When every function buys its own API, the enterprise loses control of cost, data, and policy. We build a governed, self-hosted model platform — Llama, Mistral, Qwen behind a central gateway — that many functions share, with model routing and central control so each team gets the right model while the enterprise keeps one boundary, one cost view, and no per-vendor lock-in.
Left to itself, AI adoption fragments. Finance signs one API, support another, engineering a third, and each negotiates its own pricing, ships its own data outside the boundary, and applies its own — or no — policy. The enterprise ends up with redundant spend, scattered data exposure, and no consistent view of how AI is used or governed. A shared, self-hosted platform inverts that: one set of open models, inside your boundary, that every function draws on.
The platform centralizes what should be central and leaves teams what should be local. Data control, access policy, logging, and cost governance live in one place; each function still gets the model and scope its work requires. Because the models are open and self-hosted, you route across them to land the cheapest capable model per request, swap models underneath as better ones ship, and keep every request inside your network — turning AI from a sprawl of vendor contracts into infrastructure the enterprise owns and governs.
A shared open-model platform with routing, governance, and control engineered for many functions at once.
Value concentrates wherever many functions need models and the enterprise needs one place to control them:
Yes — that is the point of a shared platform. We deploy a set of open models behind a central gateway so finance, legal, support, engineering, and operations all draw on the same governed, self-hosted capacity. Each team gets the model and access scope its work requires, while the enterprise gets one place to manage data control, cost, and policy instead of a different API contract per department.
A routing layer sends each request to the cheapest capable model — a small fast model for simple tasks, a larger one for hard reasoning — with quotas, access control, logging, and policy enforced centrally. Because the models are self-hosted, that gateway also keeps every request inside your boundary, gives you one consolidated cost and usage view, and lets you swap models underneath without changing how any team integrates.
Bring the functions already using AI and the contracts behind them. In thirty minutes we will show how one governed, self-hosted platform with routing and central control consolidates that spend, keeps data in-boundary, and removes per-vendor lock-in — and how we would build it. 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: