Advanced AI 대화형 에이전트 Tools for Professionals

Discover cutting-edge AI 대화형 에이전트 tools built for intricate workflows. Perfect for experienced users and complex projects.

AI 대화형 에이전트

  • Asteroid lets you design, train, and embed AI-powered customer service chat agents that handle inquiries and automate workflows.
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    What is Asteroid AI?
    Asteroid AI offers a comprehensive suite for creating intelligent conversational agents without coding. Businesses start by uploading documentation, FAQs, or product catalogs into Asteroid’s knowledge base. The platform uses advanced NLP and machine learning to train, refine, and personalize agent responses. Teams can customize personalities, set fallback rules, and define automated workflows for lead qualification or ticket routing. Once configured, agents can be deployed on websites, mobile apps, or messaging platforms via simple embed codes or API integrations. Real-time dashboards track conversations, user satisfaction, and agent performance metrics, enabling ongoing optimization. Security features include data encryption, role-based access controls, and compliance with major privacy standards. Asteroid scales from small startups to enterprise deployments, streamlining customer engagement and operational efficiency.
  • Autodm AI boosts consumer-brand interactions with personalized and conversational AI experiences.
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    What is Autodm?
    Autodm AI is a generative AI platform designed to create conversational agents that mimic human interactions. These intelligent agents can manage multiple conversations simultaneously, providing personalized and immersive experiences that increase customer engagement and sales. The platform offers multi-agent orchestration, data management, and advanced moderation features. It's specifically engineered for public and private organizations looking to improve customer service, automate responses, and gain deeper insights into consumer behavior.
  • Mobile AI Agent that integrates with Anna Money to provide conversational financial insights, expense categorization, and budgeting advice.
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    What is Anna Mobile LLM Agent?
    Anna Mobile LLM Agent is a conversational AI framework designed for seamless integration within the Anna Money mobile app. It employs large language models to interpret user natural language inputs, fetch real-time account and transaction data via secure APIs, and perform tasks such as expense categorization, transaction summarization, and budgeting advice. Developers can configure custom tools, triggers, and context memories to tailor the agent to specific financial workflows. With built-in support for OpenAI, Azure OpenAI, and local transformers models, as well as a React Native front-end, the agent ensures responsive, secure, and personalized financial assistance on both iOS and Android devices.
  • An AI agent platform enabling users to build, customize, and deploy knowledge-powered chatbots with document ingestion and enterprise integrations.
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    What is Bolna AI Platform?
    Bolna AI Platform provides a comprehensive suite for building AI-driven conversational agents. It features a visual builder for designing dialogue flows, a robust document ingestion pipeline with semantic vector search for knowledge retrieval, and support for multiple languages. Integrations with Slack, Microsoft Teams, and website widgets are available out of the box, while APIs allow deep embedding into custom applications. Analytics dashboards offer insights on usage and performance. Bolna’s modular architecture enables rapid prototyping, iterative refinement, and scalable deployment across enterprise environments.
  • Open-source end-to-end chatbot using Chainlit framework for building interactive conversational AI with context management and multi-agent flows.
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    What is End-to-End Chainlit Chatbot?
    e2e-chainlit-chatbot is a sample project demonstrating the complete development lifecycle of a conversational AI agent using Chainlit. The repository includes end-to-end code for launching a local web server that hosts an interactive chat interface, integrating with large language models for responses, and managing conversation context across messages. It features customizable prompt templates, multi-agent workflows, and real-time streaming of responses. Developers can configure API keys, adjust model parameters, and extend the system with custom logic or integrations. With minimal dependencies and clear documentation, this project accelerates experimentation with AI-driven chatbots and provides a solid foundation for production-grade conversational assistants. It also includes examples for customizing front-end components, logging, and error handling. Designed for seamless integration with cloud platforms, it supports both prototype and production use cases.
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