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Development of SLM/LLM Emphasis System

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LLFarM - SLM/LLM

last updated:Apr 16, 2026

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We will develop a smart and secure generative AI system by combining SLM and LLM!

**Features** 1) Balancing security and high performance Confidential information is handled on the Local LLM (SLM) side, while also leveraging the high inference performance of the Frontier LLM as needed. 2) Optimization tailored to business and industry It is easy to reflect specific domain knowledge such as internal documents, product information, and business flows, making it easier to meet unique demands that are difficult for general AI to address. 3) Support for fine-tuning and RAG Additional training or search integration of the Local LLM can be performed according to the application, improving response accuracy, consistency, and reproducibility. 4) Flexible system configuration It can be implemented in configurations that match the constraints and operational conditions of each company, including on-premises, cloud, and integration with existing business systems. 5) Support unique to contract development We provide consistent support from requirements organization to prototyping, implementation, evaluation, and improvement, finishing it in a form that can be used on-site.

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Development of SLM/LLM Emphasis System

LLFarM_SLM_LLM_ChatGPT Image 2026年3月12日 22_22_17.png
LLFarM_SLM_LLM_ChatGPT Image 2026年3月12日 22_22_17.png
  • Related Link - https://web-farmer.net/work/llmとslmを組み合わせてセキュアなシステ…
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【Specifications】 - A hybrid configuration that combines Local LLM (SLM) and Frontier LLM, balancing confidentiality and response performance. - Utilizes specific domain knowledge such as internal documents, business procedures, and product specifications on the Local LLM side, allowing for a design that minimizes external transmission. - Supports fine-tuning and additional training for the Local LLM as needed, optimizing for expressions and criteria specific to industries and businesses. - Accommodates contract development aimed at practical operations, including API integration, RAG, business system connections, and on-premises/cloud configurations. - Provides consistent support from requirements organization, prototyping, evaluation, implementation, to operational improvement. 【Our Strengths】 Since shifting to Deep Learning in 2013, we created our own deep learning framework in C language in 2014. We have been developing AI systems for major company N since 2017, and subsequently developed numerous AI systems in the manufacturing and healthcare sectors. 2016: Winner of the 1st Artificial Intelligence Hackathon at Media Workshop. 2018: Silver medal at the Ocean Research and Development Agency Data Analysis Competition. 2020: Bronze medal at the Ministry of Economy, Trade and Industry Data Analysis Competition AI Edge Contest.

Price information

Prices will be provided on an individual basis. PoC and small-scale verification: from several hundred thousand yen. Full development including business system integration: from one million yen to several million yen. Fine-tuning, RAG construction, external API connections, and security requirements will be added based on the content. We will propose the optimal configuration according to your requests, operational conditions, and implementation form.

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Applications/Examples of results

【Uses】 1) Internal Inquiry Support It can be utilized as an internal assistant to quickly respond to questions from employees and responsible parties by referring to internal regulations, business manuals, product specifications, etc. 2) Customer Support Assistance It can be used to create response proposals and provide explanations for sales and support personnel based on FAQs, proposal materials, and past cases. 3) AI Systems for Specific Industries In fields such as manufacturing, healthcare, construction, and finance, where there are many specialized terms and unique rules, it can provide high-precision support that reflects domain knowledge. 4) Highly Confidential Operations It enables the safe use of AI while handling internal information and customer data that is difficult to share externally on the Local LLM side. 5) Business Automation and Enhancement It can be utilized to improve the efficiency of daily operations and support decision-making through document summarization, classification, search, response generation, and knowledge utilization.

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Our company is engaged in various artificial intelligence-related businesses, including artificial intelligence development, artificial intelligence consulting, artificial intelligence seminars, and artificial intelligence application development. Since 2013, we have shifted to Deep Learning, working on improvements to CNNs and RNNs, and by 2015, we developed our own model using RNNs. Additionally, starting in 2016, we expanded our focus to deep reinforcement learning, developing numerous simulation models and robot models. Please feel free to contact us if you have any inquiries.

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