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Duck.ai, Proton Lumo, Brave Leo, and local models are alternatives to consider—but they protect different parts of your privacy. Duck.ai removes some identifying metadata before sending prompts to a model provider; Lumo says it deletes query data after generating a response and protects saved chats with zero-access encryption; Brave Leo is an account-free option integrated into its browser, according to Proton; and local models can keep inference on your computer. None of those descriptions means the same thing as “fully private.” If your priority is that a hosted provider never receives your prompt, a relay-based chatbot is not enough: consider a local model, and account for any connected tools that can send data elsewhere.
At a glance
| Name | Best for | Key spec | Checked |
|---|---|---|---|
| Duck.ai | Reducing identifying metadata sent with prompts to hosted model providers | DuckDuckGo says it removes personal metadata before routing prompts; the selected model provider still processes prompt content | Nov 2026 |
| Proton Lumo | Hosted AI with encrypted saved chat history and stated limits on training | Proton says queries are deleted after response generation and saved chats use zero-access encryption | Nov 2026 |
| Brave Leo | An account-free assistant integrated into a browser | Proton describes it as not retaining conversations on Brave servers or using them for training | Nov 2026 |
| Ollama or LM Studio | Running a model locally to reduce exposure to a hosted assistant provider | Local inference processes prompts on the user’s computer; setup, hardware, and connected tools matter | Nov 2026 |
This is a comparison of privacy boundaries, not an independently verified security ranking. Product policies can change, and vendor statements are not equivalent to independent security audits. Check the current policy and settings for the specific assistant, model, account, and features you plan to use.
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What does “private AI” mean in practice?
“Private” can describe several separate protections: limiting identifying metadata, restricting model training, shortening data retention, preventing an operator from reading saved history, or processing prompts on a device you control. A service can offer one protection without offering the others. For example, removing an IP address before routing a prompt may reduce the identifying information sent along with it, but it does not keep the prompt text from the model provider.
For a useful comparison, ask four questions about the exact interaction you plan to have:
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- Where is the prompt processed? A hosted assistant processes it on company or provider infrastructure. A relay can forward it to another provider. A local model processes it on your computer unless a feature connects to an outside service.
- Who receives the prompt content? Consider the interface operator, the model provider, and any additional service involved in features such as file moderation or web search. Metadata removal does not make prompt content disappear.
- What happens after processing? Training, short-term caching, retention for safety or legal reasons, and saved chat history are different things. “Not used to train” does not necessarily mean “never retained.”
- Who can access saved chats? Chats stored locally, chats synced in readable form, and chats protected by encryption the operator says it cannot decrypt have different access boundaries.
For sensitive personal-finance information, do not treat a privacy label as permission to paste account details, passwords, tax identifiers, statements, or other identifying records into a chatbot. A safer starting point is to remove names, account numbers, addresses, transaction references, and other details that are not needed to ask the question. This reduces what you disclose; it does not guarantee that an AI service is appropriate for every sensitive task.
Is Duck.ai a private alternative to ChatGPT, Gemini, and Copilot?
Duck.ai is a hosted relay that DuckDuckGo says removes personal metadata such as your IP address before sending prompts to an underlying model provider. It may reduce identifying metadata in that handoff, but the selected provider still receives and processes the prompt itself.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsDuckDuckGo says chats are not recorded or stored by default and are not used to train models by DuckDuckGo or its underlying providers. Its Duck.ai privacy help page also describes provider-specific terms and exceptions. This is a useful distinction: the default handling description is not a guarantee that every model and feature has identical retention behavior.
In particular, DuckDuckGo’s help page says some OpenAI and Anthropic models may keep prompts in short-term memory for up to one hour, without writing them to disk. Its service policy says providers delete information when it is no longer needed to generate an output, at most within 30 days, with limited safety and legal exceptions. These statements refer to different descriptions and scopes. Do not treat either duration as a universal retention period for every Duck.ai model: check the privacy dialogue for the model selected at the time you use it.
Saved history and sharing are separate from the handling of a default chat. DuckDuckGo says recent chats are stored locally unless that option is turned off. Optional Sync & Backup stores chats encrypted on its servers so, according to the policy, DuckDuckGo cannot decrypt them; synced chats are automatically deleted if not accessed for 18 months. If you create a shared-chat link, anyone with that link can view the chat. The default link expiration is 48 hours, although other expiry choices are available. Treat sharing as a separate disclosure decision, not as private storage.
