What is private AI deployment?
Deploying AI models and applications on servers or dedicated cloud environments the company controls, so data never passes through public services.
In detail
When using public AI services, data is sent to the provider's servers. Private deployment places the model (including open-source models run locally) in the company's own environment, with data storage and access controlled by the company, making it easier to meet compliance and confidentiality requirements.
For example
A company that handles a large number of customer contracts deploys an open-source model on its own servers to search and summarize contract clauses.
How companies use it
Worth considering when sensitive data is involved, the industry is strictly regulated, or large volumes of calls are needed over the long term. Assess the costs of hardware, operations and model updates.
Common misconceptions
Counting only software costs and ignoring hardware, power and operations staff. Private deployment is not necessarily cheaper than cloud services.
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