Combining SLM and LLM to streamline legal document searches!
In the legal industry, document search requires accuracy and speed. Efficiently finding necessary information from a vast amount of legal documents greatly affects business efficiency. Decisions based on incorrect information can lead to significant risks. Our SLM/LLM emphasis system improves the search accuracy of legal documents and contributes to business efficiency. 【Use Cases】 - Case law search in law firms - Contract search in corporate legal departments - Investigation of litigation materials by lawyers 【Benefits of Implementation】 - Reduction in search time - Decrease in the risk of information leaks - Significant improvement in business efficiency
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basic information
【Features】 - Balances security and high performance - Optimization tailored to specific businesses and industries - Supports fine-tuning and RAG - Flexible system configuration - Ongoing 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 Studio. In 2018, we received a silver medal in the data analysis competition organized by the Japan Agency for Marine-Earth Science and Technology. In 2020, we won a bronze medal in the AI Edge Contest organized by the Ministry of Economy, Trade and Industry.
Price information
Pricing will be based on individual estimates. 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 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 Support It can be utilized as an internal assistant to quickly respond to questions from employees and personnel by referencing 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 for improving 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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