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Uploads deserve particular caution. DuckDuckGo says uploaded images and files are screened for child sexual abuse material by a third-party moderation provider and, in some cases, by the model provider; flagged material is retained and reported. That process is distinct from the default text-chat description. If your question can be answered without uploading a document or image, leaving it out avoids creating that additional handling path.
Consider Duck.ai if your main concern is reducing identifying metadata sent with prompts while using a hosted model. Do not choose it on the assumption that the prompt stays on your device, that all models share one retention rule, or that an uploaded file follows exactly the same path as ordinary text.
What privacy protections does Proton Lumo offer?
Lumo is hosted: Proton says its models run on servers it controls. Proton also says it deletes query data after processing, does not use chat content to train models, and protects saved chat histories for Free or Plus accounts with zero-access encryption. This combines server-side processing with a separate protection for saved history; it is not local inference.
According to Proton’s Lumo privacy documentation, “After Lumo processes your query and generates a response, the data is erased.” Proton says saved chats synced through a user’s Proton account are protected with zero-access encryption, meaning Proton says it cannot read their contents. Guest conversations, by contrast, are erased at the end of each session. These are Proton’s descriptions of its service, not an independent audit or a promise about every possible system log, feature, or future policy change.
Proton says chat content is not used to train models except when users expressly submit anonymized feedback for the Apertus model. Feedback is an optional path worth checking before sending: a statement about ordinary chat handling does not automatically cover content a user deliberately submits as feedback.
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The central trade-off is straightforward. Lumo’s stated deletion and saved-history encryption may suit someone who wants a hosted assistant and a protected account history, but the prompt is still processed on Proton-controlled servers. Zero-access encryption for saved chats should not be confused with a claim that inference happens on the user’s own device.
Proton’s support information currently names Qwen 3.5, GLM 5.3, Image-Turbo, FireRed-Image-Edit-1.1, and Apertus 1.5 as available models. Model availability changes, so check Lumo’s current interface rather than relying on a static model list when deciding which one to use.
What should you know about Brave Leo?
Brave Leo is integrated into the Brave browser. Proton’s comparison page describes it as available for free without an account, designed not to retain conversations on Brave servers, and not to use conversations for model training. Proton also describes multi-model access and a pilot of Trusted Execution Environment encryption.
Those claims come from Proton’s comparison of private European AI assistants, not from Brave’s own documentation. They are therefore a starting point for comparison, not enough evidence to make a detailed claim about Leo’s current implementation or the scope of a pilot feature. Before sharing sensitive material, check Brave’s current privacy documentation and the settings for the particular Leo model or feature you intend to use.
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Leo may be worth considering if browser integration and avoiding a separate account are priorities. But “no account” and “no server-side retention,” as described by another provider, do not establish that every request is processed locally or that no outside model provider is involved. Confirm where prompts go and what applies to the chosen model before relying on it for sensitive conversations.
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Can Ollama or LM Studio keep prompts on your computer?
Local models can move more of the privacy boundary onto a device you control: the model runs on your computer rather than sending every prompt to a hosted assistant provider. The Electronic Frontier Foundation (EFF) names Ollama and LM Studio as examples of software that can run models locally, while warning that setup takes technical know-how and generally requires a reasonably modern computer.
EFF says, “Because a local model is running on your computer, it tends to be the most privacy protecting way to use an AI tool, though it does tend to require some technical know-how to set up and a reasonably modern computer to run.” That is a relative statement about where inference takes place, not a guarantee that a whole setup can never disclose data. A system that uses web searches or other connected tools can still send information outside your device. Review what a feature connects to before using it with sensitive prompts.
There is no single hardware specification that can responsibly be given for every local model and workload. The computer needed depends on the model and how you intend to use it; the available guidance does not establish one configuration as suitable for all users. Check the requirements for the exact model and client before buying hardware for this purpose. A local installation also shifts more responsibility to you: you need to understand which model is installed, what optional connections are enabled, and how your device and stored files are managed.
Consider local inference if keeping prompt processing off a hosted assistant provider is your priority and you can handle setup and device requirements. Do not assume “local” covers connected tools: an online search, remote service, or other feature can create a separate route for information to leave the computer.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which alternative fits the privacy boundary you care about?
