MakeSomethingNew Launches AI Agent Building Service for Enterprises
MakeSomethingNew Inc. has launched a service to design and develop custom AI agents for enterprises. The service integrates generative AI with internal systems to automate tasks, offering end-to-end support from PoC to full-scale production.
📋 Article Processing Timeline
- 📰 Published: April 23, 2026 at 18:00
- 🔍 Collected: April 23, 2026 at 09:31
- 🤖 AI Analyzed: April 24, 2026 at 04:34 (19h 2m after Collected)
MakeSomethingNew Inc. (Headquarters: Tokyo; Representative Director: Eiichi Sugiyama) announces the launch of its AI Agent Building Service for enterprises.
This service utilizes generative AI such as ChatGPT and Claude to support the design, development, and implementation of AI agents that are ready for practical business use, encompassing everything from internal data search, information organization, and inquiry response, to integration with business systems and the assistance/automation of routine tasks.
In recent years, while the utilization of generative AI has advanced in many companies, there are quite a few cases where it remains at the 'trying it out in chat' stage and has not been sufficiently integrated into frontline operations. Particularly in enterprise deployments, systems and data are often dispersed across departments, making it crucial to design according to business workflows and integrate with existing systems in order to make it usable on the ground.
MakeSomethingNew addresses these challenges by individually designing AI agents tailored to each company's business and system environment, providing end-to-end support from Proof of Concept (PoC) all the way to full-scale production implementation. Rather than simply introducing an AI chat, we aim for AI utilization that is actually used internally and leads to tangible results.
Background
With the evolution of generative AI, business tasks such as information retrieval, document creation, inquiry handling, and knowledge sharing in enterprises are undergoing major changes. Furthermore, in recent years, there has been a growing interest in 'AI Agents' that do more than just answer questions; they assist operations by referencing multiple information sources and can integrate with internal systems as needed.
On the other hand, the following challenges are observed in actual enterprise implementations:
- Internal documents and data are scattered, making it difficult to reach the necessary information.
- AI is being tested, but it hasn't been incorporated into actual business workflows.
- It cannot link with CRMs, SFAs, and various business systems, making it hard to lead to operational improvements.
- It stops at departmental verification and does not proceed to production operation.
- The ideal form of AI utilization suited to the company's specific operations has not been clarified.
Given this background, the critical theme for companies is not just 'introducing AI' itself, but how to embed AI into operations and make it usable on the front lines.
Service Overview
MakeSomethingNew's AI Agent Building Service for enterprises designs, develops, and implements AI agents according to a company's operational challenges and existing system environment.
AI agents can search internal documents and knowledge bases to provide answers, organize information according to company rules, and assist with tasks by linking with various systems as necessary. This not only allows employees to quickly access the information they need but also leads to the streamlining of routine work and the standardization of business quality.
Additionally, MakeSomethingNew handles everything consistently—from conceptual consultation to requirements definition, design, development, verification, implementation, and operational support—assisting in realistic deployments tailored to each company's situation.
Demo Video
Features of this Service
1. Building AI agents tailored to each company's operations
The required form of AI utilization differs depending on the industry, department, and business content. Based on each company's business workflows and existing environment, MakeSomethingNew designs and builds AI agents suited to specific tasks such as information retrieval, inquiry response, document creation support, data referencing, and operational assistance.
2. Integration with internal systems and data to make it usable in practical business
Even if AI is introduced, its practical application is limited if it is not connected to internal documents and business systems. This service supports the construction of AI agents that can be used in frontline operations by integrating with files, databases, business applications, and various SaaS platforms.
3. Accompanying support from PoC to full production rollout
Many generative AI projects stall at the verification stage. This service goes beyond a one-off prototype; it provides end-to-end support from requirements definition to implementation and operation, with an eye toward continuous use in actual business operations.
4. Consistent support from conceptualization to implementation and operation
We also provide accompanying support from the conceptualization stage for initial challenges such as 'We don't know where to start' or 'It's hard to decide which operations to implement it in first.' We assist with everything from clarifying implementation themes to actual deployment according to each company's circumstances.
Anticipated Use Cases
This service is designed for corporate needs such as:
- Wanting to introduce an AI assistant capable of cross-searching internal knowledge.
