On-premise AI
On-premise AI runs on a company’s own hardware instead of someone else’s cloud. Data and model stay in-house.
On-premise AI refers to artificial intelligence operated entirely on a company’s own infrastructure — on its own servers or GPU machines in its own data centre — rather than in an external provider’s cloud. Both the data and the model never leave the building.
The key advantage is sovereignty: no data leakage to third parties, no dependence on a cloud provider’s availability or pricing, and no legal grey zone when transferring personal data. For regulated industries — finance, healthcare, public administration — it is often the only viable option.
MangoSeed builds AI solutions so they run either on-premise on your hardware or in an EU cloud (Frankfurt). One GPU machine, one browser client per tool, licence-based activation — the models run locally, the data stays under your control.
Frequently asked
What is the difference between on-premise AI and cloud AI?
With on-premise AI, model and data run on the company’s own hardware; with cloud AI, data is sent to an external provider’s servers. On-premise offers maximum data sovereignty and independence.
Is on-premise AI GDPR-compliant?
On-premise AI greatly eases GDPR compliance because personal data never leaves the company and no third-country transfer takes place.