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Tailored AI Chatbot Solutions Boosting Productivity

Tailored AI Chatbot Solutions
Boosting Productivity

AI chatbots can be developed in various forms, ranging from generative AI-based chatbots to
natural language processing chatbots and simple rule-based chatbots, depending on the intended use.
HIVELAB designs and provides customized AI chatbots optimized for each client's characteristics and intended use.

Hivelab provides tailored AI chatbot solutions boosting productivity.

HIVELAB's AI chatbot solutions meet a variety of needs,
including improving work efficiency, providing customer support,
and developing generative AI based on internal corporate data.

  • LLM with RAG

    RAG (Research Augmented Generation)-based LLM chatbots reference specific databases to generate answers, reducing hallucinations and providing accurate responses. HIVELAB's chatbot solutions offer LLM with RAG-based chatbots that reference internal corporate data or specialized databases.

  • Scenario Chatbot

    Rule-based chatbots, capable of providing simple answers based on predefined rules, are ideal for simple tasks. Natural language processing and machine learning-based chatbots can understand the intent and context of questions, making them ideal for customer support.

  • Integrating AI Chatbots with Business Systems

    When AI chatbots are integrated with business systems, they can perform even more functions. HIVELAB provides AI chatbot interfaces that integrate with various business systems and APIs. This allows AI chatbots to perform a variety of tasks, such as analyzing data, creating infographics and dashboards, verifying brand guideline violations, processing reservations and refunds, and uploading social content and sending messages.

Tailored AI Chatbot Solutions
Process

HIVELAB provide AI chatbot solutions that best fit your purpose and core functions.

Define chatbot, select tech, build data, train, customize and update continuously.

01 Definition of AI Chatbot (Purpose, Users, Application Channels, Core Functions)

02 Technology Stack of AI Chatbot (LLM with RAG, NLP/ML, Rule-based)

03 Building Learning Database, Designing Conversation Scenarios and Interfaces

04 Learning and Training of AI Models, and Developing AI Chatbot Integration Functions

05 Customized AI Chatbot Utilization and Continuous Learning Updates