AI Security & Compliance
Even if your AI runs on-premises, that doesn’t mean it’s secure. We harden your AI operation and make it verifiable: cybersecurity, ISO compatibility, data protection.
The server room in the basement is not a security concept
Local AI feels secure because nothing sits in the cloud. But it has the same attack surfaces as any other system in the building, plus a few of its own.
Forgotten admin accounts, open maintenance access, unvetted model updates, rigged documents that slip foreign instructions to the model: the firewall sees none of it.
We secure the AI operation on three levels: technically against attacks, organizationally with ISO-oriented evidence, and on data protection with clean technical implementation. Verifiable, not asserted.
The firewall doesn’t see the new attack paths
On-premises protects against exactly one risk: data flowing into someone else’s cloud. Everything else needs controls of its own.
Behind the firewall, therefore secure. That’s how it feels.
- Remote maintenance & admin accounts permission model + multi-factor login
- Model updates from the internet signed, vetted update paths
- Rigged documents & inputs input filters + guardrails
- AI in the middle of the company network network segmentation
- Unnoticed access to data complete audit logging
Every one of these paths exists on-premises too. Each one gets a control.
What we offer
Six building blocks on three levels: security, ISO, data protection
Access & permission model
Who may use the AI, what it may see, who may change it. With multi-factor login for administrators and regular review of stale accounts.
Hardening the AI environment
Network segmentation, closed maintenance access, minimal rights for every service. The AI runs isolated, not in the middle of the company network.
Protection against rigged inputs
Rigged documents can slip foreign instructions to a model. We filter inputs, limit the possible consequences and log anything suspicious.
Controlled update paths
Model and software updates enter signed and vetted, with rollback. No direct internet access from the AI environment.
ISO-oriented evidence
Risk analysis, logging, change management and documented controls that fit an ISO 27001-oriented security management. We make you audit-ready, we don’t certify.
Data protection in the technology
Data minimization, deletion concepts, logging of access to personal data. Technical implementation of GDPR requirements, not legal advice.
Project example
A local AI that stands up to a security audit
From feeling secure to verifiably secure
A machine builder ran a local document AI for design files and felt secure because nothing sat in the cloud. Preparing for a security audit showed a different picture: remote maintenance access worked without multi-factor login, model updates were installed unvetted, and access to the design data wasn’t logged. We separated the AI environment from the rest of the network, introduced a permission model with multi-factor login, moved updates to signed packages and logged every data access. Since then the evidence for the audit comes straight from the system.
AI environment separated from the rest of the company network
Updates only signed, vetted and reversible
Audit evidence provable straight from the system
Seven more building blocks to a production system
AI Readiness Assessment
Inventory, vulnerability analysis and roadmap to production. In 10 working days.
Learn morePrivate AI & On-Premises
Run AI inside your own building: local models, your own hardware, full data sovereignty.
Learn moreProduction Hardening
Make the existing pilot fit for operation: error handling, edge cases, human-in-the-loop.
Learn moreAgent Governance & Guardrails
Permissions, tool access, approval workflows and complete audit logs.
Learn moreAI Infrastructure & Deployment
Cloud, data pipelines, version control and deployment with rollback.
Learn moreEnterprise System Integration
Connect agents to ERP, CRM and legacy. With permission model and rollback.
Learn moreEvaluation & Managed Operations
Quality checks, monitoring, early warning of quality decay and incident response in day-to-day operation.
Learn moreHow secure is your local AI, really?
We review access, update paths and logging of your AI environment and tell you honestly where it burns.