Full AI capability deployed inside your environment — on-prem, air-gapped, or your own VPC — with zero data egress and complete sovereignty. When your data legally or contractually cannot reach a hosted API, we bring the model to the data instead.
For most enterprises, the question of where AI runs is a matter of preference. For a meaningful slice of them, it is a hard constraint. Classified programs, protected health information, material non-public financials, privileged legal matters, and contractually fenced customer data share one property: they cannot be sent to a third-party, hosted model API — not because of caution, but because regulation, classification, or contract forbids it outright.
The answer is to invert the usual flow. Instead of shipping your data out to where the model lives, you bring the model in to where the data already sits. We deploy the entire stack — weights, inference runtime, retrieval, and application — inside your network boundary, your air-gapped enclave, or your private cloud tenancy, so the data never crosses a line it is not allowed to cross. The capability is the same; the perimeter is yours.
Every layer runs where you control it — nothing depends on a connection to anyone else's cloud.
Some workloads cannot be served any other way. On-premise and air-gapped deployment is the only option when the data carries an obligation that outbound transit would violate:
Fixed scope, fixed price, twelve weeks from briefing to live deployment inside your perimeter.
Yes. We deploy the model weights, inference runtime, retrieval layer, and application into an enclave with no route to the public internet. Models are loaded from media or an internal registry, updates arrive through a controlled one-way transfer process, and nothing — no prompts, no documents, no telemetry — ever leaves the boundary. The system runs entirely on local compute.
It depends on the model size, concurrency, and latency target. Smaller quantized models run on a single workstation GPU; production deployments for many concurrent users typically need one or more multi-GPU servers. We size the GPU, memory, and storage to your workload before any purchase — see our GPU infrastructure page for the sizing detail — and can target hardware you already own.
Model and software updates flow inward, never outward. New open-weight model versions, security patches, and evaluation sets are staged in a controlled zone, scanned, and promoted into the enclave through a reviewed one-way process. Your data, prompts, and fine-tuning corpus stay inside the boundary the entire time, so the system improves without a single byte of your information leaving.
How private, air-gapped deployment maps to the realities of each regulated vertical we serve.
Tell us the constraint — the regulation, the classification, the contract clause — and the workload it blocks. In thirty minutes we will show how a fully private, zero-egress deployment runs that workload inside your boundary. Response inside 24 hours.
As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets: