Revolutionizing Customer Support
An interactive overview of how a Multi-Agent AI System can automate ticket triage, accelerate resolutions, and elevate the customer experience.
The Challenge with Traditional Support
Scaling customer support is difficult. Rising ticket volumes lead to slower responses, agent burnout, and declining customer satisfaction.
24.4 Hours
Avg. First Response Time
42%
Customers expect a response in under an hour
$1.6 Trillion
Lost by U.S. businesses due to poor service
The Solution: A Multi-Agent AI Team
This system uses a team of specialized AI agents working together to handle customer requests efficiently. Click on each agent in the diagram to understand its specific role.
Triage Agent
The Front Desk
Knowledge Agent
The Researcher
Resolution Agent
The Problem Solver
Escalation Agent
The Human Handoff
Triage Agent
The first point of contact. It reads the incoming customer ticket, understands the user's intent, categorizes the issue (e.g., Billing, Technical, Feedback), and determines its urgency. It then routes the ticket to the appropriate specialist agent.
How It Works: A Ticket's Journey
Follow a customer support ticket as it moves through the automated system, from initial submission to final resolution.
1. Ticket Arrives
Customer submits a request via email or web form.
2. Triage & Categorize
Triage Agent analyzes and routes the ticket.
3. Information Gathering
Knowledge Agent fetches data from help docs.
4. Resolution / Escalation
Resolution Agent answers, or Escalation Agent hands off to a human.
Performance & Impact
By automating routine tasks, the AI system dramatically improves key support metrics and frees up human agents for high-value interactions.
Key Metric Improvement
Ticket Volume by Category
Agent Deep Dive
Explore the core instructions (prompts) that define how each agent behaves and what tools they can use.
Example Prompt: Triage Agent
This prompt instructs the agent on how to analyze and classify an incoming ticket.
ROLE: You are a Triage Agent for a SaaS company.
TASK: Analyze the following customer ticket. Identify the category, sentiment, and urgency.
CATEGORIES: ['Billing', 'Technical Support', 'Account Access', 'Feedback', 'Sales Inquiry']
URGENCY: ['Low', 'Normal', 'High', 'Critical']
OUTPUT: Return a JSON object with 'category', 'sentiment', and 'urgency' keys.