#Japan #AI Technology #Tokyo #Richerka #Nittetsu Trading

Richerka's AI Trial with Nittetsu Trading

In a significant move towards enhancing operational efficiencies in the manufacturing sector, Richerka, a Tokyo-based startup led by CEO Shota Umeda, has launched a practical experiment focusing on integrating AI into quotation processes for Nittetsu Trading, another Tokyo firm. This initiative aims to address the challenges posed by the diverse and vast array of steel product catalogs, often presented in varying formats by different manufacturers.

Background of the Experiment

The steel industry is notorious for its extensive catalogs, where each country and manufacturer has its unique data presentation style. Within Nittetsu Trading's sales team, personnel have been tasked with searching for products from these catalogs in response to various quotation requests received in unconventional formats such as PDFs and emails. This archaic system heavily depends on the sales representatives' experience and intuition, leading to inefficiencies and potential errors in their operations.

For instance, representatives often find themselves reconciling vague specifications across different catalogs, leading to a cumbersome manual process that is outdated in today’s fast-paced market.

The Aim of the AI Trial

Richerka's objective with this experiment is to examine the feasibility of automating the gathering of catalog data, enabling quick and accurate matching of product information. The plan is to implement the AI technology on a limited basis initially, focusing on selected products over a two-month period to evaluate its effectiveness.

By leveraging Richerka’s RECERQA Scan technology, which relies on AI Optical Character Recognition (OCR), the project intends to analyze the structure of these catalogs. This will involve extracting vital data such as specifications, size, and weight, subsequently organizing and structuring the information correctly for efficient use.

Steps in the Proof of Concept (PoC)

The primary objective of this PoC involves several key steps:
1. Catalog Structure Analysis: Utilizing the AI-OCR technology to extract information from irregular catalogs, ensuring relevant data is organized correctly.
2. Database Design: A user-friendly database structure will be designed, focusing on searchability and convenience for the sales team’s practical usage.
3. Integration of AI in Quotation Processes: Ultimately, the aim is to develop a workflow where incoming quotations can automatically be read by the AI, allowing immediate extraction and matching of product information.

This PoC serves as the initial phase toward a company-wide implementation, with insights gained expected to inform comprehensive system design and implementation in subsequent phases.

Envisioned Outcomes

Through this collaboration, both Richerka and Nittetsu Trading aim to enhance the efficiency of product search and quotation creation processes, ultimately allowing sales personnel to devote more time to building customer relationships and delivering higher-value propositions. The broader mission is to elevate the quality of service through the use of AI, transforming sales activities in the steel industry.

Richerka is dedicated to the belief that if people can focus on more creative and enriching tasks, society as a whole can thrive. With its slogan, "Bringing creativity to everyone," Richerka aims to create environments conducive to innovation and efficiency in business processes.

For inquiries about their products and services, visit their contact page. For career opportunities, check their job listings.

About Richerka

Founded in April 2022, Richerka is driven by the mission of solving traditional business challenges through the implementation of AI. Their RECERQA series offers solutions primarily in supply chain management, addressing issues like master data management (MDM), workflow automation (AI-RPA), and digitizing analog information (AI-OCR). By harnessing technology, they aim to resolve operational obstacles faced by their clients effectively.