Herix Begins Proof-of-Concept Project to Support Sojitz in AI Utilization for M&A and Subsequent Subsidiary Management
Herix has partnered with major general trading company Sojitz to launch a proof-of-concept project focusing on AI utilization in M&A and subsequent subsidiary management. The initiative aims to enhance operational efficiency and leverage historical data through generative AI.
📋 Article Processing Timeline
- 📰 Published: May 13, 2026 at 19:00
- 🔍 Collected: May 13, 2026 at 10:31
- 🤖 AI Analyzed: May 13, 2026 at 10:50 (18 min after Collected)
Herix Co., Ltd. (Representative Director CEO: Jo Nakamura, Headquarters: Minato-ku, Tokyo, hereinafter Herix: https://herix.jp/) has commenced a proof-of-concept (PoC) project to support Sojitz Corporation (Representative Director President CEO: Koyu Uemura, hereinafter Sojitz), a major general trading company, in utilizing AI in the M&A domain and subsequent subsidiary management.
This initiative aims to build a mechanism that promotes operational efficiency through the utilization of both systems and AI, targeting M&A investment decisions, Post-Merger Integration (PMI), and subsequent subsidiary management, tailored to the business characteristics of a trading company. It also seeks to facilitate the utilization of historical case data accumulated over time.
◾️ Background of This Initiative
With the advancement of generative AI, it is becoming realistic to utilize past operational data, including unstructured data that was previously difficult to leverage, as new material for decision-making.
The M&A domain and subsequent subsidiary management are areas where data has been accumulated over many years for each case and subsidiary. By utilizing AI in these areas, there is potential not only to improve operational efficiency but also to expand the decision-making itself.
◾️ About This Initiative
This PoC project aims to examine and support the advancement of operations through AI utilization, targeting Sojitz's M&A investment decisions, PMI, and subsequent subsidiary management, tailored to the business characteristics of a trading company, until July 2026.
Specifically, we will examine and verify from the following two perspectives:
1. Operational efficiency through the utilization of both systems and AI: We aim to improve overall operational efficiency by combining the use of systems and AI in business processes related to M&A investment decisions, PMI, and subsequent subsidiary management.
2. Building a mechanism to promote the utilization of historical case data: We will work on creating a mechanism, including the use of AI, to leverage case data accumulated by Sojitz to enhance new investment decisions, PMI, and subsequent subsidiary management.
Herix will advance this PoC project by leveraging its expertise in the finance x AI domain.
◾️ Future Outlook
Based on the knowledge gained from this initiative, Herix will promote AI utilization in M&A investment decisions, PMI, and subsidiary management for major business corporations, including general trading companies. We will deeply engage with each company's unique business characteristics and decision-making processes, contributing as a partner to design and implement AI utilization together with on-site teams.
Companies interested in AI utilization in specialized and finance domains are encouraged to contact us via the link below.
https://herix.jp/#contact
This initiative aims to build a mechanism that promotes operational efficiency through the utilization of both systems and AI, targeting M&A investment decisions, Post-Merger Integration (PMI), and subsequent subsidiary management, tailored to the business characteristics of a trading company. It also seeks to facilitate the utilization of historical case data accumulated over time.
◾️ Background of This Initiative
With the advancement of generative AI, it is becoming realistic to utilize past operational data, including unstructured data that was previously difficult to leverage, as new material for decision-making.
The M&A domain and subsequent subsidiary management are areas where data has been accumulated over many years for each case and subsidiary. By utilizing AI in these areas, there is potential not only to improve operational efficiency but also to expand the decision-making itself.
◾️ About This Initiative
This PoC project aims to examine and support the advancement of operations through AI utilization, targeting Sojitz's M&A investment decisions, PMI, and subsequent subsidiary management, tailored to the business characteristics of a trading company, until July 2026.
Specifically, we will examine and verify from the following two perspectives:
1. Operational efficiency through the utilization of both systems and AI: We aim to improve overall operational efficiency by combining the use of systems and AI in business processes related to M&A investment decisions, PMI, and subsequent subsidiary management.
2. Building a mechanism to promote the utilization of historical case data: We will work on creating a mechanism, including the use of AI, to leverage case data accumulated by Sojitz to enhance new investment decisions, PMI, and subsequent subsidiary management.
Herix will advance this PoC project by leveraging its expertise in the finance x AI domain.
◾️ Future Outlook
Based on the knowledge gained from this initiative, Herix will promote AI utilization in M&A investment decisions, PMI, and subsidiary management for major business corporations, including general trading companies. We will deeply engage with each company's unique business characteristics and decision-making processes, contributing as a partner to design and implement AI utilization together with on-site teams.
Companies interested in AI utilization in specialized and finance domains are encouraged to contact us via the link below.
https://herix.jp/#contact