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For an AI chatbot outside Meta’s product ecosystem, compare Proton Lumo, Duck.ai, and Brave Leo. Their published privacy approaches differ: Proton describes erasing query data after processing and encrypting saved history so Proton cannot read it; DuckDuckGo describes removing identifying metadata before sending prompts to model providers, with stated exceptions; and Brave says it does not log hosted Leo chats after generating a response. If you want prompts processed on your own computer, Brave also documents a way to connect a locally running model—but that shifts hardware, setup, and security responsibilities to you.
Those are company descriptions, not independent audits or guarantees that no one could ever access your data. The useful question is not simply whether a chatbot is “private,” but what it processes, what persists, who receives it, and where the model runs.
What “private AI chatbot” should mean
A chatbot has to process a prompt to produce a response. Privacy differences arise around the surrounding data practices: whether a service keeps prompts or responses afterward, whether it uses conversations to improve models, whether another model provider receives the prompt, and whether processing happens in a company’s cloud or on your device.
Before choosing a service, check these separate questions rather than relying on a single privacy label:
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- Processing: Which company or model provider receives the prompt, files, or other content you submit?
- Retention: Is information stored after the response, cached briefly during processing, or kept only when you save chat history?
- Model improvement: Are conversations used for training by default, only after you opt in, or under particular exceptions?
- Storage location: Is history on the provider’s servers, encrypted so the provider says it cannot read it, or kept in local browser storage?
- Exceptions: Do safety reviews, abuse investigations, legal requirements, feedback, or file moderation change the ordinary rules?
- Account and region: Do the terms apply to your account type, location, plan, and the exact chatbot surface you use?
A service may say it does not retain a chat log while still processing the prompt on its servers. Likewise, a locally stored conversation is not the same thing as a model running locally. Keep those distinctions in mind when comparing the options below.
How the main alternatives differ
Proton Lumo, Duck.ai, and Brave Leo are the clearest alternatives in the available product documentation for readers who want a ready-to-use chatbot outside Meta’s ecosystem. The comparison below describes what each company says about its own service; it is not an independent security assessment.
| Option | Where the model runs | What the provider says about chats | Important distinction |
|---|---|---|---|
| Proton Lumo | On Proton-controlled servers. | Proton says queries are sent over TLS, erased after processing, and not logged. It says chats are not used to train its models, except with express permission for anonymized feedback on an Apertus 1.5 response. | Saved history for Free or Plus users is synced using zero-access encryption. This describes saved history, a different stage of handling from processing and deleting a query. |
| Duck.ai | DuckDuckGo sends prompts to underlying model providers after removing identifying metadata. | DuckDuckGo says chats are not stored by default and provider agreements restrict retention and training. | The help page identifies exceptions, including short-term caching for some models and moderation of uploaded files. |
| Brave Leo, hosted models | On Brave-run hosted models. | Brave says chats are not logged after response generation or used to train models. Chat history is stored locally on the device. | Temporary chat and disabled history are available. A model connected through BYOM can be remote, in which case the endpoint provider’s practices matter. |
| Brave Leo, local model through BYOM | On your own desktop when connected to a locally running model. | Brave’s BYOM documentation describes prompts and conversations staying on-device for a local endpoint. | You supply compatible software and hardware, and take on model setup, updates, and device security. |
Privacy commitments can be useful for deciding what to try, but the cited product pages do not establish that one service is “the safest.” They do not independently verify implementation or cover every security incident, legal process, account setting, or regional requirement.
Proton Lumo: cloud processing with encrypted saved history
Lumo is a hosted assistant: Proton says its models run on Proton-controlled servers. It also says query data is erased after it processes the request and generates a response, and that queries are not logged. Proton’s stated training policy is that chats are not used to train its models unless a user expressly permits anonymized feedback on an Apertus 1.5 response.
Saved history is a separate case. Proton says Free or Plus users’ saved history is synced using zero-access encryption, meaning Proton says it cannot read that stored history. This should not be confused with the processing step: the model still needs to handle a query to answer it, and encrypted saved history describes how retained history is stored, not how a prompt is processed.
