Your recipes and supplier costs aren't for a chatbot vendor to keep.
Private LLM hosting on a dedicated machine in EU-Central, for restaurant groups and food service operators running menu writing, reservation and order support, or review response without sending recipe, cost, or customer data through a shared AI provider.
Not legal advice. This page describes GPUwerk's infrastructure and contractual commitments. It is not an opinion on your obligations for customer personal data or your rights over your own recipes and supplier terms. Check with your own legal or privacy team before deciding what can run where.
Where an LLM fits in a restaurant or food service business
Menus, recipes, and supplier costs are the kind of thing a competitor would love to see, and reservation and order data ties directly to identifiable guests. Both end up in the same prompt if the workflow isn't set up carefully.
Menu and description writing
Drafting menu copy, seasonal specials, or allergen notes from a recipe and ingredient list. The underlying recipe, portion cost, and supplier pricing behind that copy is exactly the kind of competitive detail a shared AI vendor's logs shouldn't ever hold.
Reservation and order support
Answering booking questions, summarizing a large party's requirements, or triaging delivery order issues. Names, phone numbers, and dietary or allergy notes tied to a reservation are personal data, and often sensitive personal data, the moment they're linked to a guest.
Review response
Drafting a reply to a public review, or summarizing review trends across locations for a franchise or group. Review text can name staff and describe specific visits, which is worth keeping off infrastructure a competitor's operator could theoretically also be using. See the private AI customer support guide →
Why a dedicated instance instead of a shared API
A multi-location group's recipe costing, supplier pricing, and guest data all pass through the same handful of AI-assisted workflows: menu writing, review response, reservation support. Sending that through a shared API means trusting a vendor's retention policy with recipe economics and guest personal data at the same time. A dedicated GPUwerk instance keeps the model, the source data, and the output on a machine assigned to your business alone, with no other operator's traffic anywhere near it and GPUwerk not accessing workload content except at your request for support or where a legal obligation requires it.
What's actually in the contract
For your operations lead or IT lead to review directly.
| Question | Answer |
|---|---|
| Where does it run? | EU-Central, on a dedicated single-tenant machine assigned to your business |
| Who operates it? | PRINT IT! SE, a Societas Europaea registered in Prague, Czech Republic. No US parent entity. |
| Who can reach the instance? | Through the instance itself, only holders of your SSH keys; password login is disabled fleet-wide. GPUwerk keeps infrastructure administrator access to the underlying machine, as on any hosted service, and under the DPA does not use it on your content except at your request for support or where a legal obligation requires it. |
| Does GPUwerk see recipe or guest data? | No. We host the hardware and, under the DPA, do not access, read, copy, index or analyse workload content. |
| Sub-processors for the workload? | None, listed at /legal/sub-processors |
| DPA (GDPR Art. 28)? | Published at /legal/dpa, no charge |
| Data on termination? | Container and workspace volume deleted from the node, then the node is sanitised before reassignment. Filesystem deletion, not a cryptographic erase; export what you need before terminating, since it isn't reversible. |
| Pricing | Spark-1x from $0.79/hour on demand, billed per minute; Spark-2x from $1.79/hour. A customer-requested stop holds the reservation at 75% of the running rate. See /pricing for full detail. |
Questions we get from restaurant and food service teams
Is our supplier pricing and recipe data safe to run through an LLM?
That depends on where the model runs and who can reach it, not the model itself. On a GPUwerk dedicated instance in EU-Central, the machine is assigned to your business alone and reachable only through your SSH keys; GPUwerk does not access, read, copy, index or analyse what runs on it except at your request for support or where a legal obligation requires it.
Does GPUwerk see our reservation or order data?
No. GPUwerk operates infrastructure, not models. Reservation, order, and customer data processed on your instance are handled by software you install, and under our data processing agreement GPUwerk does not access that content except at your request for support or where legally required.
Do you sign a DPA covering reservation and customer data?
Yes, a standard GDPR Article 28 DPA is published at /legal/dpa at no charge, and there are no sub-processors for instance workloads.
Does GPUwerk train on our data?
No. GPUwerk runs infrastructure, not models. There is nothing for GPUwerk to train on, since we do not access instance content except as described in the DPA.
Related reading
Private LLM hosting for hospitality · Private LLM hosting for franchise businesses · Private AI for customer support
Related pages
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