HACARUS at TECH BEAT Shizuoka 2023

HACARUS At TECH BEAT Shizuoka 2023

We will exhibit at “TECH BEAT Shizuoka 2023” held at Grandship (Suruga-ku, Shizuoka City) from July 19th (Wednesday) to 21st (Friday). We will introduce HACARUS’ latest small data centric offerings, which enable deployment of AI without the need for big data, targeting the medical, manufacturing, and construction industries.

“TECH BEAT Shizuoka 2023” will bring together over 100 startups with cutting-edge technologies to conduct business presentations and business matching with companies in Shizuoka Prefecture. The event will feature keynote speeches and panel discussions by renowned business leaders as well as academic and experienced professionals, including Professor Yutaka Matsuo (Graduate School of Engineering, The University of Tokyo), Professor Akie Iriyama (Graduate School of Business Management, Waseda University), Professor Seiko Shirasaka (Graduate School of System Design and Management, Keio University), and Professor Hiroaki Miyata (School of Medicine, Keio University).

Exhibition Overview

Event Name: TECH BEAT Shizuoka 2023

Date: July 19th (Wednesday) to 21st (Friday), 2023, 10:00-17:00

Venue: Grandship (2-3-1 Higashi-Shizuoka, Suruga-ku, Shizuoka City)

Organizer: TECH BEAT Shizuoka Executive Committee (Secretariat: Shizuoka Prefecture, Shizuoka Bank)

Target Industries: All industries

Participating Startups: 102 companies in 11 categories

Visitor Registration (Free): https://www.tenjikai-uketsuke.com/form/techbeat-shz2023/

Official Website: https://techbeat.jp/tech-beat-shizuoka-2023/

HACARUS Booth: J-6 (Medical and Healthcare)

We will showcase HACARUS’s AI instruments, which enable the construction of highly interpretable AI without the need for big data, targeting the medical, manufacturing, and construction industries. We will present various products through videos.

① Measuring Product Quality: “HACARUS Check for FANUC CRX Series” – Fully Automated Inspection

We will introduce a new product released on June 23rd, which utilizes two robots for inspection and transportation, offering a 360-degree fully automated inspection solution. A demonstration video will be presented.

② Measuring Worker Safety Awareness: “HACARUS Workplace Safety for KY” – Supporting Hazard Anticipation Activities

We will introduce an application that supports Hazard Anticipation (KY) activities, which are conducted before work begins, for the construction and manufacturing industries. By inputting work conditions and images of the construction site using a smartphone or tablet, our AI automatically extracts hazardous points and labor accident cases, supporting workers in their proactive safety activities. It helps prevent the stagnation, subjectivity, and monotony of daily KY activities, contributing to the reduction of labor accident risks.

③ Measuring Patient Health: “HACARUS MD” – Diagnostic Support AI Platform for Healthcare Professionals

We will introduce AI software such as “HACARUS MD for Colposcopy” that simplifies image storage, processing, and creation of findings records for colposcopy examinations using a colposcope (vaginal speculum). Please note that this product is not a medical device program based on the Pharmaceutical and Medical Device Act.

④ Measuring Drug Safety: “HACARUS DD” – AI Drug Discovery Support Platform

Combining the expertise of drug discovery researchers with AI, we streamline image analysis in the drug discovery process, contributing to the realization of a rapid drug discovery process.



HACARUS INC. provides big insights from small data and has since its founding in 2014, supplied solutions in 100+ AI projects across the Medical and Manufacturing fields. Headquartered in Kyoto, Japan, and backed by Osaka Gas and Miyako Capital (Kyoto University), among others, its technology enables humans to make better, faster, and more reliable decisions based on data-driven insights. HACARUS’ proprietary AI engine is built using Sparse Modeling, a method that understands data like a human would – by its unique key features and is far more resource, time, and energy-efficient when compared to Deep Learning. To learn more, visit https://hacarus.com


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