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AI Chatbot Implementation Overview

Welcome to the ept AI chatbot implementation guide! This overview page will direct you to the right documentation for your current stage of development.

Quick Start Path​

For most implementations, follow this step-by-step path:

1. Preparing the AI​

Set up your knowledge base and AI intelligence

  • Organize and upload your content (documentation, FAQs, policies)
  • Configure knowledge sources and Knowledge Source Configurations (KSCs)
  • Tune AI behavior and response quality
  • Test your AI's knowledge and responses

2. Integrating the Chatbot​

Add the chatbot to your website or application

  • Set up secure Auth0 authentication
  • Create backend token endpoints
  • Initialize the chatbot in your web application
  • Configure channels for different platforms

3. Configuring the Design​

Customize the visual appearance and user experience

  • Configure themes, colors, and positioning
  • Brand integration and custom styling
  • Mobile and desktop optimization
  • Advanced UI customization

4. Context-Aware Chat​

Make your chatbot context-aware and intelligent

  • Provide user and page context with each message
  • Display relevant prompt questions based on current page
  • Implement dynamic prompts for single page applications
  • Advanced context management and best practices

5. Continuous Improvement​

Monitor, analyze, and optimize performance

  • Set up performance monitoring and analytics
  • Analyze response quality and user satisfaction
  • Update knowledge base based on user interactions
  • Implement A/B testing and feature improvements

Implementation Approach​

An ept AI chatbot combines natural language processing with your organization's knowledge base to provide intelligent, contextual responses. The system can be deployed across multiple channels including web interfaces, mobile apps, messaging platforms, and CRM systems.

Quick Reference​

Need help with a specific task?

Prerequisites​

Before implementing your AI chatbot, ensure you have:

  • Administrator Access: You need admin privileges to configure channels and knowledge sources
  • Knowledge Content: Prepare your documentation, FAQs, product information, and other content
  • Integration Requirements: Gather API keys, credentials, and permissions for your target platforms
  • Use Case Definition: Clearly define what your chatbot should help users accomplish

Common Implementation Patterns​

Customer Support Chatbot​

Goal: Reduce support ticket volume and provide 24/7 assistance

  1. Knowledge Base: FAQs, product documentation, troubleshooting guides
  2. Channels: Website widget, email integration, support portal
  3. Design: Professional, helpful tone with clear escalation paths
  4. Monitoring: Track resolution rate, user satisfaction, and ticket deflection

Sales Assistant Chatbot​

Goal: Qualify leads and provide product information

  1. Knowledge Base: Product specs, pricing, competitive comparisons
  2. Channels: Website, CRM integration, landing pages
  3. Design: Engaging, persuasive interface with lead capture
  4. Monitoring: Conversion rates, lead quality, engagement metrics

Internal Knowledge Bot​

Goal: Help employees find information quickly

  1. Knowledge Base: HR policies, procedures, internal documentation
  2. Channels: Slack, Teams, intranet
  3. Design: Casual, efficient interface for quick answers
  4. Monitoring: Usage patterns, knowledge gaps, employee satisfaction

Architecture Overview​

Key Components​

  • Knowledge Sources: Your content repositories (documents, URLs, databases)
  • Knowledge Source Configurations (KSCs): Logical groupings of knowledge for different use cases
  • AI Engine: Natural language processing and response generation
  • Channels: Integration points for different platforms and applications
  • User Interfaces: The actual chat widgets and interaction points

Support and Resources​

Documentation​

Configuration References​

Monitoring and Analytics​