The context that makes AI valuable is too sensitive for the cloud.
Customer information, internal decisions and confidential project documents make AI valuable in daily work. External cloud services process this content on the provider’s infrastructure. Local AI keeps the processing inside your company.
With most AI tools, every question leaves the company. Local AI answers where your knowledge already is.
Three things are decided together with you before the start.
The operating environment is planned for your task: suitable hardware, model selection, maintenance and responsibilities.
Source storage and access rights are considered separately from running the model. Permissions decide which context may be used.
Answers and actions are different steps. Business services check rules and calculations; actions follow agreed approvals.
One operating foundation, three perspectives.
Your companySources, people and processes
CortexCompany brainLearn more
ImagoPersonal knowledge twinLearn more
ActaWorkflows with rules and approvalsLearn more
Local AIAI models on your infrastructureAnything else? Ask us directly, we answer every question personally.
The AI model runs on infrastructure under your control. Storage locations, knowledge sources, access rights and external connections are defined separately for each use case.
No. Running the model locally does not by itself define where sources are stored or which external interfaces exist. We look at these data paths separately and agree which connections are allowed and necessary for your use.
That depends on model provisioning, data sources, updates and connected services. Requirements for an isolated operation have to be planned and checked separately.
Model size, data volume, response times and concurrent use determine the requirements. Before deciding, we review your existing environment and the concrete use case.
We define a bounded task and success criteria. In the pilot we assess answer quality, source evidence, access rules, correction effort and operations.
