A shared workspace across approved model choices
Keep the team’s working environment clear while separating model providers, hosting and optional integrations.
Editorial analysis and illustrative technical scenarios. They do not define the features or integrations included in a UTOMAI subscription. See Private AI On-prem pre-launch information.
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Workspace, model provider and infrastructure are different layers of an AI offer. People need a consistent place to work with approved knowledge and agents. IT needs to know where storage and inference run, which external services are involved and who operates each part.
Make the platform the common point
UTOMAI brings the company’s AI workspace, knowledge and configurable agents into one proposition. Dedicated Cloud and on-premise are deployment choices around that platform. An external provider is a possible component of a permitted model route, rather than the definition of the company’s whole AI environment.
Agree the route for each model
Open-weight models are the intended base. External frontier models can be requested from European or non-European providers, subject to the selected terms and data flows. The planned Italian Cloud hosting and optional European locations must be checked alongside the actual location of inference and backups.
Extend without confusing the core offer
Reading live files from an existing repository, updating CRM data or connecting an ERP requires its own integration scope. Existing business software can remain in place while the team starts with supported knowledge and models. A separate proposal can then define the extensions that matter.
A good architecture discussion ends with a short map of services, locations and responsibilities. It should explain the operating choices without asking business users to assemble an AI stack before they can use their workspace.
