homula List of Products and Services

We would like to introduce a case study where "generative AI" was implemented in the EC department of the travel and hotel industry. The company faced the challenge of low conversion rates on their travel booking site, with users dropping off during the process. By utilizing generative AI, they were able to suggest suitable travel plans for each customer based on past travel history and interest data. This led to an improvement in the conversion rate for travel bookings. 【Case Overview】 ■Challenges - Unable to accurately grasp customer preferences, resulting in generic travel plan suggestions. - Past customer data was not utilized, preventing offers for repeat customers. ■Results - The booking rate for repeat customers increased by 35%, enhancing customer loyalty. - Search time was reduced by 50%, achieving a smoother booking experience. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study of the implementation of "generative AI" at a major e-commerce company. The company faced the challenge of not utilizing existing customer purchase data, which prevented them from providing suitable offers for repeat customers. To address this, AI automatically generated personalized discount offers for repeat customers, which were delivered via email and push notifications. This led to a 20% increase in product purchase rates and expanded e-commerce sales. 【Case Overview】 ■Challenges - Low purchase rates on the online store and high cart abandonment rates - Poor usability in product search, making it difficult for customers to quickly find the products they want ■Results - Improved conversion rates by 15% through cart abandonment measures - Reduced the time customers spent finding desired products by 40% through search optimization *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented for knowledge organization in the manufacturing industry (production department). In the company, the trouble response manuals for the manufacturing process were dispersed, making it time-consuming to find the necessary information. To address this, an AI agent utilizing RAG was introduced, integrating the manuals and trouble case database within the factory. This led to a reduction in trouble response time. [Case Overview] ■ Challenges - The burden on veteran employees concentrated due to the lack of knowledge among younger engineers. - Past cases were not systematically managed, leading to a reliance on individual responses. ■ Results - Improved response capabilities of new engineers reduced the burden on veteran employees. - Shortened trouble response time and reduced production line downtime. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study on the implementation of "generative AI" in knowledge management at a major manufacturing company. The company faced the challenge of increased working hours due to inefficiencies in internal knowledge management. To address this, they implemented an agent-based RAG system, integrating the internal knowledge base (regulations, manuals, Q&A history, etc.). This enabled immediate responses to inquiries. 【Case Overview】 ■Challenges - Increased labor costs due to overlapping business processes - Increased burden of handling inquiries ■Results - Increased burden of handling inquiries - Streamlined information sharing and real-time updates of knowledge *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study where "HubSpot CMS" was implemented in the marketing of a school corporation. The corporation had been requesting development from vendors each time to expand their content, which posed a challenge due to high costs. By implementing our product, they were able to manage content with no-code solutions, resulting in a reduction in marketing costs. 【Case Overview】 ■Product Category: HubSpot ■Duration: 6 months ■Challenge: High costs due to reliance on vendors for development ■Solution: Implementation of "HubSpot CMS" ■Results: Reduction in marketing costs *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study where "generative AI" was implemented in the planning operations of a major company dealing with office-related products. The company faced the challenge of insufficient organization of a large amount of internal data, leading to decreased analysis efficiency. To address this, they implemented data documentation and semantic search. This significantly improved the transparency of data utilization and analysis efficiency. 【Case Overview】 ■Challenges - Insufficient organization of a large amount of internal data leading to decreased analysis efficiency - Lack of clarity on where data is located, hindering planning operations ■Results - Significant improvement in the transparency of data utilization and analysis efficiency *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study of a human resources platform company that implemented "HubSpot" in their sales operations. The company was using our product as a sales and contract management tool internally, but it was not being utilized effectively. Therefore, we dispatched a specialized consultant to conduct interviews regarding the existing usage and to redesign the system. This led to improved efficiency through the automation of sales operations. 【Case Overview】 ■Challenges - Unable to automate or design processes in-house, resulting in ineffective use of the tool. ■Results - Improved efficiency through the automation of sales operations. - Centralized data management due to the necessary data being stored in "HubSpot." *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in the sales of a company that provides data related to apparel. The company faced the challenge of inefficiency in searching and assigning sales data. As a solution, we developed an application that includes a database search function. The duration was three months. [Case Overview] ■ Product Category: Generative AI ■ Duration: 3 months ■ Challenge: Inefficiency in searching and assigning sales data ■ Solution: Developed an application with a database search function *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study of a SaaS company that implemented "generative AI" in their sales process. The company faced a challenge with a high dropout rate on their B2B inquiry form due to the cumbersome input of job titles and company size. To address this, they introduced an auto-completion feature for form inputs. When users entered their email address or company name, the AI automatically filled in the company information. This reduced the form dropout rate by 25% and expanded their opportunities for business negotiations. 【Case Overview】 ■Challenges - Slow response times after form submission led to a loss of customer interest. - Many of the inquiries received included leads with low purchasing intent. ■Results - Improved response speed immediately after inquiries, increasing the negotiation acquisition rate by 20%. - Enhanced lead scoring accuracy, boosting sales efficiency by 30%. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study where a major recruitment advertising company implemented "generative AI" in their sales operations. The company faced challenges in new customer acquisition due to inconsistent lead quality, making it difficult to identify priority prospects. To address this, they introduced lead scoring and segmentation using generative AI, which helped identify priority prospects. The target negotiation rate increased by 38%. 【Case Overview】 ■Challenges - Delayed follow-up on leads, resulting in a decrease in conversion rates - Insufficient lead information registered in the CRM ■Results - Reduced sales follow-up time by 45%, optimizing resources - Improved personalization accuracy through automatic lead data completion *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case study where a major general contractor implemented "generative AI." The company faced challenges due to insufficient utilization of past construction data, which hindered the application of know-how from similar projects. To address this, AI analyzed past construction data and proposed suitable construction methods for similar projects. By leveraging construction know-how, they achieved a cost reduction rate of over 10% for the project. 【Case Overview】 ■Challenges - The construction management tasks on-site were complicated, leading to time-consuming progress checks. - Safety management reporting was done manually, resulting in inefficiency. ■Results - Reduced the time for creating construction management reports by 80%. - Real-time safety management reduced the risk of accidents. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in the legal department of the new business division for human resources. In this department, checking contracts that vary by client took a lot of time and became a bottleneck in the contract signing process. To address this, we introduced an AI agent that utilizes the RAG model and integrates with a database of past contracts. This reduced the contract review time by 60%. 【Case Overview】 ■Challenges - There was a risk of overlooking important contract clauses, leading to unstable review accuracy. - Knowledge from similar contracts was not utilized, requiring a review from scratch each time. ■Results - The proof of concept (PoC) was completed in two months, and full-scale operation began in the third month. - The burden on the legal department was reduced, and sales speed improved. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in employee training at a major retail company. The company faced the challenge of inconsistent quality in customer service due to training manuals being managed separately for each store. To address this, they introduced a digital training system utilizing generative AI, creating an environment where knowledge related to store operations can be learned in a chat format. This enabled new employees to become immediately effective. 【Case Overview】 ■Challenges - Training manuals were managed separately for each store, leading to inconsistencies in customer service quality. - Updating and searching for manuals took a lot of time. ■Results - Staff training time was reduced by 50%, enabling new employees to become immediately effective. - Knowledge sharing related to store operations was made real-time, eliminating dependence on specific individuals. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in development support at a major electronic components manufacturer. The company faced the challenge that the accuracy of responses from standard RAG (Retrieval-Augmented Generation) was insufficient for specialized tools. In response, they built an advanced design support tool utilizing agent-based RAG. This enabled the learning of past design data and the performance prediction of new design proposals. 【Case Overview】 ■Challenges - Insufficient response accuracy of standard RAG for specialized tools - Need to integratively utilize electrical and mechanical characteristic data in design support ■Results - Early detection and prevention of design errors - Reduction in design time *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in development support at an electronic component manufacturer. The company faced a challenge where different design rules needed to be applied for each product during circuit design, resulting in time-consuming rule checks. To address this, they utilized an agent-based RAG to integrate circuit design rules, past design data, and defect cases. This allowed for the early detection of design errors and reduced correction costs. 【Case Overview】 ■Challenges - When design errors occur, the correction costs during the prototyping phase skyrocket. - The review burden on veterans increases. ■Results - Automation of rule checks reduced design man-hours by 30%. - Standardization of design knowledge accelerated the onboarding of new employees. *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We would like to introduce a case where "generative AI" was implemented in development support at an automotive parts manufacturer. In this company, past design data was not integrated in the design of automotive parts, making it difficult to reuse similar designs. By utilizing an agent-based RAG, we integrated design data, CAE simulation results, and part characteristic data. This shortened design time and improved product development speed. 【Case Overview】 ■Challenges - Adjusting CAE simulation parameters took a lot of time - Unable to predict the impact range of design changes in advance, leading to an increase in the number of prototypes ■Results - Reduced the number of prototypes by half, achieving cost reduction - Improved simulation accuracy through optimization of CAE analysis *For more details, please refer to the related links or feel free to contact us.