Start with the information you want to protect, then choose the boundary that addresses it. A preference for less identifying metadata points toward a different choice than a requirement that a model provider never receive your prompt.
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| If your priority is… | Option to investigate | What it does not settle |
|---|---|---|
| Reducing personal metadata sent with prompts to a hosted provider | Duck.ai | The provider still processes prompt content; model-specific caching and retention terms matter |
| Hosted processing with stated deletion after response generation and encrypted saved history | Proton Lumo | Inference still happens on Proton-controlled servers; Proton’s statements are not an independent audit |
| An assistant integrated into a browser without a separate account, as described by Proton | Brave Leo | Check Brave’s own current documentation for prompt routing, retention, and feature details |
| Processing prompts on a device you control | Ollama or LM Studio with a suitable local model | Setup and hardware needs vary; connected tools can transmit data externally |
These are not rankings of answer quality. The cited material does not provide comparative benchmarks establishing that any option matches another assistant for coding, research, financial explanations, or general answers. A public discussion describes a desire for “clear, precise, and well-structured answers” with privacy, but an individual request is not evidence that a particular service delivers equivalent capability. Treat answer quality as a separate question to evaluate for your own non-sensitive tasks, rather than inferring it from a privacy policy.
How can you reduce disclosure when asking an AI about money?
Choose the least revealing prompt that still gives the assistant enough context. For example, rather than pasting a bank statement, summarize the relevant categories and amounts yourself, remove names and account details, and ask a general question. That does not make any service risk-free, but it avoids sending unnecessary identifiers and documents.
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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →- Decide whether a hosted service is acceptable. If the model provider must not receive the prompt, a metadata-removing relay does not meet that requirement. Consider local inference, while checking that connected tools are not enabled for the task.
- Check the exact model and feature. Read the assistant’s current privacy dialogue or documentation for routing and retention. A service can have different arrangements by model, and ordinary chats may be treated differently from uploads, feedback, voice, sync, or shared links.
- Remove details the question does not need. Avoid including credentials, full account numbers, tax identifiers, addresses, names, or raw records. Replace exact personal details with a simplified description or rounded figures where that still lets you ask the question.
- Choose history and sharing deliberately. Review whether chats are saved locally or synced, who can access saved history, and whether a conversation link can be opened by anyone who has it. Do not assume a conversation is private just because it is not used for training.
- Recheck before a different kind of interaction. Uploading a file, submitting feedback, or turning on a connected tool can involve a different data path. If you cannot establish how a feature handles the information, leave it off for sensitive material.
How we picked these alternatives
This list focuses on options with a documented privacy distinction relevant to replacing a mainstream hosted assistant: Duck.ai’s metadata-removing relay, Lumo’s stated query deletion and zero-access saved history, Brave Leo’s browser integration and account-free availability as described by Proton, and local inference using examples named by EFF. The comparison separates prompt processing, recipients, training, retention, saved-history access, and convenience instead of compressing them into a single “private” score. It does not claim independent verification, rank answer quality, or treat a vendor policy as proof of equivalent security.
For further context, see the EFF’s privacy considerations for AI tools, which explains why a local model can reduce exposure while still requiring attention to setup and connected features.
Frequently Asked Questions
Can I use AI without sending my prompts to a company?
A model running locally can process a prompt on your computer instead of sending it to a hosted assistant provider. That answer changes if you enable connected features such as web search, so check each feature’s data path rather than relying on the word “local.”
Does encrypted AI chat mean the provider cannot see my prompt?
Not necessarily. Encryption may protect saved history from an operator while a hosted model still needs to process the prompt to generate a response; check whether a service distinguishes inference from stored chats.
Can I get ChatGPT-level answer quality from a privacy-focused alternative?
The cited sources do not provide head-to-head quality benchmarks, so equivalent performance cannot be promised. Test alternatives with non-sensitive questions representative of your needs, and assess privacy settings separately from answer quality.
Should I upload a bank statement to an AI chatbot for budgeting help?
Avoid uploading an unredacted statement when a summary of the relevant figures will do. File handling can involve additional providers or moderation steps beyond ordinary text chat, so remove identifying details and check the upload policy before sharing anything.
