Conversational AI-based Service

A Conversational AI-based Service is an online service that utilizes AI technology for conversational capability (enable conversational interactions between service users and AI-based systems).

• AKA: Conversational AI Service, AI Chatbot Service, Intelligent Conversational Service, AI Dialog Service.
• Context:
  • It can typically provide conversational AI-based service interaction through conversational AI-based service interfaces, conversational AI-based service response generation, and conversational AI-based service dialog management.
  • It can typically process conversational AI-based service user input via conversational AI-based service natural language understanding, conversational AI-based service intent recognition, and conversational AI-based service entity extraction.
  • It can typically maintain conversational AI-based service conversation flow with conversational AI-based service turn management, conversational AI-based service topic tracking, and conversational AI-based service coherence mechanisms.
  • It can typically generate conversational AI-based service output through conversational AI-based service response formulation, conversational AI-based service tone adaptation, and conversational AI-based service format selection.
  • It can typically implement conversational AI-based service quality control through conversational AI-based service content filtering, conversational AI-based service safety measures, and conversational AI-based service output moderation.
  • It can typically maintain conversational AI-based service user session with conversational AI-based service context tracking, conversational AI-based service conversation history, and conversational AI-based service personalization.
  • It can typically implement conversational AI-based service availability through conversational AI-based service cloud infrastructure, conversational AI-based service scaling mechanisms, and conversational AI-based service redundancy systems.
  • ...
  • It can often utilize conversational AI-based service technology such as conversational AI-based service language models, conversational AI-based service dialog frameworks, and conversational AI-based service semantic processing.
  • It can often support conversational AI-based service personalization with conversational AI-based service user profiling, conversational AI-based service preference learning, and conversational AI-based service adaptive response.
  • It can often provide conversational AI-based service business value through conversational AI-based service customer engagement, conversational AI-based service operational efficiency, and conversational AI-based service user satisfaction.
  • It can often integrate with conversational AI-based service enterprise systems through conversational AI-based service API connections, conversational AI-based service data exchange, and conversational AI-based service workflow automation.
  • It can often implement conversational AI-based service security measures including conversational AI-based service authentication, conversational AI-based service data protection, and conversational AI-based service access control.
  • It can often collect conversational AI-based service usage analytics for conversational AI-based service performance optimization, conversational AI-based service user behavior analysis, and conversational AI-based service continuous improvement.
  • It can often utilize conversational AI-based service AI models such as conversational AI-based service language models, conversational AI-based service intent classifiers, and conversational AI-based service knowledge base.
  • ...
  • It can range from being a Text-based Conversational AI-based Service to being a Voice-based Conversational AI-based Service to being a Graphical Conversational AI-based Service to being a Multimodal Conversational AI-based Service, depending on its conversational AI-based service interaction modality.
  • It can range from being a Single-Turn Conversational AI-based Service to being a Multi-Turn Conversational AI-based Service, depending on its conversational AI-based service dialog complexity.
  • It can range from being an Information-Focused Conversational AI-based Service to being an Agent-Capable Conversational AI-based Service, depending on its conversational AI-based service action capability.
  • It can range from being a Web-based Conversational AI-based Service to being a Mobile Conversational AI-based Service to being a Device-Specific Conversational AI-based Service, depending on its conversational AI-based service platform deployment.
  • It can range from being an Open-Topic Conversational AI-based Service to being a Domain-Specific Conversational AI-based Service, depending on its conversational AI-based service knowledge scope.
  • It can range from being a Simple Conversational AI-based Service to being a Complex Conversational AI-based Service, depending on its conversational AI-based service capability sophistication.
  • It can range from being a Rule-Based Conversational AI-based Service to being a Learning-Based Conversational AI-based Service, depending on its conversational AI-based service adaptation approach.
  • It can range from being a Reactive Conversational AI-based Service to being a Proactive Conversational AI-based Service, depending on its conversational AI-based service initiation pattern.
  • It can range from being a Pure-Text Conversational AI-based Service to being a RAG-based Conversational AI-based Service, depending on its conversational AI-based service information retrieval approach.
  • It can range from being a Free Conversational AI-based Service to being a Premium Conversational AI-based Service, depending on its conversational AI-based service monetization model.
  • It can range from being a Consumer Conversational AI-based Service to being an Enterprise Conversational AI-based Service, depending on its conversational AI-based service target audience.
  • It can range from being a Cloud-Hosted Conversational AI-based Service to being an On-Premise Conversational AI-based Service, depending on its conversational AI-based service deployment model.
  • ...
  • It can require conversational AI-based service infrastructure including conversational AI-based service computing resources, conversational AI-based service network capacity, and conversational AI-based service storage systems.
  • It can implement conversational AI-based service business models such as conversational AI-based service subscription pricing, conversational AI-based service usage-based billing, and conversational AI-based service freemium approach.
  • It can address conversational AI-based service security requirements through conversational AI-based service authentication, conversational AI-based service data protection, and conversational AI-based service access control.
  • It can support conversational AI-based service user experience via conversational AI-based service response speed, conversational AI-based service interface design, and conversational AI-based service error handling.
  • It can include conversational AI-based service development tools for conversational AI-based service conversation design, conversational AI-based service intent configuration, and conversational AI-based service testing procedures.
