scoville Launches 'Hokemaru,' an AI Sales Support System for Insurance Agencies that Automates Intent Tracking and Comparison Records

株式会社scoville (Headquarters: Ebisu, Shibuya-ku, Tokyo; CEO: Masahiro Idatani) announced the official launch of 'Hokemaru,' an AI-driven sales support system for insurance agencies, on May 20, 2026.

Hokemaru is a sales support system that uses AI to transcribe meeting audio, automatically create meeting records, intent tracking, and comparison recommendation records, and assist with full-scale compliance checks for insurance solicitation interviews. With its simple operation, agents can focus on interacting with their customers.

About Hokemaru Hokemaru is an AI system designed to support insurance agencies in documenting interviews, creating intent tracking and comparison recommendation records, and verifying compliance. Based on interview audio, the AI generates transcriptions and organizes customer intentions, background information, proposal details, and meeting summaries. These records can be used for reviewing previous meetings, policy maintenance, monitoring, agent training, and audit purposes.

Furthermore, by using the AI to perform a primary compliance check based on the entire audio data of all interviews, agencies can achieve the often time-consuming task of full-scale review without burden. The check criteria are designed based on the Insurance Business Act Article 300, business quality evaluation standards, and regulatory guidelines, which are crucial for insurance agency practices.

Key Features - Easy start of interview recording: Agents can record meeting audio via smartphones, tablets, or PCs, with support for online meeting tools and file uploads. - Automatic creation of intent tracking and comparison records: AI organizes customer intentions, background, and proposal content to automatically generate interview records. - AI-driven full compliance check and risk notification: The AI monitors all interviews based on the Insurance Business Act Article 300 and other relevant regulations. It alerts administrators to potential issues or inadequate explanations. - Utilizing records as customer information: Fact-based records facilitate trouble resolution, maintenance, and proposal preparation.

Case Study Results - Approx. 67% reduction in documentation time: Documentation time per interview reduced from 45 minutes to 15 minutes. - Significant improvement in quality and quantity of records: Average record length increased from approx. 750 characters to approx. 3,200 characters per record. - Realization of full compliance checks: Shifted to an AI-driven system checking approx. 550 interviews per month.

Future Developments The company will continue to focus on enhancing customer management features and functionalities to support comparative recommendation sales based on customer intentions and interview content.