Trust in AI deep dive:Sovereign

The importance of data and AI sovereignty is greater than ever. Sovereignty—where data is properly managed and AI systems operate autonomously without undue external influence—is essential in modern business management.
“Multi-AI Agent Technology,” in which AI systems collaborate like a team to carry out tasks
Technology introduction
Multi-AI agent technology enables multiple AI agents to work together as a team while continuously and safely learning from execution results, human feedback, policy updates, and specification changes. The agents identify why actions succeed or fail, extract knowledge and best practices, and apply validated learnings to future tasks.
Why it matters
This technology reduces the need for ongoing expert-led tuning by enabling AI to continuously evolve within business operations. Organizations can build and improve AI tailored to their business needs without heavy dependence on specialized AI expertise.
Example use case
Making vast information easier to discover
In business systems such as electronic medical records, identifying the impact of regulatory or policy changes often depends on experienced specialists who know where to look across large volumes of documentation. By applying Multi-AI Agent Technology, AI agents learn from previous search results and human feedback to identify not only directly related documents but also relevant supporting information. This reduces manual effort while enabling more comprehensive and reliable impact analysis.
“AI Security Technology” for the safe and continuous use of AI
Technology introduction
Multiple AI systems can collaborate across attack, defense, and validation functions to identify vulnerabilities, analyze potential attack patterns, assess countermeasure effectiveness, and address emerging threats such as prompt injection attacks. Data and AI Space Collaboration Technology enables organizations to securely collaborate across company and industry boundaries while preserving data sovereignty. By combining data spaces—which allow data to remain under the control of its owner—with distributed AI execution, organizations can analyze and utilize data across multiple enterprises without moving the data itself.
