Proposing safe and efficient routes with SLM and LLM, achieving cost reduction!
In the transportation industry, route optimization faces many challenges, including rising fuel costs, a shortage of drivers, and demands from customers for shorter delivery times. Selecting the optimal route is essential for cost reduction and improving customer satisfaction in response to these challenges. The SLM/LLM emphasis system contributes to solving these issues. 【Use Cases】 - Optimization of delivery routes - Proposal of detour routes in emergencies - Response to real-time traffic conditions 【Effects of Implementation】 - Reduction in fuel costs - Shortening of delivery times - Improvement in customer satisfaction
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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 created 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 based on 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 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, which have many specialized terms and unique rules, it can provide high-precision support that reflects domain knowledge. 4) Highly Confidential Operations It enables the use of AI with safety considerations while handling internal information and customer data that are difficult to share externally on the Local LLM side. 5) Business Automation and Enhancement It can be utilized for efficiency in daily operations and decision support through document summarization, classification, searching, 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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