Clear scope
The task and outcome are defined before tool permissions.
Private AI infrastructure: more control over models, data and tools
Private AI does not automatically mean everything runs locally. The important question is which data, models and integrations belong in which trust zone.
Controlled access
Read, write and approval rights are separated.
Measurable operations
Logs and business KPIs belong to the workflow.
Deployment models
Local models, dedicated servers and cloud models can be combined according to the sensitivity of each workload.
Data paths
Prompts, documents and tool responses are separated by sensitivity and sent only to approved services.
Agent runtime
Agents need a controlled runtime for skills, tools, memory, logging and policies in addition to the model itself.
Operations
Monitoring, backups, updates and rollback are part of the infrastructure rather than afterthoughts.
Define the next step
Use the configurator or one of the free tools to define a controlled starting point for a pilot.
Start AI Configurator