Centered on AI AMAZE, the company has developed a suite of AI Agent products tailored to various industries. It offers a one-stop, no-code AI service platform that enables enterprises to quickly build their own AI agents without requiring technical expertise.

The platform supports multiple devices and over 10 languages, delivers responses in as fast as 1.5 seconds, and integrates multimodal interactions—including voice, text, and images—to create more human-like, intelligent customer service and guided experience solutions.

1. Enterprise AI Agent Workflow Automation Platform (Enterprise AI Agent): Enables enterprises to implement AI Agents, integrating internal and external data sources to automatically execute data analysis, cross-system collaboration, information processing, and business workflows. It helps enterprises establish intelligent and automated operational processes, reducing manual processing costs and enhancing operational efficiency.

2. Data Integration and Intelligent Analysis Services: Integrates heterogeneous internal and external data sources within the enterprise, performing data cleaning, aggregation, and analysis to automatically generate visualized reports and actionable decision-making insights.

3. Gen BI: Utilizes generative AI to automatically generate business analysis reports and visual charts, rapidly converting raw data into managerial decision-making insights to accelerate the enterprise decision-making process.

4. AI Interview / Listen ME: Provides AI-powered automated interview and research tools, supporting interview design, Q&A execution, transcription generation, and analysis.

5. AI Intelligent Customer Service System: Automatically responds to customer inquiries using natural language understanding (NLU) technology, providing real-time and consistent customer support to reduce labor burdens and enhance service quality.
(The content above was translated by AI.)

Real-Time Game Translation System for Gamers – A system featuring screen projection, optical character recognition (OCR), and real-time multilingual translation. Built on generative AI, it is trained with large-scale game data, utilizes the team’s patented NLP processes, and integrates various style models along with a custom game-specific dictionary to provide locally optimized, high-quality translations. The primary target users are gamers, offering real-time translation for games without localized language support, while secondary users include indie and small-to-medium game developers.

MaiGPT Enterprise AI Assistant Platform:
Provides an enterprise-grade GPT for internal company use, supporting multi-model switching, single sign-on (SSO), access control, usage analytics, knowledge-base Q&A, document analysis, content generation, and multi-channel deployment. It helps employees use AI safely and efficiently within the organization.
AI KM Enterprise Knowledge Management System:
Helps enterprises transform PDFs, Word files, Excel spreadsheets, PPTs, webpages, SOPs, FAQs, product manuals, and internal documents into searchable, citable, and permission-controlled AI knowledge bases. It supports RAG retrieval, source citation, knowledge classification, document version control, and access management.
Agent Development Platform:
Provides a low-code environment for building customized AI agents, supporting prompt configuration, knowledge-base integration, tool calling, API integration, Text-to-SQL, workflow design, and testing/validation. It can be applied to customer service, internal assistants, data querying, process automation, and industry-specific scenarios.
Multi-Channel AI Conversational Services:
Helps enterprises deploy AI agents across multiple channels, including websites, LINE, WhatsApp, Messenger, Instagram, Telegram, Microsoft Teams, and APIs. This enables organizations to integrate AI into existing customer service and internal collaboration workflows.
Text-to-SQL / Data Query Agents:
Enables enterprises to connect databases with AI agents, allowing users to query reports, orders, inventory, operational data, and other structured datasets using natural language, reducing reliance on engineering or data teams.