From 'Chat' to 'Action'
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Say goodbye to robotic replies. Build an intelligent service system that understands, empathizes, and truly solves business problems through Agentic AI and multimodal interaction.

Generational Leap in Service

Compare traditional customer service models with next-gen AI-driven systems.

Dimension
Traditional CS
Next Gen AI CS
Service Entity
Human led, Bot assisted
AI led, Human assisted (70%+ by AI)
Interaction
Text or Voice only
Multimodal (Text + Voice + Image/Video + Screen)
Memory
Manual check of history
Memory Enhanced AI (Cross-session, Real-time CRM)
Execution
Bot can only answer, not act
Agentic AI (Calls APIs for returns, refunds, etc.)
Emotion
Rely on agent experience
Voice/Text Emotion Recognition (Auto-alert)
Mode
Passive response
Predictive/Proactive Service
Efficiency
High AHT, High Cost
AHT Down 60% (Cost Down 35-60%)

Core AI Applications

Building an intelligent service matrix with deep cognition and execution capabilities

Memory Enhancement

Remembers 'Who, What, Where'. Real-time CRM/Order system access for 360 view.

Effect: No repetition needed, misunderstandings down 40%.

Multimodal CS

Supports voice, text, image/video recognition. Appliance model ID via photo, OCR bills.

Value: Complex resolution rate up ~50%.

Emotional Intelligence

Voice emotion accuracy 90%+. Predicts outbursts 30-60s ahead. Routing to senior agents.

Use: Real-time soothing prompts, reduced escalations.

Agentic AI

From 'Speaking' to 'Doing'. Verify -> Query -> Decide -> Act -> Ticket loop.

Trend: ~56% of interactions handled by Agentic AI.

Predictive Service

Analyze logs and behavior to find issues early. Notify and compensate before complaint.

Effect: Complaints down 35%, FTR up 20%.

Industry Scenarios

Tailored intelligent solutions for industry pain points

Retail / E-commerce

Recommendation & Sales
Conv. +30%
Real-time matching, personalized offers.
Auto After-sales
85% Automated
Auto-judge returns, generate slips.

Bank / Finance

Smart Account Svc
90%+ AI Handled
Balance, lost card, limit adjustment.
Loan Pre-audit
Hours not Days
OCR docs, rule engine screening.

Retail / E-commerce

Recommendation & Sales
Conv. +30%
Real-time matching, personalized offers.
Auto After-sales
85% Automated
Auto-judge returns, generate slips.

Bank / Finance

Smart Account Svc
90%+ AI Handled
Balance, lost card, limit adjustment.
Loan Pre-audit
Hours not Days
OCR docs, rule engine screening.

Implementation Path

Phased evolution from quick relief to full intelligence

Basic AI CS (1-2 Mo)

Relief First

Goal: Quick pressure relief for hotline/online.

  • Select 3-5 high freq scenarios
  • Unified Knowledge Base
  • FAQ Bot

Result: Self-service 50-60%.

Enhanced AI (2-3 Mo)

Understanding

Goal: Personalization and complex issue handling.

  • Integrate CRM/Order sys
  • Memory AI
  • Emotion + Multimodal

Result: CSAT +15%, FTR 80-85%.

Agentic AI (2-3 Mo)

Action Taking

Goal: End-to-end task completion.

  • Automate 3-5 key flows
  • Standardize APIs
  • Risk rules

Result: End-to-end auto rate 40-60%.

Core Implementation Impact Metrics

CSAT
84%
Up to 84%
FTR
85%
Up 20%
Avg Handle Time
4min
Down 60%
Cost Per Svc
66%
Down 66%

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