LaKeel Announces "LaKeel Agentic Assistant," an AI Agent Building System
LaKeel Inc. will launch "LaKeel Agentic Assistant" in April 2026, an AI agent building system that autonomously links and analyzes information from dispersed internal systems to support real-time responses and task execution. This system aims to dramatically improve operational efficiency across organizations by enabling AI to act as an agent that completes practical tasks.
📋 Article Processing Timeline
- 📰 Published: April 1, 2026 at 00:30
- 🔍 Collected: April 1, 2026 at 01:06 (36 min after Published)
- 🤖 AI Analyzed: April 22, 2026 at 09:11 (512h 4m after Collected)
LaKeel Inc. (Headquarters: Minato-ku, Tokyo; President & CEO: Tsutomu Kubo; hereinafter "LaKeel") will begin offering "LaKeel Agentic Assistant," an AI agent building system that enables AI to autonomously link and analyze information from dispersed internal systems to support real-time responses and task execution, starting in April 2026.
This system is built on the "LaKeel DX" system development and operation platform, allowing users to easily build "AI agents" that autonomously extract necessary information and perform practical tasks. The MCP (Model Context Protocol) server, integrated into "LaKeel DX," enables seamless connection with various internal and external systems. Users can quickly build agents optimized for practical tasks from a settings screen using natural language, without programming.
Furthermore, by utilizing RAG (Retrieval-Augmented Generation) technology, accurate responses and judgments based on textual information such as internal regulations and manuals are possible. By autonomously executing tasks consistently from information reference to task delegation, it establishes a sustainable workflow that does not depend on specific personnel, thereby promoting dramatic operational efficiency across the entire organization.
**■ Background: From "Information Search and Response" to "Completion of Practical Tasks"**
Enterprise data is fragmented across individual systems (HR, accounting, core systems, etc.). Traditional AI chatbots could provide prescribed "responses" but could not handle "execution of practical tasks" across multiple systems. As a result, ancillary tasks such as information search and re-execution in individual systems have become a significant burden. "LaKeel Agentic Assistant" enables AI to autonomously find necessary data and consistently perform tasks from information linkage to procedure execution. As an "agent that completes practical tasks" beyond mere conversation, it creates an environment where people can concentrate on higher-value work.
**■ Key Features and Characteristics**
**● Conversational Interface for Completing Practical Tasks**
Personnel responsible for building AI agents can set items such as "role," "skills," and "(linked) tools" using natural language. Business users can simply request tasks from the AI in a chat format, and the AI will immediately perform cross-system data acquisition, reference the latest information using web search, and delegate tasks.
**● Seamless System Integration with MCP Server**
"LaKeel DX" provides a mechanism to catalog all functions of linked systems and the LaKeel series. By integrating the MCP server into this mechanism, AI agents can utilize all systems and functions registered in the catalog as "tools they can use."
**● Secure Reference Environment with Thorough Access Control**
It inherits access rights from existing systems, ensuring that AI does not acquire information beyond the user's viewing permissions. Combined with accurate internal regulation referencing using RAG technology, it realizes secure information utilization.
**■ Usage Scenario**
**HR Domain: Leave and Return-to-Work Management (Agent Building and Usage Example)**
First, by linking employment regulations and HR systems, a company-specific "Leave and Return-to-Work Agent" that understands the leave and return-to-work workflow is created.
Then, HR personnel
This system is built on the "LaKeel DX" system development and operation platform, allowing users to easily build "AI agents" that autonomously extract necessary information and perform practical tasks. The MCP (Model Context Protocol) server, integrated into "LaKeel DX," enables seamless connection with various internal and external systems. Users can quickly build agents optimized for practical tasks from a settings screen using natural language, without programming.
Furthermore, by utilizing RAG (Retrieval-Augmented Generation) technology, accurate responses and judgments based on textual information such as internal regulations and manuals are possible. By autonomously executing tasks consistently from information reference to task delegation, it establishes a sustainable workflow that does not depend on specific personnel, thereby promoting dramatic operational efficiency across the entire organization.
**■ Background: From "Information Search and Response" to "Completion of Practical Tasks"**
Enterprise data is fragmented across individual systems (HR, accounting, core systems, etc.). Traditional AI chatbots could provide prescribed "responses" but could not handle "execution of practical tasks" across multiple systems. As a result, ancillary tasks such as information search and re-execution in individual systems have become a significant burden. "LaKeel Agentic Assistant" enables AI to autonomously find necessary data and consistently perform tasks from information linkage to procedure execution. As an "agent that completes practical tasks" beyond mere conversation, it creates an environment where people can concentrate on higher-value work.
**■ Key Features and Characteristics**
**● Conversational Interface for Completing Practical Tasks**
Personnel responsible for building AI agents can set items such as "role," "skills," and "(linked) tools" using natural language. Business users can simply request tasks from the AI in a chat format, and the AI will immediately perform cross-system data acquisition, reference the latest information using web search, and delegate tasks.
**● Seamless System Integration with MCP Server**
"LaKeel DX" provides a mechanism to catalog all functions of linked systems and the LaKeel series. By integrating the MCP server into this mechanism, AI agents can utilize all systems and functions registered in the catalog as "tools they can use."
**● Secure Reference Environment with Thorough Access Control**
It inherits access rights from existing systems, ensuring that AI does not acquire information beyond the user's viewing permissions. Combined with accurate internal regulation referencing using RAG technology, it realizes secure information utilization.
**■ Usage Scenario**
**HR Domain: Leave and Return-to-Work Management (Agent Building and Usage Example)**
First, by linking employment regulations and HR systems, a company-specific "Leave and Return-to-Work Agent" that understands the leave and return-to-work workflow is created.
Then, HR personnel