Private AI or Hosted AI for Your Business?
Start with the task and the information
Decide what the tool needs to do, which information it needs and who is responsible for reviewing the result. The deployment decision should follow those requirements rather than a general preference for local or cloud software.
Do not treat every hosted service as the same
A personal account, a business workspace and an API can have different controls and terms. For example, OpenAI states that business data from its business products and API is not used for model training by default. Check the actual product, settings and terms instead of assuming every hosted tool handles data identically.
Private deployment brings its own responsibilities
A local or privately hosted model can be considered when the business needs control over its environment. That still leaves decisions about document permissions, network access, updates, monitoring and the people maintaining it.
The useful comparison is the complete operating arrangement. A local model is not automatically a complete business application, and avoiding a hosted API does not mean the system has no running costs.
Connect the model to a defined workflow
The interface, source documents, allowed actions and review points determine how useful the tool is at work. A model producing a draft is a different requirement from a system allowed to update operational records.
Choose the smallest controlled solution
NexOps can build private AI where it serves a defined requirement, either as a workspace or within a business system. We agree the task and data boundaries first, then the model and deployment.
