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Radineer / Services
AI Internal Search System (RAG Implementation)
RAG development is a service that builds AI systems connecting internal documents and knowledge bases with LLMs to generate accurate, information-grounded responses.
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Choose the scope you need.
Internal ChatGPT Development
Knowledge Base Development
Existing System Integration
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How we work.
- 1
Requirements Interview & Data Assessment
- We interview you about your business challenges, target data, and security requirements to design the optimal RAG architecture.
- 2
PoC & Prototype Development
- We build a prototype using real data and validate search accuracy and practical usability.
- 3
Production Environment Build & Tuning
- We set up the production environment and perform accuracy tuning, UI development, and existing system integration.
- 4
Launch & Continuous Improvement
- After launch, we provide ongoing support for accuracy monitoring, data updates, and feature improvements.
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The support you need, one piece at a time.
Scope
- Internal ChatGPT Development
- Knowledge Base Development
- Existing System Integration
- Security Compliance
- 01
Internal ChatGPT Development
- 02
Knowledge Base Development
- 03
Existing System Integration
- 04
Security Compliance
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What we actually do.
- 01
Build an AI chatbot trained on your internal documents. Anyone can access the information they need simply by asking questions in natural language.
- 02
Build a unified search platform integrating manuals, FAQs, meeting notes, and other internal documents. Eliminate information silos.
- 03
Seamlessly integrate with existing tools like SharePoint, Confluence, Notion, and Google Drive. Minimize deployment effort.
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See our own work.
See our work through the services and screens we've published.
Our public service
Our AI SaaS comparison service07 / 09
Pricing and terms.
PoC (Proof of Concept)
From ¥500,000
Small-scale data validation and accuracy assessment. Verify the impact of RAG implementation with real data.
Standard
From ¥2,000,000
Department-level production deployment. Build a RAG system focused on specific business domains.
Enterprise
From ¥5,000,000
Company-wide deployment with multiple data source integration. Build a large-scale internal knowledge platform.
Monthly Maintenance & Operations
From ¥100,000/month
Accuracy improvement, data updates, and monitoring. Ongoing support for post-deployment operations.
Compare plans side by side
Compare by cost and what is included. On a phone, scroll sideways.
| Item | PoC (Proof of Concept) | Standard | Enterprise | Monthly Maintenance & Operations |
|---|---|---|---|---|
| Price | From ¥500,000 | From ¥2,000,000 | From ¥5,000,000 | From ¥100,000/month |
| What is included & terms | Small-scale data validation and accuracy assessment. Verify the impact of RAG implementation with real data.
| Department-level production deployment. Build a RAG system focused on specific business domains.
| Company-wide deployment with multiple data source integration. Build a large-scale internal knowledge platform.
| Accuracy improvement, data updates, and monitoring. Ongoing support for post-deployment operations.
|
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Before you get in touch.
What can I consult you about?
You can consult us about: Internal ChatGPT Development, Knowledge Base Development, Existing System Integration, Security Compliance.
What are your pricing plans?
PoC (Proof of Concept): From ¥500,000. Standard: From ¥2,000,000. Enterprise: From ¥5,000,000. Monthly Maintenance & Operations: From ¥100,000/month.
How does the engagement work?
We proceed in this order: Requirements Interview & Data Assessment → PoC & Prototype Development → Production Environment Build & Tuning → Launch & Continuous Improvement.
Inquire about AI Internal Search System (RAG Implementation)
Tell us about your challenges and goals.
Inquire about AI Internal Search System (RAG Implementation)
Read details on services and pricing
What is included
Internal ChatGPT Development
Build an AI chatbot trained on your internal documents. Anyone can access the information they need simply by asking questions in natural language.
Knowledge Base Development
Build a unified search platform integrating manuals, FAQs, meeting notes, and other internal documents. Eliminate information silos.
Existing System Integration
Seamlessly integrate with existing tools like SharePoint, Confluence, Notion, and Google Drive. Minimize deployment effort.
Security Compliance
On-premises/VPC deployment options keep internal data in-house while enabling AI-powered search. Fully compliant with your security policies.
How we work, in detail
Requirements Interview & Data Assessment
We interview you about your business challenges, target data, and security requirements to design the optimal RAG architecture.
PoC & Prototype Development
We build a prototype using real data and validate search accuracy and practical usability.
Production Environment Build & Tuning
We set up the production environment and perform accuracy tuning, UI development, and existing system integration.
Launch & Continuous Improvement
After launch, we provide ongoing support for accuracy monitoring, data updates, and feature improvements.
Pricing & plan details
PoC (Proof of Concept): From ¥500,000
Small-scale data validation and accuracy assessment. Verify the impact of RAG implementation with real data.
- Small-scale Data Validation
- Accuracy Assessment Report
- Prototype Development
- Implementation Decision Support
Standard: From ¥2,000,000
Department-level production deployment. Build a RAG system focused on specific business domains.
- Department-level Deployment
- Production Environment Setup
- Data Integration Configuration
- User Training
- 3-Month Maintenance Included
Enterprise: From ¥5,000,000
Company-wide deployment with multiple data source integration. Build a large-scale internal knowledge platform.
- Company-wide Deployment
- Multiple Data Source Integration
- Advanced Security
- Custom UI Development
- Dedicated Support
Monthly Maintenance & Operations: From ¥100,000/month
Accuracy improvement, data updates, and monitoring. Ongoing support for post-deployment operations.
- Accuracy Monitoring
- Regular Data Updates
- System Monitoring
- Inquiry Support