Fully local
Models and data on the same machine or server. Processing works with the network unplugged.
- The data stays inside your infrastructure
- Open, self-hosted models, keys kept in-house
- The limit is the GPU you have available
On-premise AI
AI that works where your data already is.
Models that run on your machine or on your server. The documents stay where they already are, and the person deciding stays the person who decided before.
Or write to us: info@ggtechnologies.sm
1997
the first project
18
years in manufacturing
900
workers in the study
Where we start
The data you would need AI on is the data that cannot leave.
Many companies stop short of AI for one reason: the data they would need to use it on is exactly the data that cannot leave. Medical records, contracts, designs, customer and supplier data.
The fix is less exotic than it sounds: the model runs inside your own infrastructure and the documents never leave it. It is the principle Podz.AI is built on, and the same one we apply in tailored projects.
Based in
Via Marino Moretti 23, 47899 Serravalle, Republic of San Marino.
Development
Software designed and developed entirely in Europe.
Product
Podz.AI, the personal AI workstation, built on the DigiSense® framework.
How it works in practice
Three configurations, depending on where the data must stay and how much power is needed.
Hybrid with anonymisation
The processing stays on-premise. When cloud power is needed, personal data is masked before it is sent and restored in the answer.
- Masking of names, dates and addresses
- Masked fields are replaced before the request leaves your machine
- What may leave is decided case by case
Integration with systems in use
AI reads documents and business systems where they already are, and there they stay.
- Controlled access to archives
- The data stays in your own archives
- Traceability of who asked for what
How we work
The choice between local, hybrid and cloud starts from the data, not from the technology.
01
Classify the data
Which data is involved, who may see it, and which task has to be done.
02
Draw the boundary
Where the model runs, what it sees and what it must never see. This is where the architecture is decided.
03
Install on-premise
Installation inside your own infrastructure, integration and testing with the people who will use it.
04
Maintain
Maintenance, model updates and evolution over time.
FAQ
Frequently asked questions
What machine does it take to run AI on-premise?
It depends on model size and load, and in practice on how much GPU memory you have. For one person, a Mac with Apple Silicon or a PC with a dedicated GPU. For continuous business use, a server with a GPU. Exact sizing we do together, before any quote. It is a trade we practised before AI needed it: in the late nineties our chief executive was assembling workstations with the graphics cards chosen to run CAD, and the constraint was the same one.
Is local AI less capable than cloud AI?
On generic tasks, frontier cloud models remain more powerful. On a defined task — reading one type of document, extracting certain fields — the gap narrows considerably, and the confidentiality advantage weighs more.
Can I start on-premise and open up to the cloud later?
Yes, that is the most common setup. You start fully in-house and open to the cloud only for the steps that need it, with personal data masked before sending.
Is anonymisation enough for compliance?
On its own, no, and the distinction is a technical one: for GDPR purposes the compliance assessment belongs to the data controller — whoever decides why and how that data is used. What you need in order to make it, we document: which fields are masked, what actually leaves, and how you verify it.
Where does my data get processed, if you are in San Marino?
On your own servers. In an on-premise architecture the model runs inside your own infrastructure: the place of processing is yours, and our home country bears on the contract rather than on the path the data takes. That is the difference from a cloud service, where that path runs through the supplier by design. Where a service of ours processes data on your behalf, the applicable law and the place of processing sit in the contract, before anything starts.