We will streamline the recruitment process with SLM and LLM, supporting optimal talent acquisition!
In recruitment activities, the efficiency of document screening and interview evaluation is an important issue for the human resources department. Particularly, as the number and diversity of applicants increase, the time and effort required to identify suitable candidates are also growing. The SLM/LLM emphasis system supports recruitment operations with advanced information processing capabilities while maintaining confidentiality. 【Usage Scenarios】 - Automatic screening of application documents - Assistance with interview evaluations - Providing personalized information to candidates 【Benefits of Implementation】 - Reduction in selection time - Alleviation of the burden on recruiters - Decrease in the risk of hiring mismatches
Inquire About This Product
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. From 2017, we have been developing AI systems for major company N. Subsequently, 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 won 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 requirements will be added based on the specifics. We will propose the optimal configuration tailored to your requests, operational conditions, and implementation form.
Delivery Time
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 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 use of AI with safety considerations while handling internal information and customer data that are difficult to disclose externally on the Local LLM side. 5) Business Automation and Advancement It can be utilized to enhance the efficiency of daily operations and support decision-making through document summarization, classification, search, response generation, and knowledge utilization.
catalog（1）
Download All Catalogs
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.
![[For Financial Institutions] SLM/LLM Fraud Detection System](https://image.mono.ipros.com/public/product/image/2105530/IPROS8363969778099571600.png?w=280&h=280)
