VIRTUAL AGENT "ABHI" - COMPREHENSIVE DESIGN
VIRTUAL AGENT NAME: Abhi ( )
PLATFORM: Webex AI Agent (formerly Dialogflow CX option)
VOICE: Neural TTS - Indian English Male
PERSONA: Friendly, professional, helpful
PHASED ROLLOUT:
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PHASE 1 (Month 1-2): Foundation
10 core intents (English only)
Basic FAQ handling
Order status lookup (API integration)
Containment target: 25%
PHASE 2 (Month 3-4): Enhancement
25 intents (add Hindi language)
Account balance inquiry
Appointment scheduling
Containment target: 35%
PHASE 3 (Month 5-6): Advanced
50 intents
Complex troubleshooting flows
Proactive recommendations
Containment target: 45%
PHASE 4 (Month 7-12): Optimization
Add Tamil, German
Continuous learning from interactions
Abhavtech AI Platform integration
Containment target: 50%+
ABHI VIRTUAL AGENT - PHASE 1 INTENT LIBRARY
INTENT 01: greeting.hello
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Purpose: Welcome customers, establish rapport
Channels: Voice, Chat, WhatsApp
Training Phrases (20):
English:
- Hello
- Hi
- Good morning
- Good afternoon
- Good evening
- Hey there
- I need help
Hinglish:
- Namaste
- Hello, kaise hain aap
- Hi, mujhe help chahiye
- Namaste, main call kar raha/rahi hoon
Response Template:
"Hello! Welcome to Abhavtech. I'm Abhi, your virtual assistant.
I can help you with:
Order status and tracking
Product information
Account inquiries
Connect you to an agent
How can I help you today?"
Follow-up Intents: order.status, product.inquiry, agent.handoff
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INTENT 02: order.status
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Purpose: Check order delivery status and tracking
Channels: Voice, Chat, WhatsApp
Integration: HTTP Request to Order Management API
Training Phrases (30):
Direct queries:
- Where is my order
- Track my order
- Order status
- Check order status
- What is my order status
- Is my order shipped
- Has my order shipped
- When will my order arrive
- Delivery status
- Package location
With order number:
- Order 12345 status
- Track order 12345
- Where is order number 12345
- Status of ORD-12345
- Check ORD-12345
Hinglish:
- Mera order kahan hai
- Order ka status kya hai
- Delivery kab hogi
- Package kahan pohoncha
- Mera saman kab aayega
Frustrated:
- My order is late
- Why is my order delayed
- This is taking too long
- I want to know where my order is
Required Entities:
@order_number: Pattern: ORD-[0-9]{5,8} or numeric 5-8 digits
@customer_email: Optional, for lookup if no order number
@customer_phone: Optional, for lookup from ANI
API Integration:
Endpoint: {{ABHAVTECH_API}}/orders/{{order_number}}/status
Method: GET
Headers: Authorization: Bearer {{API_TOKEN}}
Response Fields: status, shipped_date, carrier, tracking_number,
estimated_delivery, current_location
Response Templates:
[Order Found - In Transit]:
"Your order {{order_number}} shipped on {{shipped_date}} via
{{carrier}}. It's currently {{current_location}}.
Expected delivery: {{estimated_delivery}}.
Track it here: {{tracking_link}}"
[Order Found - Delivered]:
"Great news! Your order {{order_number}} was delivered on
{{delivered_date}} at {{delivered_time}}.
Is there anything else I can help with?"
[Order Not Found]:
"I couldn't find an order with that number. Could you please
double-check the order number? It should start with ORD- followed
by 5-8 digits. Or I can look it up using your email address."
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INTENT 03: agent.handoff
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Purpose: Transfer to human agent
Channels: Voice, Chat, WhatsApp
Training Phrases (25):
- Talk to a human
- Speak to an agent
- Transfer me to a person
- I want to talk to someone
- Human please
- Get me a representative
- Real person
- Operator
- Agent please
- I don't want to talk to a bot
- Connect me to support
- This is not helping
- You're not understanding me
Hinglish:
- Agent se baat karani hai
- Kisi insaan se baat karao
- Mujhe kisi se baat karni hai
- Real person chahiye
Handoff Action:
1. Set context: intent=agent_request, reason=customer_requested
2. Generate context summary for agent
3. Route to appropriate queue based on conversation topic
4. Provide estimated wait time
Response Before Handoff:
"Of course! I'll connect you with one of our team members right away.
Based on our conversation, I'll transfer you to our {{queue_name}}
team. The estimated wait time is {{wait_time}}.
Please hold while I connect you."
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ADDITIONAL PHASE 1 INTENTS (Summary):
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04. product.inquiry - Product information requests
05. store.hours - Business hours and location
06. billing.balance - Account balance inquiry
07. return.policy - Return and refund policy
08. password.reset - Password reset assistance
09. greeting.goodbye - Conversation closure
10. fallback.default - Unrecognized input handling
TOTAL TRAINING PHRASES (Phase 1): ~200
CISCO AI ASSISTANT - AGENT ASSIST CONFIGURATION
FEATURE STATUS CONFIGURATION
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REAL-TIME FEATURES:
Context Summaries Enabled Auto-generate on transfer
Description: AI-generated summary when call transfers
between agents or from Virtual Agent
Suggested Responses Enabled Top 3 suggestions
Description: Real-time response suggestions based on
conversation context and knowledge base
Sentiment Analysis Enabled Real-time display
Description: Customer sentiment (Positive/Neutral/Negative)
displayed in Agent Desktop
Escalation Trigger: Alert supervisor if sentiment is Negative
for >2 minutes
Dropped Call Summaries Enabled Save to CRM
Description: AI summary if customer disconnects, saved
for callback context
POST-CALL FEATURES:
Auto CSAT Scoring Planned Q2 2026
Description: AI-predicted CSAT without customer survey
Based on interaction analysis
Call Summary Enabled Auto-generate
Description: Automatic call summary for agent wrap-up
Editable before save
AGENT WELLBEING:
Burnout Detection Planned Q2 2026
Description: Monitor agent stress indicators
Recommend wellness breaks
Wellness Break Trigger: After 4 consecutive difficult calls
Or 90% occupancy for 2+ hours