Custom RAG Chatbot

A Custom RAG Chatbot is a custom chatbot that is a RAG-based chatbot system (supports RAG operations to provide context-aware responses based on specific knowledge sources).

• Context:
  • It can provide AI Responses through language models and knowledge retrieval.
  • It can process User Querys using natural language understanding.
  • It can access Document Sources through retrieval systems.
  • It can maintain Conversation Context via chat history and session management.
  • It can generate Contextual Responses using retrieved information.
  • It can support Document Formats including text, pdf, and structured data.
  • ...
  • It can range from being a General Purpose RAG Chatbot to being a Domain Specific RAG Chatbot, depending on its knowledge scope.
  • It can range from being a Basic RAG Implementation to being an Enterprise RAG System, depending on its deployment scale.
  • ...
• Examples:
  • Platform Based Implementations, such as:
    • Anthropic Projects-based Chatbots based on Anthropic Projects service (using Claude models).
    • OpenAI CustomGPT-based Chatbots based on OpenAI CustomGPT service (using GPT models).
    • Google NotebookLM-based Chatbots based on Google NotebookLM service (using Gemini models).
  • Industry Applications, such as:
    • Legal Document Chatbots based on RAG systems (for contract analysis and legal research).
    • Medical Research Chatbots based on RAG systems (for healthcare information and clinical data).
    • Technical Support Chatbots based on RAG systems (for product documentation and troubleshooting).
  • Enterprise Implementations, such as:
    • Corporate Knowledge Base Chatbots based on RAG systems (for internal documentation).
    • Customer Support Chatbots based on RAG systems (for support tickets).
    • Research Assistant Chatbots based on RAG systems (for market research).
  • ...
• Counter-Examples:
  • Basic Chatbots, which lack knowledge retrieval capabilities.
  • Rule-Based Systems, which use predefined response patterns.
  • Pure LLM Chatbots, which don't use external knowledge.
• See: Retrieval Augmented Generation, Language Model, Knowledge Base System, Conversational AI.

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A Platform RAG Chatbot is a custom RAG chatbot that leverages a specific AI platform's models and infrastructure (to provide context-aware responses).

• Context:
  • It can access Platform Models through api integration.
  • It can utilize Platform Tools for task execution.
  • It can manage Document Storage using platform infrastructure.
  • It can handle Authentication via platform security.
  • It can support Platform Integrations with other services.
  • ...
  • It can range from being a Basic Platform Implementation to being an Enterprise Platform Deployment, depending on its usage scope.
  • It can range from being a Single Purpose Platform Bot to being a Multi Function Platform System, depending on its capability set.
  • ...
• Examples:
  • Major Implementations, such as:
    • Anthropic Projects-based Chatbots using Claude capabilitys.
    • OpenAI CustomGPT-based Chatbots using GPT capabilitys.
    • Google NotebookLM AI Productivity Service using Gemini capabilitys.
  • ...
• Counter-Examples:**
  • Custom Built Chatbots without platform integration.
  • Generic RAG Systems using open source models.
  • Hybrid Implementations combining multiple platforms.
• See: AI Platform, Cloud Infrastructure, API Integration, Enterprise AI System.

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