Private AI Construction Solution | On-Premises LLM・RAG

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last updated：Nov 11, 2026

アプライド

Utilize generative AI without disclosing confidential information outside the company! Build an integrated environment from GPU servers to in-house dedicated LLM and RAG.

Private AI is a solution that allows companies to build their own dedicated generative AI environment, utilizing AI while securely managing confidential information and internal data. It supports a wide range of applications, including in-house ChatGPT, technical document search AI (RAG), research and development support, and business automation through AI agents. It controls the transmission of data to external AI services and can perform AI inference and document searches in an on-premises environment. At Applied, we propose an enterprise AI infrastructure based on NVIDIA RTX PRO Blackwell-equipped GPU workstations and AI servers, combined with Dify, vLLM, and NVIDIA NIM. We assist in building the optimal environment tailored to the specific applications and scale of use, from hardware selection and LLM implementation to RAG construction, security settings, and integration with existing systems.

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basic information

【PoC・Small Scale】40,000 to 10,000,000 yen (excluding tax) DGX Spark series AI edge computer or workstation equipped with RTX PRO 6000 Blackwell. Supports AI chat and RAG verification for departments. 【Department Shared AI Server】10,000,000 to 20,000,000 yen (excluding tax) Two RTX PRO 6000 Blackwell Server Editions, 256 to 512GB memory, 8 to 16TB NVMe SSD, 10/25GbE. 【Company-wide AI Infrastructure】20,000,000 to over 40,000,000 yen (excluding tax) 4 to 8 of the same GPUs, 512GB to over 1TB memory, supports 25/100GbE. ■Supported Software: Dify, vLLM, Ollama, Open WebUI, NVIDIA NIM, Qdrant, etc. ■Environment: On-premises construction, supports RAG, authentication integration, and monitoring settings. *Prices are approximate and include hardware and construction costs. Specifications and costs will be provided in individual estimates.

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Applications/Examples of results

【Manufacturing and Design Development】 AI searches for confidential drawings, design specifications, quality control records, and past trouble information within the internal environment. Supports the sharing of technical information and the efficiency of design operations. 【Research and Development / Technical Department】 Utilized for searching technical literature, summarizing CAE analysis results, organizing experimental data, generating programs, and creating research reports. 【Information Systems / Management Department】 Streamlines internal AI chat, manual searches, inquiry responses, meeting minutes creation, and confirmation of internal regulations. 【AI Agents / Business Automation】 Utilizes tools like Dify to support data aggregation, report creation, and automation of business workflows linked with internal systems. 【Example of Implementation Configuration】 An on-premises RAG infrastructure equipped with RTX PRO 6000 Blackwell 96GB, assuming 30 employees with 5-10 simultaneous users. Estimated cost of 12 million yen (excluding tax) and an implementation period of 8-12 weeks.