Accelerate code generation in a secure environment by integrating SLM and LLM!
In the IT industry, there is always a demand for improved development efficiency. In particular, an environment that allows for rapid code generation while ensuring security becomes a source of competitive advantage. The SLM/LLM emphasis system enables efficient code generation by handling sensitive information with a Local LLM (SLM) to ensure safety, while also leveraging the high inference performance of frontier LLMs. 【Use Cases】 - Code generation in a secure environment - Code generation based on internal documents - Integration with existing systems 【Benefits of Implementation】 - Reduction in development time - Decrease in security risks - Reduction in development costs
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basic information
【Features】 1. Balancing security and high performance 2. Optimization tailored to specific businesses and industries 3. Support for fine-tuning and RAG 4. Flexible system configuration 5. Support unique to contract development 【Our Strengths】 Since shifting to Deep Learning in 2013, we developed our own deep learning framework in C language in 2014. We began developing AI systems for major company N in 2017. Since then, we have developed numerous AI systems in fields such as manufacturing and healthcare. In 2016, we won the first Artificial Intelligence Hackathon at Media Workshop. In 2018, we received a silver medal in the Ocean Research and Development Agency Data Analysis Competition. In 2020, we won a bronze medal in the Ministry of Economy, Trade and Industry Data Analysis Competition AI Edge Contest.
Price information
Prices will be provided on a case-by-case basis. PoC and small-scale verification: starting from several hundred thousand yen. Full development including business system integration: starting from one million yen to several million yen. Fine-tuning, RAG construction, external API connections, and security requirement compliance will incur additional charges depending on the content. We will propose the optimal configuration tailored to your requests, operational conditions, and implementation form.
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Applications/Examples of results
【Uses】 1) Internal Inquiry Response It can be utilized as an internal assistant to quickly answer 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 explanation support 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 enables high-precision support that reflects domain knowledge. 4) Highly Confidential Operations It allows for 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 for the efficiency of daily operations and decision support through document summarization, classification, search, response generation, and knowledge utilization.
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Company information
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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