Is there a private ChatGPT for business?

"Private" gets used for three different setups. Each one answers a different question: who can read the prompts, who decides how long they are kept, and whose hardware runs the model. For a firm of 10 to 200 people, the right kind depends on which of those questions your clients, insurers, and regulators actually ask.

See the workflow for how to move your team's ChatGPT use to company AI.

What does "private" mean for an AI chatbot?

In practice it means three separate things. No training: the provider keeps your prompts and files out of the data it uses to improve its models. Retention control: someone at your company decides how long conversations are kept and can delete them. Containment: prompts are processed only by companies you have a contract with, or by no outside company at all. A business plan of a public chatbot gives you the first and part of the second. Self-hosting gives you all three, at a price.

How do the three kinds of private AI chat compare?

If staff already use ChatGPT, Claude, or Copilot, is the work version private?

Each of the big vendors makes the same core commitment for its business editions, and each draws the line at the work account. ChatGPT: OpenAI says data from its business plans and API is excluded from model training by default, and on its Business plan workspace admins control how long data is kept and can view, export, and delete members' conversations. Claude: Anthropic's commercial terms state that it "may not train models on Customer Content from Services." Copilot Chat: Microsoft says prompts from staff signed in with a work account on an eligible Microsoft 365 plan fall under its Data Protection Addendum and stay out of foundation model training. Web search queries sent to Bing follow separate terms.

The protections belong to the work account. A client file pasted into someone's personal account falls under personal-plan terms, and Microsoft states that staff signed in with a personal account get none of the enterprise protections. A business plan also leaves two things to you: what staff paste in, and which rules apply to client data. Is ChatGPT safe to use at work? covers what each ChatGPT and Claude plan does with your data.

What does a company-administered AI chat add?

Your company decides who gets in, which documents each team can use, how long conversations are kept, and which rules each prompt is checked against before it leaves. The prompts still reach a model provider, so the provider's API terms apply underneath: the major APIs exclude traffic from training by default and keep it for up to 30 days for abuse monitoring, with zero data retention available to customers the provider approves. Ask the app provider which model APIs it uses and under which of those terms.

To add checks on each prompt without a new chat app, Sentinel is an AI gateway that reads each prompt on its way to a supported AI tool and replaces the identifiers it recognizes before the prompt leaves the computer. Raw prompts and responses stay in the customer's environment.

What is a self-hosted or on-premise LLM, and what does it cost?

A self-hosted model is an open-weights model downloaded and run on hardware you control, in your office or in your own cloud account. Prompts never reach an outside AI company. Several AI companies publish open-weights models, including some built for a single high-memory GPU. For what "open" covers, see What is the difference between open weights and open source?.

The cost is mostly GPU memory. Hugging Face's rule of thumb is about 2 GB of GPU memory per billion parameters at standard 16-bit precision, so a 70-billion-parameter model needs about 140 GB just to load. Compressing the model to 8 or 4 bits cuts that, with some change in answer quality. Modelled: a four-GPU cloud server with 192 GB of GPU memory, run around the clock at on-demand rates, comes to about $7,660 a month by our arithmetic from a public cloud price list dated October 7, 2026. That figure leaves out storage, backups, and the staff time to patch, monitor, and upgrade the model. Smaller models need less memory and cost less to run.

For most firms of 10 to 200 people, that arithmetic settles it. Self-hosting earns its cost when a contract or regulator requires prompts to stay on infrastructure you control.

What should you ask any private AI chat provider?

Whichever kind you pick, the same six questions sort a real commitment from a marketing line. Ask for each answer in writing.

• Where are conversations stored? Ask which company, which cloud, and which country holds them, including any model provider behind the app.
• For how long? Ask for the default retention period, who can change it, and how soon a deleted conversation leaves backups.
• Who can read them? Ask whether your admins, the provider's staff, or contractors can open a conversation, and for what reasons.
• Do they train a model? Ask whether prompts, files, or feedback ever feed any model, and whether that is off by default or only on request.
• What does the admin control? Ask about sign-in, user roles, document access, retention settings, logs, and checks on prompts before they leave.
• What does the contract say? Ask for the commercial terms and data processing addendum that make each answer above binding.

Start from your client contracts: if one names where data may be processed, that requirement picks the kind for you. To follow a prompt from the keyboard to the model and back, read Where does your data go when people use AI?.