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Infrastructure - 5 min

What is local AI?

Local AI means AI runs inside your own environment, for example on a local device, server or network. It is about more control over data, availability, cost and dependency on external AI platforms.

5 sections Practical explanation For teams and organizations
01

In short

Local AI is AI that does not fully depend on an external cloud environment. Processing happens locally, on dedicated hardware or inside your own network. That keeps the AI foundation closer to the organization using it.

02

Why does this matter?

A lot of AI usage depends on external platforms with subscriptions, API costs and third-party rules. Local AI reduces that dependency. It is especially relevant when internal knowledge, privacy, continuity or predictable costs matter.

03

Is local AI the same as edge AI?

The terms overlap. Edge AI emphasizes processing close to the data source. Local AI emphasizes availability inside your own environment. In practice, the terms are often used together.

04

What can run locally?

Examples include answering internal questions, searching documents, using knowledge bases, summarizing information, running agents or supporting workflows. Not everything has to be local, but sensitive or availability-critical parts often benefit from it.

05

What should you consider?

Local AI requires good choices around hardware, models, access, updates and management. It is not a loose trick, but an infrastructure decision. The strongest setup combines local capability with clear rules about what may still connect externally.

Next step

See what fits your organization

If you want to know whether AITJE Assistent, AITJE Custom or a future product direction fits your organization, we can go through that with you directly.

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