For sensitive questions or documents, choose between a hosted chatbot with clearly stated privacy controls and local AI software that processes prompts on your device. Neither “temporary” nor “private” automatically means “never retained” or “inaccessible to people with authorized access.” Check what happens to your data after you send it, whether a human or organization administrator could access it, and whether any connected tools receive it.
What to check before sharing sensitive information
Privacy involves several separate controls. A chatbot might exclude a conversation from history or model training while still retaining it for safety purposes. Deleting a conversation may have a different timeline from the service’s handling of training data. And a consumer account may follow different rules from a workplace account.
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- Processing: Does the prompt go to a hosted service, or is the model actually running locally?
- Training: Can the conversation be used to improve models, and do settings or safety exceptions affect that?
- History and memory: Is the chat saved, and can it create or update a personalized memory?
- Retention: How long can the provider keep the content, including after deletion or in a temporary mode?
- Access: Could safety reviewers, workplace administrators, or compliance systems access it?
- Other recipients: Are plugins, connected apps, tools, or cloud models involved?
For confidential work, regulated records, or other high-consequence material, follow your employer’s or client’s rules first. Redact names, account numbers, and other identifiers when they are not necessary to the question. A chatbot’s privacy controls do not, by themselves, make every disclosure appropriate.
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How the main options differ
| Option | What the provider says about sensitive chats | Important qualification |
|---|---|---|
| ChatGPT Temporary Chat | OpenAI says temporary chats are excluded from history, do not create or update memories, and are not used to improve its models while temporary. | OpenAI may retain a copy for up to 30 days for safety. Personalization settings may use existing memories, custom instructions, and plugins; workspace and account restrictions also apply. Saving a chat converts it to a regular chat. (OpenAI Help Center, 2026.) |
| Claude Incognito | Anthropic says Incognito chats are not saved to chat history or Claude memory and are not used for model training. | Retention is 30 days by default, or longer with an Enterprise custom retention setting. Team and Enterprise chats can appear in organizational exports; Enterprise Compliance API access is also described. (Anthropic Support, 2026.) |
| Proton Lumo | Proton says it keeps no logs of questions or replies, uses zero-access encryption for saved conversations, and does not train on user data. | These are Proton’s descriptions of its service, not independent audit findings. Proton says Lumo is open source; that alone does not establish that every deployment or operational control has been independently audited. (Proton, Lumo privacy page.) |
| Ollama with a local model | Ollama says it does not collect, store, transmit, or access prompts and responses processed locally. | That statement applies when processing is local. Ollama distinguishes cloud-hosted models, which process content transiently to provide the service, and says it may collect limited device and usage metadata. Verify the selected model and any connected tools. (Ollama Privacy Policy.) |
Hosted chatbots: useful controls, with retention caveats
ChatGPT Temporary Chat
Temporary Chat reduces persistence and training use; it is not a promise of zero retention or anonymity. OpenAI says it may keep a copy for up to 30 days for safety. If personalization is enabled, existing memories, custom instructions, and plugins may still affect the experience. Saving the conversation makes it a regular chat.
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OpenAI’s consumer data guidance says content may be used to improve model performance depending on settings. It says content from ChatGPT Business, Enterprise, Edu, Healthcare workspaces, and the API Platform is not used for that purpose by default. These are different account contexts, so check the controls that apply to your own account or workspace. OpenAI’s Help Center cautions: “Please do not enter sensitive information that you would not want reviewed or used.”
Claude Incognito
Anthropic describes Incognito chats as temporary conversations that are not saved to chat history or Claude memory. It says they are not used for model training, but are retained for 30 days by default; an Enterprise custom retention setting can extend that period. For Team and Enterprise accounts, organizational exports and, for Enterprise, Compliance API access are relevant access considerations.
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Anthropic says consumer conversations can be used for model improvement if a user opts in, if a conversation is flagged for safety review, or through another explicit opt-in. Its separate statement that Incognito chats are not used for improvement should not be confused with a claim that no one can review content for safety. Anthropic’s guidance on sensitive data recommends caution with Social Security numbers, payment-card and bank details, health records, passwords, and confidential business or personal documents.
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For ordinary deleted Claude chats, Anthropic says they disappear from history immediately and are deleted from backend storage within 30 days. If a user allows model improvement, Anthropic says data may be retained in de-identified form in training pipelines for up to five years; policy-violation flags and feedback have separate retention periods. These deletion and training-pipeline statements concern different data-handling stages.
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Local AI: the strongest way to keep prompts on your device
With local inference, the model runs on your computer rather than sending each prompt to a hosted model. Ollama says locally processed prompts, responses, and model interactions are not collected, stored, transmitted, or accessible to Ollama. The important condition is that the model is actually running locally: Ollama distinguishes cloud models, which process content transiently to deliver the service. Avoid cloud routing and connected tools when handling sensitive material, and check the mode before entering a prompt.
Local processing shifts practical responsibility to your device and setup. Consider who can access the computer, whether its storage is protected, and whether the model or an integration is using a remote service. Ollama also says it may collect limited device and usage metadata; its claim about local prompts does not mean the software collects no information of any kind.
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Hardware depends on the model
Ollama’s model guidance illustrates why there is no universal “AI-ready” memory threshold. It says its quantized gpt-oss-20b can run on supported systems with as little as 16 GB of memory. Its Llama 3.2 Vision guidance specifies at least 8 GB of VRAM for the 11B variant and 64 GB of VRAM for the 90B variant. Those are model-specific requirements, not a guarantee that any computer with 16 GB will run every model well.
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Choose an option for your risk and workflow
- For low-sensitivity questions where convenience matters: A hosted chatbot’s temporary mode may reduce history and training use. Read its retention and access terms, and avoid including identifiers you do not need to share.
- For a hosted service with explicit privacy claims: Proton Lumo may suit readers who value Proton’s stated no-logs, zero-access encryption, and no-training approach. Treat those as provider claims, not proof of independent verification.
- For material that should stay on your own machine: Use local inference, confirm that the selected model is local rather than cloud-hosted, and avoid integrations that send content elsewhere. Make sure your hardware supports the model you intend to run.
- For workplace, client, regulated, or highly confidential documents: Use only a service approved under the applicable organization’s policies. Consumer privacy modes do not override administrator access, compliance requirements, or contractual rules.
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