Recerqa Secures ¥1.7 Billion in Series A Funding Led by Angel Bridge

Recerqa has successfully raised ¥1.7 billion in a Series A funding round, with Angel Bridge as the lead investor. The company is known for its innovative use of AI to streamline order processing tasks, transforming routine operations into more efficient processes. This funding round includes contributions from Genesia Ventures, New Commerce Ventures, Mizuho Bank, Shoko Chukin Bank, Sumitomo Mitsui Banking Corporation, Resona Bank, Joyo Bank, and Hokuriku Bank.

Revolutionizing Order Processing

Recerqa's platform leverages AI to automate and optimize various order processing tasks, such as estimation, ordering, inspection, and invoicing. The service aims to improve efficiency by allowing human workers to focus on more creative and value-generating tasks. The company's proprietary architecture, known as "Quattro," supports these processes through a four-layer system: data normalization, business logic management, decision-making, and execution.

Strategic Use of Funds

The newly acquired funds will be directed towards several key areas:

  • Product Development: Enhancing the RECERQA platform's capabilities, particularly the Quattro architecture, to better serve manufacturing and trading sectors.
  • Organizational Expansion: Hiring more AI engineers, field data engineers (FDEs), product engineers, and consultants to support growth.
  • Business Expansion: Focusing on increasing market presence among major manufacturing companies and trading firms.

Expanding Industry Impact

Recerqa's AI-driven solutions have already been adopted by major players in the manufacturing, trading, and insurance sectors, including companies like Kao, Nippon Steel Trading, and Ajinomoto AGF. With the new funding, the company plans to expand its reach and enhance the functionality of its industry-specific templates, further establishing its presence in these key sectors.

Recerqa, founded in 2022, continues to push the boundaries of AI application in business operations, aiming for a full-scale deployment that prioritizes efficiency and innovation.