• Other information systems

We offer "LeedScope," which utilizes cutting-edge technologies, including generative AI, to solve inbound sales challenges. Generative AI automatically researches and scores lead information, instantly identifying priority customers. This enables optimal allocation of sales resources and efficient nurturing, significantly improving conversion rates. Through demos, you can experience the transformation of the sales process, including integration with CRM and personalized approaches. In addition to "LeedScope," we also provide customized applications of generative AI tailored to each company. On the day of the event, we will hold a free consultation session with dedicated consultants at our booth. Date: April 15 (Tue) - 17 (Thu), 2025 Location: Tokyo Big Sight Booth Number: 15-46

• SFA/Sales Support System

Homula Inc. is a company that supports business growth and digital transformation (DX) through AI, CRM/MA, and data. We provide tailored, one-stop support, as well as localized consulting, data analysis, development, infrastructure implementation, and marketing operations. We have established partnerships with various tech companies that support DX and growth, focusing on AI, data, and CRM. 【Business Overview】 ■ Comprehensive support for generative AI - Support for generative AI implementation and proof of concept (PoC) - RAG construction - LeedScope ■ Other contracted development - Data infrastructure construction and analysis, support for CRM/MA implementation *For more details, please download the PDF or feel free to contact us.

• Other information systems

"LeedScope" is an inbound sales automation tool that enables the immediate discovery and follow-up of high-priority customers, dramatically improving the conversion rate. AI collects information such as company name, revenue, location, and job title from the lead's name and email address, enriching lead information and significantly reducing the effort required for account research. It synchronizes with CRM tools like Hubspot and Salesforce, as well as chat applications, allowing sales representatives to focus on closing appropriate deals rather than conducting information research. [Solutions] - Automatic research of lead information - Identification of high-priority inbound leads - Real-time messaging to leads with appropriate content *For more details, please download the PDF or feel free to contact us.

• Other information systems