Generative AI & AI Agent Development

End-to-End Support for
Generative AI & AI Agent Development from PoC to Production— End-to-End Support

From requirements definition, PoC, development, and production operations, our dedicated team provides comprehensive support. By leveraging offshore resources, we help achieve both faster delivery and lower costs.

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500 Engineers
100+ Clients
220+ Development Projects
2〜4wks PoC Startup
⏱
PoC Small Start
Validated in 2–4 weeks
BAP AI Delivery Monitor
JP
Japan Point of Contact: PM / BrSE
Requirements Definition & Japanese Communication
100% Japanese Support
PoC → Production Deployment
JP
AI Engineering Team
RAG Development, LLM Integration, Agent Design
Team of 500+
ISO 27001 / 9001 · Operational Stability v2.6.4
📊
Cost Optimization
Offshore Leverage
PROBLEM

Don't you have these challenges?

Tried generative AI, but got stuck at PoC and couldn't move to production
No in-house specialists in AI agents or LLM integration
Can't decide which use case to tackle first
Want AI to correctly reference internal knowledge, but don't know how
Concerned about security and operational structure, unable to take the next step
Can't determine whether in-house development or outsourcing is more appropriate
What matters most is not technology selection, but "designing with production in mind" and "articulating business challenges.
SOLUTION 01

AI Agent Development

We design and develop AI agents that autonomously execute tasks by selecting and combining multiple tools and data sources to achieve your goals.

Design & Implementation

  • Agent design aligned with business workflows (phased design of autonomous scope)
  • Tool integration with external systems and APIs

Quality & Operations

  • Evaluation of output quality and continuous improvement design
  • Support ranging from semi-autonomous (with human review checkpoints) to fully phased autonomy
SOLUTION 02

Generative AI / RAG Development / ChatGPT Integration

RAG Development

  • A system that references internal documents and manuals to provide answers with cited evidence
  • Design built on the premise of proper data handling and permission management

ChatGPT Integration & App Development

  • API integration with existing systems and chat tools
  • Generative AI app development: document summarization, internal chatbots, content generation support
TECH STACK

Technology Coverage Areas

LLM / Foundation Model Integration

API integration with major large language models

RAG Infrastructure

Knowledge retrieval via vector search and document search

Backend

API development and existing system integration

Frontend

Web / chat UI and business applications

Cloud & Infrastructure

Building and operating in cloud environments

Security

Authentication, access management, and data isolation design

※ Specific technologies adopted will be selected based on requirements.

WHY US

Why Choose Us

01
Cost Optimization through Offshore Development

Backed by a team of 500+ engineers, we deliver development on a variable-cost model that keeps fixed costs low while maintaining quality. Supports both lab-type and contract-based engagements.

02
Direct Dialogue with Technically Skilled BrSEs

All our BrSEs come from engineering backgrounds. With many holding N1/N2 Japanese proficiency, they go beyond interpreting — they understand the technical and business essence, preventing rework and miscommunication.

03
From PoC (2–4 Weeks) to Full Production

We validate feasibility through a small-scale start in 2–4 weeks, then provide end-to-end support all the way to a production-ready system — not just proof of concept. Ideal for new technology adoption, AI integration, and legacy modernization.

04
Track Record of 100+ Clients and 220+ Projects

100+ clients, 220+ projects. Over 75% of our work has been delivered to Japanese companies, many of which are mid-sized to large enterprises.

05
Japanese-Grade Quality & Security Standards

ISO 27001 and ISO 9001 certified. We maintain quality and security management on par with Japanese vendors, giving you full peace of mind when outsourcing.

06
Balancing Quality and Efficiency with AI

We leverage generative AI for spec documentation, automated test generation, QA optimization, and review workload reduction — achieving both faster delivery and sustained quality.

