The Tool Desk
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Does local AI send your chats online?
It depends on the app and the services enabled for the conversation. A locally running model can process prompts on your device, while a chat interface may also connect to cloud models, web search, remote document extraction, cloud embeddings, or other external tools.
Open WebUI says the selected endpoint determines where inference happens: when you choose a cloud model, your prompt and included context go to that provider under its terms. A local model selection does not, by itself, make separately configured cloud tools or processing services local. See Open WebUI’s provider-endpoint documentation.
Check the model and endpoint for each sensitive chat, then inspect whether auxiliary services are enabled. If the endpoint or data path is unclear, do not assume the content stays on your device.
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Where are local AI chats and files stored?
“Local” describes a processing arrangement, not a guarantee that data is inaccessible. Chat histories, uploaded documents, indexes, databases, logs, and backups may be stored on the computer or on a self-hosted server. People with access to the device, application administration, database, host, or backup system may be able to access that data.
Open WebUI describes self-hosted deployments as controlled by the organization operating the server, database, storage, model connections, logs, backups, and network placement. That makes the operator and the machine part of the privacy boundary, even when inference uses a local model. Its chat data privacy and encryption guidance recommends encrypted storage and backups. For its SQLite setup, it recommends placing the data directory on an encrypted filesystem such as FileVault, BitLocker, or LUKS; it says SQLCipher is unsupported since v0.9.0. Do not assume app-level database encryption is enabled by default.
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Encrypt backup copies separately and test that you can restore them. An encrypted external drive can protect a backup when it is disconnected, but it does not secure active files while mounted or prevent a cloud endpoint from receiving prompts.
How to reduce access and retention
Use the controls your particular interface provides to limit how long chats remain available and who can view, export, or share them. Open WebUI documents temporary chats, controls for administrator chat access and exports, group-scoped file and knowledge permissions, and metadata-level audit logging. These are product-level controls, not a barrier against a trusted host or operator accessing underlying infrastructure.
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- Use temporary chat where available for conversations you do not want retained in ordinary history.
- Review administrator access, chat export, sharing, and upload settings.
- Limit file and knowledge access to the groups that need it.
- Keep audit logs metadata-only unless storing chat contents is explicitly approved.
- Protect the device with a strong login and supported full-disk encryption; encrypt backup copies as well.
Why tools and extensions change the privacy picture
Treat plugins, tools, and agent features as code with permissions, not as harmless additions to a local chat. Open WebUI’s security hardening guide says server-side Tools and Functions can read files, make network requests, access environment variables, and interact with the database under the application process’s permissions.
Only enable tools you trust, and restrict who can create or import them. For a self-hosted service reachable over a network, follow its current hardening guidance, use access controls and TLS as appropriate, restrict allowed origins, and do not expose an unauthenticated service to the internet. Open WebUI documents a wildcard CORS default and advises restricting origins.
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What LM Studio and Ollama say about privacy
Vendor policies can help explain how a product says it handles data, but they are not independent audits and do not establish how every configuration behaves. Read the policy for the specific feature you use, rather than treating a product-wide label such as “local” as a blanket promise.
| Product | Vendor statement about local use | Separate network activity or qualification |
|---|---|---|
| LM Studio | LM Studio says prompts sent to local models, chat histories, and documents stay on the device. | Model downloads, update checks, and cloud features involve separate network activity. See LM Studio’s privacy documentation. |
| Ollama | Ollama says it does not collect or transmit local prompts and responses. | Its policy says it may collect limited non-content device and usage metadata, and that prompts to cloud-hosted models are handled transiently. See Ollama’s privacy policy. |
These statements apply to the vendors’ described services and features; they do not settle what a separate chat interface, extension, operating system, or configured endpoint does. Recheck policies after significant product updates because features and defaults can change.
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A practical privacy check before using sensitive content
- Identify every component. Note the chat interface, runtime, model, file-indexing component, and any connected services; each may have different storage and network behavior.
- Confirm the endpoint. Check the model selected for the current chat and inspect configured endpoints. If a cloud model is selected, assume prompts and included context are sent to that provider under its terms.
- Inspect auxiliary features. Look for web search, remote extraction, cloud embeddings, external tools, and agent features that may handle content outside the local model.
- Secure storage and backups. Use supported full-disk encryption for active data and encrypt backups separately. For Open WebUI’s SQLite setup, follow its guidance on encrypted filesystem storage rather than assuming database-level encryption.
- Limit access and retention. Review temporary-chat, retention, administrator access, export, sharing, upload, permissions, and audit-log settings.
- Review tool permissions and network exposure. Enable only trusted extensions, limit who can add them, and apply the service’s current network hardening guidance.
How to compare local AI setups
There is no evidence-based universal ranking of local AI applications here. Compare the parts of the setup that determine where content goes and who can reach it:
Quick Recap
- Which endpoint performs inference, and what data terms apply?
- Where are chats, uploaded files, indexes, logs, and backups stored?
- Does encryption cover both active storage and backup copies?
- Who has application, database, host, and backup access?
- What retention, deletion, export, and sharing controls are available?
- Which tools or connected services can access or transmit content?
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
