Course Goal
To equip new raiaLabs team members with the knowledge and skills to effectively build, train, and deploy AI agents using the raiaAI platform, with a focus on creating high-quality instructions, managing knowledge bases, and automating workflows.
Foundation: Understanding Agent Types and Use Cases
This foundational module introduces the three main categories of AI agents that raiaLabs typically builds for clients. Understanding these agent types is crucial for making informed decisions about training approaches, channel deployment, and business integration strategies.
Agent Type 1: Support Agent (General Knowledge)
Primary Function: Support Agents serve as the first line of customer service, handling general inquiries, troubleshooting common issues, and providing information from the company's knowledge base. These agents are designed to resolve routine customer questions efficiently while escalating complex issues to human representatives.
Typical Deployment Channels:
Copilot: Used by human support representatives to draft responses and access information quickly
Live Chat: Direct customer interaction on websites and customer portals
Email: Automated email response handling and ticket management
Key Characteristics:
Broad knowledge base covering multiple topics and departments
Focus on accurate information retrieval and clear communication
Strong escalation protocols for issues beyond their scope
Emphasis on maintaining consistent brand voice and customer experience
Common Use Cases:
Answering frequently asked questions about products or services
Providing account information and status updates
Guiding customers through basic troubleshooting procedures
Explaining company policies and procedures
Collecting initial information for complex support tickets
Training Considerations:
Requires comprehensive knowledge base covering all customer-facing information
Needs clear routing instructions to handle diverse query types
Benefits from extensive FAQ and troubleshooting documentation
Requires strong fallback and escalation procedures
Agent Type 2: Sales Agent
Primary Function: Sales Agents are designed to engage prospects and customers throughout the sales process, from initial lead qualification to closing deals. These agents can handle both inbound inquiries and outbound sales activities, adapting their approach based on the customer's stage in the sales funnel.
Typical Deployment Channels:
Outbound SMS: Proactive outreach to leads and prospects
Email: Follow-up sequences, nurture campaigns, and sales correspondence
Inbound Live Chat: Engaging website visitors and qualifying leads in real-time
Key Characteristics:
Persuasive communication style focused on conversion
Deep understanding of products, pricing, and competitive advantages
Ability to qualify leads and identify sales opportunities
Integration with CRM systems for lead tracking and management
Common Use Cases:
Lead qualification and scoring
Product demonstrations and feature explanations
Pricing inquiries and quote generation
Appointment scheduling with sales representatives
Follow-up on abandoned carts or incomplete applications
Nurturing prospects through email sequences
Training Considerations:
Requires detailed product knowledge and competitive positioning
Needs sales methodology and objection handling techniques
Benefits from customer persona and buyer journey documentation
Requires integration with sales tools and CRM systems
Agent Type 3: Analyst Agent
Primary Function: Analyst Agents operate behind the scenes within automated workflows, processing data, generating reports, and making decisions based on predefined criteria. These agents rarely interact directly with customers but play crucial roles in business operations and data analysis.
Typical Deployment Channels:
Workflow Integration: Embedded within n8n or other automation platforms
API Endpoints: Called by other systems to perform analysis or processing
Scheduled Tasks: Running automated reports and data processing jobs
Key Characteristics:
Data-focused with strong analytical capabilities
Designed for accuracy and consistency in processing
Integration with multiple data sources and business systems
Minimal need for conversational abilities, maximum need for precision
Common Use Cases:
Lead scoring and qualification based on behavioral data
Report generation and data summarization
Content analysis and categorization
Risk assessment and compliance checking
Data validation and quality assurance
Automated decision-making within business processes
Training Considerations:
Requires structured data and clear decision criteria
Needs comprehensive understanding of business rules and processes
Benefits from examples of edge cases and exception handling
Requires integration documentation for data sources and outputs
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