When it makes sense
- Personal data under GDPR that you can't or don't want to send to a US cloud provider
- Financial, legal or contract data covered by confidentiality or regulation
- Source code and internal documents you'd rather not share with any vendor
- High, steady volumes where paying per request costs more than running your own hardware
If none of these apply, a hosted model is often cheaper and simpler, and we'll tell you so.
What we set up
- Model choice: open models matched to the task and tested on your data before you commit
- Hardware sizing: what to buy or rent, on your premises or in a European data centre you choose
- Access: a private API your applications call, behind your own authentication and network
- Integration with your existing systems, documents and databases
- Upkeep: monitoring, updates, and moving to better models as they're released
Our experience
We run our own AI on our own servers every day, including the agents that write code for our projects. We've also built software for regulated environments: a core-banking migration for a credit and deposit institution, and a fund-management platform we've maintained for six years. We know what it takes when data handling gets audited.
Questions
Are open models good enough?
For many tasks, yes: reading documents, extracting data, classifying, summarising and translating. For the hardest reasoning tasks the large hosted models still lead. We test both on your data, so the choice rests on results.
Do we need to buy GPUs?
Not necessarily. Smaller models run on modest hardware, and renting a dedicated server is often a good first step before buying anything.
Can it run without an internet connection?
Yes. A self-hosted model can run fully offline, inside your own network.
Who maintains it?
We can, or we hand it over to your team with documentation. Either way, you own the hardware, the models and the data.