- Wanting to streamline internal inquiry responses based on regulations, manuals, and FAQs.
- Wanting to advance AI utilization in sales, customer support, and back-office operations.
- Wanting to establish a system that can retrieve information across multiple internal systems.
- Wanting to expand AI utilization from departmental experiments to company-wide business improvements.
- New IT initiatives
This service utilizes generative AI such as ChatGPT and Claude to support the design, development, and implementation of AI agents that are ready for practical business use, encompassing everything from internal data search, information organization, and inquiry response, to integration with business systems and the assistance/automation of routine tasks.
In recent years, while the utilization of generative AI has advanced in many companies, there are quite a few cases where it remains at the 'trying it out in chat' stage and has not been sufficiently integrated into frontline operations. Particularly in enterprise deployments, systems and data are often dispersed across departments, making it crucial to design according to business workflows and integrate with existing systems in order to make it usable on the ground.
MakeSomethingNew addresses these challenges by individually designing AI agents tailored to each company's business and system environment, providing end-to-end support from Proof of Concept (PoC) all the way to full-scale production implementation. Rather than simply introducing an AI chat, we aim for AI utilization that is actually used internally and leads to tangible results.
Background
With the evolution of generative AI, business tasks such as information retrieval, document creation, inquiry handling, and knowledge sharing in enterprises are undergoing major changes. Furthermore, in recent years, there has been a growing interest in 'AI Agents' that do more than just answer questions; they assist operations by referencing multiple information sources and can integrate with internal systems as needed.
On the other hand, the following challenges are observed in actual enterprise implementations:
- Internal documents and data are scattered, making it difficult to reach the necessary information.
- AI is being tested, but it hasn't been incorporated into actual business workflows.
- It cannot link with CRMs, SFAs, and various business systems, making it hard to lead to operational improvements.
- It stops at departmental verification and does not proceed to production operation.
- The ideal form of AI utilization suited to the company's specific operations has not been clarified.
Given this background, the critical theme for companies is not just 'introducing AI' itself, but how to embed AI into operations and make it usable on the front lines.
Service Overview
MakeSomethingNew's AI Agent Building Service for enterprises designs, develops, and implements AI agents according to a company's operational challenges and existing system environment.
AI agents can search internal documents and knowledge bases to provide answers, organize information according to company rules, and assist with tasks by linking with various systems as necessary. This not only allows employees to quickly access the information they need but also leads to the streamlining of routine work and the standardization of business quality.
Additionally, MakeSomethingNew handles everything consistently—from conceptual consultation to requirements definition, design, development, verification, implementation, and operational support—assisting in realistic deployments tailored to each company's situation.
Demo Video
Features of this Service
1. Building AI agents tailored to each company's operations
The required form of AI utilization differs depending on the industry, department, and business content. Based on each company's business workflows and existing environment, MakeSomethingNew designs and builds AI agents suited to specific tasks such as information retrieval, inquiry response, document creation support, data referencing, and operational assistance.
2. Integration with internal systems and data to make it usable in practical business
Even if AI is introduced, its practical application is limited if it is not connected to internal documents and business systems. This service supports the construction of AI agents that can be used in frontline operations by integrating with files, databases, business applications, and various SaaS platforms.
3. Accompanying support from PoC to full production rollout
Many generative AI projects stall at the verification stage. This service goes beyond a one-off prototype; it provides end-to-end support from requirements definition to implementation and operation, with an eye toward continuous use in actual business operations.
4. Consistent support from conceptualization to implementation and operation
We also provide accompanying support from the conceptualization stage for initial challenges such as 'We don't know where to start' or 'It's hard to decide which operations to implement it in first.' We assist with everything from clarifying implementation themes to actual deployment according to each company's circumstances.
Anticipated Use Cases
This service is designed for corporate needs such as:
- Wanting to introduce an AI assistant capable of cross-searching internal knowledge.
- Wanting to streamline internal inquiry responses based on regulations, manuals, and FAQs.
- Wanting to advance AI utilization in sales, customer support, and back-office operations.
- Wanting to establish a system that can retrieve information across multiple internal systems.
- Wanting to expand AI utilization from departmental experiments to company-wide business improvements.
- New IT initiatives