Your data never leaves your organization

On-Premise AI and KVKK-compliant private LLM solutions

We deploy AI on your organization's own servers, fully offline (air-gapped) if required. Your data never leaves; control stays in-house.

What is on-premise AI?

On-premise AI means running the model on the organization's own servers rather than in the cloud. In this approach, data never leaves the organization's network; the model is hosted on in-house hardware and, if required, runs fully offline (air-gapped). With cloud-based AI, data is sent to an external provider; with an on-premise deployment, both the data and the model remain under the organization's control. This is the critical difference for public institutions, banks, healthcare and defence organizations that cannot move their data off-site for KVKK (Turkish Personal Data Protection Law) and public-sector information security reasons. C3T deploys a suitable domestic or open large language model (LLM) as a private LLM in this architecture and integrates it with existing systems, so the organization benefits from AI without compromising data sovereignty.

Why on-premise AI?

For organizations that cannot move their data off-site, on-premise deployment is not a preference; it is often a necessity.

Data sovereignty

Your data never leaves your network. Both the model and the data stay under your control.

KVKK + information security

Because data is never moved off-site, KVKK and public-sector information security compliance is built in from the start.

Independence

No external cloud subscription and no lock-in to a single provider; the architecture stays yours.

Cost predictability

A fixed, plannable in-house infrastructure cost instead of an ever-growing token/API bill.

How does C3T deploy on-premise AI?

C3T runs on-premise AI deployment end to end: free feasibility, an organization-specific pilot, on-premise installation and integration, then maintenance and training. The model is placed on the organization's servers, adapted to its own data (RAG or fine-tuning) and integrated with existing systems. The model can be a domestic option such as the state-backed Bilge or the open-source Kumru, or whichever open model best fits the organization. If required, the deployment is fully offline; access is role-based and every operation is written to an audit log. C3T does not develop models; it is the technical partner that securely deploys and maintains the model the organization chooses.

Security & data sovereignty

Security and compliance, built into the deployment

Not a promise, but assurance that comes from the architecture of the deployment. Data stays inside the organization, access is audited and the architecture is not locked to any vendor.

  • Offline (air-gapped) option
  • Data stays on your own servers
  • Role-based access + audit logging
  • KVKK compliance
  • Domestic/open model flexibility
  • Architecture with no vendor lock-in

On-premise AI use cases

Enterprise-scale examples that run without data ever leaving the organization.

Deployment process

A risk-free start: we begin with a small-scale pilot and go live inside your organization.

01

Free feasibility

Together we assess your data, systems and goals.

02

Organization-specific pilot

We prove the approach inside your organization with a limited-scope, measurable pilot.

03

On-premise deployment + integration

We install the model on your servers, adapt it to your data and connect it to your existing systems.

04

Support + training

Maintenance, handover and team training so your organization can run it on its own.

Data sovereignty and the national AI priority

With Türkiye's AI Action Plan (2026-2030), data sovereignty in public institutions, the use of domestic and open models and secure infrastructure are coming to the fore. Because on-premise deployment processes data without it ever leaving the organization, it aligns directly with these priorities. C3T supports organizations as a technical partner in using domestic or open models on their own infrastructure, in a KVKK-compliant way.

See our about page for our approach, and our tender consulting page for public-sector and tender processes. You can explore our other AI solutions on the Artificial Intelligence hub page.

Frequently asked questions

How does on-premise AI differ from cloud AI?

With an on-premise deployment, both the model and the data run on the organization's own servers and never leave them; with cloud AI, data is sent to an external provider.

Can it run fully offline (air-gapped)?

Yes; the model can be deployed to run on the organization's network without any external connection.

How does a secure in-house assistant work?

Users sign in with their corporate identity (LDAP/Microsoft); the assistant only accesses the data the user is authorised to see, and every operation is auditable.

Which model can we use?

A domestic, state-backed model (Bilge), an open-source domestic model (Kumru) or whichever open model best fits the organization.

Can we maintain it with our own team after deployment?

Yes; handover, training and maintenance are included, and there is no vendor lock-in.

Move to AI without moving your data off-site.

Let's plan the on-premise AI deployment that fits your organization together in a free feasibility call.