Konnect-linK Co., Ltd. Officially Launches LLM/AI Agent Construction Solution for Private and On-Premise Environments
Konnect-linK Co., Ltd. has officially launched an LLM/AI agent construction solution compatible with private and on-premise environments, targeting industries with high information security requirements such as finance, manufacturing, and healthcare. This enables the secure utilization of generative AI without exposing confidential data externally.
📋 Article Processing Timeline
- 📰 Published: April 1, 2026 at 19:00
- 🔍 Collected: April 1, 2026 at 10:15
- 🤖 AI Analyzed: April 21, 2026 at 11:18 (481h 2m after Collected)
Konnect-linK Co., Ltd. (Headquarters: Chiyoda-ku, Tokyo; Representative Director: Kento Komoda; hereinafter 'the Company') has officially launched its LLM (Large Language Model)/AI agent construction solution compatible with private and on-premise environments. This launch comes as the importance of addressing AI governance and security risks grows with the expanding use of generative AI in enterprises.
This solution systemizes and offers the knowledge and know-how regarding LLM/AI agent construction in private and on-premise environments, which the Company has been developing internally for over a year and providing to clients, including Prime Market listed companies. It builds an environment where generative AI can be utilized without exposing confidential data outside the internal network, providing end-to-end support from AI strategy formulation to infrastructure design/construction, business implementation, and operational improvement. This allows companies in industries such as finance, manufacturing, and healthcare, which require high information security standards, to confidently promote AI utilization.
## 1. Background: Manifesting Information Leakage Risks of Generative AI
While generative AI significantly contributes to improving corporate productivity, information leakage risks associated with its use have recently become a serious management issue.
### (1) "Shadow AI" Risk Caused by the Absence of AI Governance
In many companies, without clear rules or governance systems established for the business use of generative AI, employees and contractors often use cloud-based AI tools based on their individual judgment.
According to IBM's "Cost of a Data Breach Report 2025," data breaches caused by "shadow AI" used without corporate approval have been confirmed in 20% of the surveyed companies ※1.
### (2) Structural Risks Associated with Cloud-based AI Use
Cloud-based generative AI services entail various security risks that can arise when user-inputted data is transmitted to external servers.
This solution systemizes and offers the knowledge and know-how regarding LLM/AI agent construction in private and on-premise environments, which the Company has been developing internally for over a year and providing to clients, including Prime Market listed companies. It builds an environment where generative AI can be utilized without exposing confidential data outside the internal network, providing end-to-end support from AI strategy formulation to infrastructure design/construction, business implementation, and operational improvement. This allows companies in industries such as finance, manufacturing, and healthcare, which require high information security standards, to confidently promote AI utilization.
## 1. Background: Manifesting Information Leakage Risks of Generative AI
While generative AI significantly contributes to improving corporate productivity, information leakage risks associated with its use have recently become a serious management issue.
### (1) "Shadow AI" Risk Caused by the Absence of AI Governance
In many companies, without clear rules or governance systems established for the business use of generative AI, employees and contractors often use cloud-based AI tools based on their individual judgment.
According to IBM's "Cost of a Data Breach Report 2025," data breaches caused by "shadow AI" used without corporate approval have been confirmed in 20% of the surveyed companies ※1.
### (2) Structural Risks Associated with Cloud-based AI Use
Cloud-based generative AI services entail various security risks that can arise when user-inputted data is transmitted to external servers.