RAToRu: Agentic AI, Multi-Agent Collaboration & RAG - The Future of Intelligent System

 

Hello from I-ON Communications!

You’ve probably been using AI tools like ChatGPT or Gemini in your daily life or at work.

These days, AI helps us get answers quickly and efficiently.

But here’s the catch: these AI systems don’t actually perform the task for you

—they only provide answers to your queries.

So, what if there was an AI that not only finds the information you need

but also executes tasks on your behalf? Sounds convenient, doesn’t it?

Today, we’re excited to introduce RAToRu, Korea’s first intelligent AI solution based on MCP (Model Context Protocol)—designed not just for extracting information, but for actually getting work done.

RAToRu is Korea’s first intelligent AI solution based on MCP (Model Context Protocol), developed by I-ON Communications.

RAToRu was designed to make full use of all corporate data in real time by storing it in a RAG system , enabling AI client services to make full use of an organization’s data.

In simple terms, you can think of RAToRu as a business-oriented AI solution that connects a company’s existing systems with AI, helping to execute actual business tasks.

So, what exactly can RAToRu do, and how does it work?

Here’s an overview of RAToRu’s three key components.

First, let’s take a look at RAGo, which represents the “RA” in RAToRu.

RAG (Retrieval-Augmented Generation) uses data as its foundation to generate accurate searches and responses.

Next, we have ToolHUB, which corresponds to the “To” in RAToRu.

ToolHUB serves as a central hub for connecting with various system APIs, enabling seamless integration across different platforms.

Finally, there’s Rubix, which represents the “Ru” in RAToRu.

Rubix acts as a conversational interface connecting users with AI.

It creates role-specific agents in parallel within the chat client, then aggregates and reviews their outputs before delivering the final response.

So, how exactly can RAToRu be used in practice?

Here are some practical use cases for RAToRu:

• Enables searching, summarizing, and querying through a LLM based on internal corporate data.
  

• Allows rapid system updates whenever new assets are added.

• Enables the integration and orchestration of internal and external system APIs using the MCP server and associated tools.
• Supports authentication, registration, approval, and execution of tasks across all API-controlled systems within the enterprise, including sending messages and emails.

So, what sets RAToRu apart from other AI solutions?

• RAGo overcomes the limitations of standard RAG systems with the “RAPTOR” approach, enhancing overall performance. It restructures long-form data into hierarchically clustered chunks based on relevance, maintaining the full context of any query.

• ToolHUB offers robust tool integration and management capabilities. Through ToolHUB, existing ICS REST APIs can be converted into tools for use within the MCP server, enabling seamless workflow automation.

• RAToRu is built on a standardized protocol, offering exceptional scalability and flexibility. It incorporates multi-agent systems and LLMs to enhance response quality—whether by querying multiple agents or aggregating outputs based on their roles.

• RAToRu operates independently of any specific LLM base model. Users can choose from public LLM services like ChatGPT, Gemini, Claude, or enterprise/private LLMs such as LG ExaONE, QWEN, Gemma, depending on their needs.

Today, we’ve introduced RAToRu, I-ON Communications’ innovative AI solution.

We hope this gave you a clear understanding of RAToRu. If you have any questions or would like to learn more, please feel free to contact us.

As always, We are  here as your reliable business partner, ready to support you.

Wishing you all a great day!

Thank you.