Maum AI

什麼是 Maum AI？

Maum AI, at maum.ai, is an enterprise AI platform organized into Builder tools, Simulation and Customized services. Teams can prepare business data, train a company-specific model, obtain it through Cloud API and connect it with other model or service APIs in Maum Orchestra.

The workflow supports scenario-based chatbots and corporate GPT applications built from company documents and service knowledge. It combines reusable software tools with optional training, integration and consulting work. Designing scenarios, configuring API properties and testing the results are part of implementation.

Maum AI 能做什麼？

Business-data preparation and model training

Use MaumDATA for preprocessing and upload Excel files or digital documents for company-specific training. The resulting AI model is exposed through Cloud API.

API workflow composition

Connect Maum AI models, chatbot engines and third-party service APIs as blocks in Orchestra. Drag-and-drop composition is combined with JavaScript configuration of block properties.

Scenario-based chatbot development

Organize service stages, questions and responses in an Excel scenario template, build and test the chatbot, then use its API specification in an app or website.

Corporate GPT and simulation

Train a company-specific GPT using manuals, FAQs or other business knowledge, test it through maumChatbot and combine the resulting API with other services. The Simulation section also provides model/service demonstrations.

使用情境

“Build a customer-support chatbot”

Prepare product information, FAQs and service scenarios, then test responses before integrating the chatbot into a customer-facing site or app.

“Query company-specific knowledge”

Use company documents and manuals to prepare a corporate GPT model, test its answers and expose it as an API for business workflows.

“Prototype a connected AI service”

Compose model and service API blocks in Orchestra, configure their properties and inspect the resulting workflow before broader deployment.

“Evaluate a custom model”

Start with business data and a defined use case, generate a model through training and use Cloud API and simulation tools to test how it handles the intended inputs.

常見問題

What does the platform include?

Builder covers MaumDATA preprocessing and Orchestra API workflows. Simulation includes maumChatbot with maumGPT, AI Human M3 and AI-service demonstrations. Customized services cover fine-tuning, implementation guidance and training support; the exact delivery depends on the selected service.

Can I use it free indefinitely?

The published offer allows platform services for one month after sign-up, with an initial model-usage allowance. Continuing model inference after that allowance requires payment. Inference and company-specific training have separate charges, depending on the service type.

Is Orchestra entirely code-free?

Orchestra uses drag-and-drop API blocks, but its guide specifies JavaScript for the properties of models, chatbot engines and service APIs. Plan for configuration work and supported API specifications; the visual workflow does not imply automatic compatibility with every external service.

What do I prepare for a chatbot or corporate GPT?

Define the service purpose, conversation stages and required voice/language options. A scenario chatbot uses an Excel fact sheet; corporate GPT training can use company introductions, product manuals, FAQs and customer-service knowledge. Test and refine the result before integration.

What is delivered after company-specific training?

The trained model is made available as an API through Cloud API. Corporate GPT results can be tested in maumChatbot, and the model API can be connected to other APIs in Orchestra. Custom integration, model training and consulting are distinct parts of the engagement.

快速資訊

Product scope

Enterprise cloud AI platform

Platform sections

Builder, Simulation and Customized services

Typical inputs

Excel templates, digital documents, manuals and FAQs

Outputs

Trained model APIs and configurable chatbot/service workflows

Adoption model

Initial one-month/usage allowance; paid continued inference and custom training