DELIVERY MODEL

Flexible Development Structure

Offshore

PM · BrSE (Japanese-speaking) + Vietnam development team

  • High cost efficiency
  • Leveraging global talent
  • Advanced technical capabilities
Hybrid

Japan-based resident PM/BrSE + collaboration with Vietnam office

  • Flexible management structure
  • Strengthened communication
  • Optimized time-zone coordination
Onsite

Resident team (PM · Engineers) / at client's office

  • Close collaboration
  • Immediate responsiveness
  • Deep understanding of Japanese business culture
CASE STUDIES

Implementation Examples

CASE 01 / RAG Development

Streamlining Internal Inquiry Response

  • Challenge: Internal manuals were scattered across systems, making it time-consuming to handle inquiries.
  • Approach: Built a RAG system referencing internal documents and developed an internal assistant that provides answers with cited evidence.
  • Result: (Generic example — specific figures are not provided as no actual client data is available) A use case designed to reduce the workload of handling internal inquiries.
CASE 02 / ChatGPT Integration

LLM Integration into Existing Systems

  • Challenge: Wanted to streamline document creation and summarization within existing business tools.
  • Approach: Integrated an LLM via API into the existing system, enabling generative AI to be used within the business workflow.
  • Result: (Generic example — specific figures are not provided as no actual client data is available) A use case designed to reduce the man-hours spent on document creation.
CASE 03 / AI Agent

Deployment of a Business-Specific Agent

  • Challenge: Routine tasks spanning multiple systems were taking considerable time and effort.
  • Approach: Designed an AI agent that calls multiple tools and built a semi-autonomous flow with human review checkpoints.
  • Result: (Generic example — specific figures are not provided as no actual client data is available) A use case designed to improve the processing efficiency of routine tasks.
PROCESS

How We Develop

1

Requirements Clarification

Align on improvement targets and evaluation metrics

2

PoC (Small-Scale Validation)

Verify technical feasibility and business impact

3

Production Design

Design data integration, permissions, and monitoring

4

Production Development & Integration

Implement and integrate with existing systems

5

Operations & Improvement

Continuously measure output quality and refine

FAQ

Frequently Asked Questions

Q1. What is the difference between AI agent development and generative AI development?
AI agents are characterized by their ability to autonomously execute multiple tasks, while generative AI is one of the underlying technologies that powers them. We handle both.
Q2. Can I request just a PoC?
Yes. We offer PoC contracts designed to validate technical feasibility and business impact on a small scale before committing to full development.
Q3. Can we proceed even if we have no in-house AI talent?
Yes. We provide end-to-end support from requirements clarification through to operations, so you can move forward without in-house specialists.
Q4. What is needed to build a RAG system?
The starting point is the internal documents and data you want the AI to reference, along with confirming your data handling policies. We work through this together during the requirements phase.
Q5. Is integration with existing systems possible?
Yes. We support embedding into existing business systems and chat tools via API integration.
Q6. What does your security setup look like?
We design data handling and access management under a management framework based on ISO 27001 and ISO 9001 international certifications.
Q7. Can quality be maintained with offshore development?
Yes. Through our quality management framework and Japanese-language communication structure, we optimize costs while maintaining quality.
Q8. How much does it cost?
Costs vary depending on requirements and scale, so we provide individual estimates after requirements clarification. (Generic example — fixed pricing is not offered.)
Q9. Can I choose the contract type?
Yes. We support contract-based, lab-based, and PoC contract models, which you can choose based on how well-defined your requirements are.
Q10. Which use case should we start with?
We work with you to select the first target process based on the balance between business impact and feasibility.
Q11. Can you support a transition to in-house development?
Yes. We can work with a knowledge transfer approach built into the process from the start.
Q12. What is the typical development timeline?
It varies by scope, but PoC can begin small-scale and then transition to production incrementally.
Q13. Can you handle operations and maintenance as well?
Yes. We provide end-to-end support including operational monitoring, keeping up with model updates, and continuous improvement.
Q14. Can I just come for a consultation?
Yes. We welcome consultations to help clarify whether to build in-house or outsource, and to organize your initial questions and priorities.

Unlock the Full Potential of Generative AI and AI Agents — From PoC to Production

Not sure where to start, which use cases to prioritize, or how to balance in-house development and outsourcing? We provide end-to-end support, from initial planning and PoC to full-scale deployment and operation.



    Feel free to reach out. We will propose the best approach tailored to your business challenges.