- Yes, it can be done: the AI, the search and your records can all run on servers in your own building.
- It suits companies whose contracts, regulators or policies rule out the cloud. For most others, a well-run cloud service is simpler and just as safe.
- It needs suitable hardware, time from your IT team, and testing, because AI models that run on site behave differently from the largest cloud models.
- Ask every vendor: does anything at all leave the building? Check each step, not only the answer.
For most companies, the question about AI is how to use it well. For some, there is an earlier question: can it run without our records ever leaving our building?
The reasons vary. A client contract that forbids storing their documents with outside providers. A regulator with strict rules on where data may sit. Records so sensitive that company policy keeps them on site. Or sites with limited internet access.
Two instincts that pull in different directions
of organisations see storing data locally as inherently safer
Cisco Data Privacy Benchmark, 2025 ↗also trust large global providers to protect their data better
Cisco Data Privacy Benchmark, 2025 ↗worry about sharing sensitive information by accident when using AI
Cisco Data Privacy Benchmark, 2025 ↗Cisco's 2025 study of 2,600 privacy and security professionals in 12 countries found both instincts at once. Most feel that data kept close is safer. Almost as many trust large cloud providers to protect it better than they could themselves. Both can be true. The right answer depends on what your records are, and what you have promised about them.
Cloud or on-premises AI?
- Nothing to install or look after
- The largest, most capable AI models
- Updates arrive without any work on your side
- Security run by specialists, around the clock
- Your records never leave your building
- Meets contracts and rules that forbid outside storage
- Works where internet access is limited
- You decide when anything changes
What running it on site really involves
Suitable hardware. AI models need servers with graphics processors (GPUs), sized for the number of people who will ask questions. This is the largest single cost, and it is yours rather than the provider's.
Models that run on site. The largest AI models are only available in the cloud. Models that run on your own servers are smaller. They work well, but they answer differently, so they need testing on your own documents before your team relies on them.
Sign-in inside your network. People still need to sign in with their work accounts, and permissions still need to be followed for every document. On site, that sign-in has to work within your own network too.
Time from your IT team. Someone has to provide the servers, keep them running, and agree with the provider how updates are delivered and tested.
Time to set up. Expect weeks to a few months from order, depending on the hardware and on your IT team, rather than the days a cloud service takes.
The one question to ask
When a vendor says their AI can run on your own servers, ask: does anything at all leave the building?
Four more questions worth asking:
- Does it follow our existing permissions for every document, exactly as the cloud version does?
- How are updates delivered, and can we test them before they reach our users?
- What hardware do we need for our number of users, and what happens as we grow?
- Who supports it, and how do they reach it if it runs inside our network?
In short
AI can run on your own servers, with nothing leaving your building. It suits companies whose contracts, regulators or policies rule out the cloud, and it needs suitable hardware, time from your IT team and careful testing. For everyone else, a well-run cloud service is usually the simpler choice. Either way, ask every vendor exactly where each step happens.