  • It can implement conversational AI-based service compliance measures for conversational AI-based service data regulation, conversational AI-based service privacy protection, and conversational AI-based service ethical guidelines.
  • ...
• Examples:
  • Virtual Assistant Conversational AI-based Services, such as:
    • General-Purpose Virtual Assistants, such as:
      • Apple Siri (2011), providing voice-controlled assistance for iOS ecosystem.
      • Google Assistant (2016), offering multi-device conversation with search integration.
      • Amazon Alexa (2014), enabling smart home control through voice interaction.
      • Microsoft Cortana (2014), supporting personal productivity with Windows integration.
    • Domain-Specific Virtual Assistants, such as:
      • Bank of America Erica (2018), handling financial transaction and account management.
      • Lark Health Assistant (2015), supporting health coaching and wellness monitoring.
      • Marriott ChatBot (2017), facilitating hotel reservation and guest service.
  • Generative AI Conversational Services, such as:
    • LLM-based Conversational Services, such as:
      • OpenAI ChatGPT (2022), providing text-based dialog with general knowledge.
      • Anthropic Claude (2023), offering constitutional AI conversation with safety alignment.
      • Google Bard (2023), delivering information-seeking dialog with multimodal capability.
    • Specialized LLM Services, such as:
      • GitHub Copilot Chat (2023), supporting code-related conversation for developer productivity.
      • Notion AI (2022), enhancing document writing with contextual assistance.
      • Microsoft Bing Chat (2023), combining web search with conversational interaction.
  • Enterprise Conversational AI-based Services, such as:
    • Customer Support Conversational Services, such as:
      • Zendesk Answer Bot (2017), providing ticket deflection through automated response.
      • IBM Watson Assistant (2016), enabling customer service automation with enterprise integration.
      • Intercom (2011), supporting website visitor engagement with lead qualification.
      • LivePerson Conversational Cloud (2018), enabling omnichannel support with AI-powered messaging.
      • Ada Support (2016), delivering automated customer experience with no-code bot builder.
    • Employee Assistance Conversational Services, such as:
      • Microsoft Copilot for Microsoft 365 (2023), enhancing workplace productivity with office integration.
      • Workday Assistant (2019), providing HR process support for employee self-service.
      • ServiceNow Virtual Agent (2018), automating IT service desk with workflow integration.
  • Industry-Specific Conversational AI-based Services, such as:
    • Healthcare Conversational Services, such as:
      • Babylon Health (2013), offering symptom assessment and medical triage.
      • Woebot (2017), providing mental health support through therapeutic conversation.
      • Ada Health (2011), delivering health information with symptom checking.
    • Financial Conversational Services, such as:
      • Capital One Eno (2017), monitoring credit card transactions and account security.
      • Kasisto KAI Banking (2013), enabling banking interaction through financial dialog.
      • Cleo (2016), providing personal finance management with budgeting assistance.
    • Retail Conversational Services, such as:
      • H&M Virtual Stylist (2018), assisting with fashion recommendation and outfit selection.
      • Sephora Beauty Bot (2016), guiding product discovery and makeup tutorial.
  • Platform-Integrated Conversational AI-based Services, such as:
    • Social Media Conversational Services, such as:
      • Facebook Messenger Platform (2016), supporting business messaging with automated response.
      • WhatsApp Business API (2018), enabling customer communication through messaging workflow.
      • WeChat Mini Programs (2017), integrating service automation within messaging ecosystem.
    • Workplace Conversational Services, such as:
      • Slack App Directory (2015), enhancing team collaboration with conversational workflow.
      • Microsoft Teams Conversational Bot (2017), supporting meeting assistance and information retrieval.
      • Discord Bot (2015), providing community management for digital community.
  • Implementation Category Conversational AI-based Services, such as:
    • Multi-Turn Text-based Conversational AI-based Services, such as:
      • OpenAI ChatGPT Service (2022), for extended conversation.
      • Microsoft Bing Chat (2023), for search-augmented conversation.
      • Google Bard Chat (2023), for information-seeking dialog.
    • Document-focused Conversational AI-based Services, such as:
      • Mendable AI (2022), for technical documentation navigation.
      • Kagi Universal Summarizer (2023), for content summarization.
    • Voice-based Digital Personal Assistants, such as:
      • Apple Siri (2011), for hands-free interaction.
      • Amazon Alexa (2014), for voice-controlled home automation.
      • Google Assistant (2016), for voice-activated search.
  • ...
• Counter-Examples:
  • Traditional Web Forms, which collect user input through structured fields rather than natural conversation.
  • Command-Line Interface Tools, which accept structured commands rather than natural language input.
  • Static FAQ Systems, which provide pre-defined answers without dynamic conversation capability.
  • Human Customer Service Systems, which rely on human agents rather than AI-based response generation.
  • Non-Interactive AI Services, which perform data analysis or processing without conversational engagement.
  • Form-Based Web Applications, which collect user input through structured form fields instead of conversational exchange.
• See: Conversational AI, AI-Based Interactive Service, Conversation-Centered Artificial Intelligence System, Chatbot System, Virtual Assistant Technology, Natural Language Processing Service, Digital Customer Experience Platform, Automated Customer Service System, AI-Supported Software Service.

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References

2023

• GBard
  • There are several different types of chatbot services user interfacees. Here are some of the most common:
    • Text-based Chatbot Service: Text-based chatbots are the most common type of chatbot user interface. They allow users to interact with the chatbot using text-based commands or by typing natural language queries.
    • Voice-based Chatbot Service: Voice-based chatbots allow users to interact with the chatbot using voice commands. This is a convenient option for users who are on the go or who have difficulty typing.
    • Graphical Chatbot Service: Graphical chatbots use a graphical user interface to allow users to interact with the chatbot. This type of user interface is often used for chatbots that provide customer service or support, as it can be more user-friendly and visually appealing than text-based chatbots.
    • Multimodal Chatbot Service: Multimodal chatbots combine elements of text-based, voice-based, and graphical chatbots. This allows users to interact with the chatbot in the way that is most convenient for them.

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