:
format: structured
sections:
- customer_issue
- resolution
- follow_up_required
length: concise
auto_save_to_crm: true
Knowledge Assistance
Integrated knowledge search:
- Search triggered automatically by conversation context.
- Manual search with natural language queries.
- Results ranked by relevance.
- Source citations included.
Next-Best-Action
Recommended actions based on context, example:
NBA Rules:
- condition: sentiment == "frustrated" AND issue_unresolved
action: offer_supervisor_escalation
priority: high
- condition: customer_tier == "premium" AND wait_time > 5min
action: offer_compensation
priority: medium
- condition: issue_type == "billing"
action: show_billing_tools
priority: normal
Configuration
Enable Agent AI
- Navigate to Agent AI ā Configuration.
- Enable Agent AI for desired queues.
- Configure feature settings.
- Test with pilot agents.
Feature Settings
| Setting | Options |
|---|
| Suggestion mode | Continuous, On-demand, Disabled |
| Auto-summary | Enabled, Disabled |
| Knowledge search | Auto, Manual, Both |
| NBA | Enabled, Disabled |
Integration
Connect Agent AI to:
- Search AI ā For knowledge retrieval.
- CRM ā For customer context.
- Case management ā For action execution.
- Quality AI ā For coaching feedback.
Agent Experience
Desktop Widget
Agent AI appears as a widget in the agent console:
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ā Agent AI [ā] [Ć]ā
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ā ā
ā Suggested Response ā
ā āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā ā
ā ā I understand your concern about ā ā
ā ā the billing charge. Let me ā ā
ā ā address them. ā ā
ā āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā ā
ā [Use] [Copy] [š] [š] ā
ā ā
ā Knowledge ā
ā ā¢ Billing FAQ (95%) ā
ā ā¢ Refund Policy (88%) ā
ā [Search manually] ā
ā ā
ā Quick Actions ā
ā [Refund] [Credit] [Escalate] ā
ā ā
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Feedback Loop
Agents can rate suggestions:
- Thumbs up ā Good suggestion.
- Thumbs down ā Unhelpful suggestion.
- Edits ā System learns from modifications.
Feedback improves suggestion quality over time.
Analytics
Agent AI Metrics
| Metric | Description |
|---|
| Suggestion acceptance | % of suggestions used |
| Time saved | Handle time reduction |
| Knowledge utilization | Searches and clicks |
| NBA conversion | Recommended actions taken |
Quality Impact
Track quality improvements:
- First contact resolution rate.
- Customer satisfaction scores.
- Quality evaluation scores.
- Handle time trends.
Best Practices
Deployment
- Start with a pilot group of agents.
- Gather feedback and iterate.
- Roll out gradually by queue/team.
- Monitor adoption and adjust.
Knowledge Quality
- Keep knowledge base current.
- Remove outdated content.
- Add content for common queries.
- Monitor search failures.
Agent Training
- Introduce Agent AI in agent training.
- Explain feedback mechanism importance.
- Show how to use suggestions effectively.
- Address concerns about AI assistance.
