The Challenge
With growing interest in AI for data analysis, reporting, and knowledge management, the organisation sought to deploy local Large Language Models. Concerns about data leakage, cloud dependency, and compliance with ISO 27001 and NIS2 created uncertainty.
The Approach
We designed and implemented a secure AI deployment framework:
- Local AI Infrastructure: LLM deployment on secure on-premises server
- Access Controls: Role-based access and network segmentation
- Policy Framework: AI usage policies for confidentiality and acceptable use
- Monitoring & Logging: Activity integration into monitoring environment
- Testing & Validation: Pilot projects with anonymised data
The Solution
Secure, local AI environment implemented, giving the organisation AI-powered knowledge management benefits while avoiding third-party cloud service risks.
Architecture
Infrastructure Layer
Dedicated on-premises server with high storage and compute
Access Control Layer
Role-based access with network segmentation and MFA
Policy Layer
Usage guidelines integrated into ISMS
Monitoring Layer
Central logging of AI interactions
Testing Layer
Controlled pilots with anonymised datasets
Results
- Enabled AI-driven efficiency without external data exposure
- Compliance with ISO 27001 and NIS2 for confidentiality and governance
- Improved speed and quality of internal reporting
- Staff felt confident knowing data remained within the infrastructure
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