A private LLM for business that keeps your data in-house
You want the speed of AI, but client data cannot leave the company and the cloud API bill keeps growing. We design and deploy a private LLM for business: models that run on your own machine, in your own cloud, or in a hybrid setup where only general work goes to the cloud.
- Sensitive data stays on hardware you control
- A clear cost comparison: local vs. cloud, before you buy anything
- Built around your documents, your tools and your team
When the cloud is not the right home for your data
Most AI tools send every prompt and every document to a third-party server. For many businesses that is fine. For others it is a real problem.
Your team avoids AI on real work
Contracts, patient notes, financial records or client files are off-limits, so AI only gets used for trivial tasks.
The API bill grows every month
Usage-based pricing looked cheap in the pilot. At full volume, the monthly invoice is hard to predict and hard to justify.
You depend on someone else's rules
A provider changes its model, its terms or its prices, and your workflow changes with it, without your say.
Waiting means your competitors learn to work with AI while your team keeps doing by hand the work that touches your most valuable data.
On-premise AI solution, cloud or hybrid: we measure before we decide
A private LLM is a language model that runs on infrastructure you control, so your prompts and documents are not sent to an outside AI provider. We help you decide which tasks should run locally, which can use the cloud, and what each option costs.
Classify your data and workloads
We map which information is sensitive, which tasks use it, and how much AI you use today. That defines what must stay local.
Deploy and test local or hybrid
We install open models on your machine or private cloud, connect them to your documents, and test them on your real tasks.
Measure cost and performance
You see quality, speed and cost side by side for local and cloud, and you keep the setup that works best for each task.
What you get with our on-premise AI deployment
Data and workload assessment
A written map of what data can go to the cloud and what must stay in-house.
Local models on your hardware
Open language models running on a machine you own or a private server, without sending data to outside AI providers.
Hybrid architecture
Cloud for general tasks, local for sensitive ones, with clear rules about what goes where.
Local AI vs cloud cost comparison
Hardware, energy and maintenance against your current or projected API spend, in USD.
Maintenance or team training
We keep models updated, or we train your team to run them.
Is a private LLM for business right for you?
This is for you if
- Healthcare, legal, finance and other teams that handle sensitive client information
- Small businesses whose AI API spend is growing month after month
- Companies that want AI working on their internal documents
- Teams that want control over which model they use and when it changes
Probably not a fit if
- Occasional AI use with no sensitive data: a standard cloud tool is simpler
- Anyone looking for a certified compliance package off the shelf
We run local AI ourselves
Xentris content factory on a local GPU
We produce our own images and video with AI models running on an in-house RTX 5090 GPU. Each piece costs US$0 in AI API fees, and the files never leave our machine.
Xentris in-house caseWhy Xentris for local AI for small business
We decide with numbers
Local is not always better. We compare quality and cost on your tasks before recommending hardware.
Cloud, local or both
We work on the cloud you already use or on your own machine, and we design the hybrid rules in between.
Your team stays in control
Documentation and training are part of the work, so the system does not depend on us forever.
Private LLM questions, answered
Is a private LLM worth it for a small business?
It is worth it when you handle sensitive data or your AI usage is high and steady. If you use AI occasionally and without sensitive information, a cloud tool is usually enough. The free audit tells you which case you are in.
On-premise AI vs cloud: what changes in cost and privacy?
With on-premise AI your data stays on hardware you control, and you pay mostly upfront for equipment plus energy and maintenance. With cloud AI you pay per use and your data is processed by the provider. We put both options side by side with your real numbers.
What hardware do I need?
It depends on the size of the model and how many people use it. Some tasks run on a single workstation with a good GPU; others need a dedicated server. We size it after testing your tasks, not before.
Can a local AI use my company documents?
Yes. We connect the model to your documents so it can search and answer from them, and the documents stay on your infrastructure.
How much does a private LLM cost?
Every project is custom, so there is no fixed price. Cost depends on hardware, the number of users and the tasks. Part of the work is a written comparison of local versus cloud cost for your case.
Is local AI less capable than cloud AI?
For some tasks it is, and for many business tasks open models are good enough. That is why we test on your own work before you decide.
Find out if a private LLM fits your business
In 20 minutes we review which of your data is sensitive, what you spend on AI today, and whether local, cloud or hybrid makes sense for you. Free, with no obligation.
Book your free AI audit →