AI Agent Infrastructure Development AI エージェント基盤構築支援
Support for AI Agent Infrastructure Development
We provide end-to-end support for building the MCP server and data infrastructure, which form the foundation for utilizing AI agents.
Challenges Challenges in Building AI Agents
- There is often no adequate common foundation—such as an MCP or data platform—in place to operate AI before initiating a PoC or custom implementation.
- Time and costs tend to increase significantly when addressing security and governance requirements, coordinating across departments, and integrating with existing systems.
Service Support Details
MCP Infrastructure Development Support
- Integration design and implementation with existing systems, tools, and data platforms
- Platform architecture design with a focus on scalability and security
Data Infrastructure Development Support
- Establishment of data collection, storage, and processing workflows
- Standardization and API enablement for providing data to AI agents
Features Service Features
Compatible with
multi-cloud environments
(AWS / Azure / GCP)
Flexible support ranging
from small-scale PoC to full-scale implementation
One-stop service
minimizing communication costs
Issues
Customer Challenges
-
Repeated PoCs lead to custom development with little reusability.
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Data is siloed across departments, and no common AI agent platform exists.
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Secure integration is needed, including proper security and access control.
Expected Effects
The MCP foundation enables rapid deployment of new AI agents.
Standardized data integration lowers development costs.
Unified access control and logging strengthen governance.
Easily extends to new AI models and data sources.
Architecture Examples on AWS
Example of infrastructure construction on AWS