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Proton’s current page lists Qwen 3.5, GLM 5.3, Image-Turbo, FireRed-Image-Edit-1.1, and Apertus 1.5. That roster is a snapshot, not a promise that the same models or features will remain available. Verify the current model and feature list in the service before relying on a particular capability.
Lumo is a reasonable place to start if you want a hosted assistant and value the distinction Proton makes between processing a query and storing a saved conversation. Its documentation does not make the service local: prompts are processed on Proton’s servers.
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Duck.ai: anonymized requests with provider-specific exceptions
Duck.ai is DuckDuckGo’s chat interface to models from underlying providers. DuckDuckGo says it removes identifying metadata, such as an IP address, before sending prompts to those providers. It also says chats are not stored by default and its provider agreements restrict data retention and training.
Read the exceptions on DuckDuckGo’s help page alongside the default policy. It identifies up to one hour of in-memory prompt caching for some OpenAI and Anthropic models, retention where legally required or related to abuse, and moderation of uploaded files. Those qualifications mean “not stored by default” should not be read as “no transient processing or retention can ever occur.” Text-chat handling and file-upload handling are not necessarily identical.
Duck.ai may suit someone who wants a single interface with access to multiple underlying models and values the stated removal of identifying metadata before prompts are forwarded. Check which model you select and whether you are uploading a file, because the listed exceptions are model- or content-specific.
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Brave Leo: browser chat, local history, and BYOM
For hosted Leo models, Brave says conversations are not stored or logged by Brave after a response is generated and are not used to train models. Brave says chat history remains on the device. Its documentation also describes temporary chat and a setting to disable history. These are browser-integrated options, but local chat history does not mean the hosted model processed the prompt on your computer.
Brave’s “Bring Your Own Model” (BYOM) route can connect Leo to a model endpoint. If that endpoint runs locally, the model processes prompts on your desktop. If it is remote, another provider receives the prompts and its privacy policy applies; Brave’s hosted-model commitments do not automatically govern that provider.
Brave’s help documentation for BYOM calls for desktop Brave and a compatible model-serving framework. It lists a minimum of 8 GB of RAM and model storage ranging from 829 MB to 40 GB, as well as sufficient processing power. Those figures are requirements described by Brave, not a guarantee that every model will run well on every device. Performance depends on the model and available hardware; the larger storage figure also makes clear that local inference can require substantial disk space.
Brave’s model list is dated October 6, 2026, so treat its model choices and feature availability as time-sensitive. If you choose a local model, you also become responsible for its installation and updates, plus the security of the device and any local files, backups, or network connections. Running a model locally gives you more control over where prompts are processed, but it does not by itself make a computer secure.
How familiar chatbots handle model improvement
Using a non-Meta chatbot does not automatically mean opting out of model improvement or all forms of retention. The consumer policies for other widely used services illustrate why settings, account types, and exceptions need to be checked separately.
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| Service and scope | What its cited documentation says | What to verify |
|---|---|---|
| Claude consumer service | Anthropic’s consumer model-improvement article, dated March 16, 2026, says chats and coding sessions may be used to improve models if the user chooses, if a conversation is flagged for safety review, or through another explicit opt-in. Incognito chats are not used for model improvement. If a user gives feedback, Anthropic says it may retain the related conversation for up to five years. | Check the current privacy setting, whether a session is Incognito, and what happens if you submit feedback. These consumer statements do not automatically describe commercial or API use. |
| ChatGPT individual service | OpenAI says content from individual services may be used for training and that users can opt out. Temporary Chat is not used to train models. OpenAI says business inputs and outputs are excluded by default unless the organization explicitly opts in. | Check the setting and account type. Business terms should not be assumed to apply to a free or personal account. |
| Gemini Apps | Google’s notice, last updated June 29, 2026, describes data processed when someone interacts with Gemini Apps while signed in, including prompts, shared files and media, and Gemini Live recordings and transcripts. It supplements Google’s general privacy policy; signed-out use is explained separately. | Confirm whether you are signed in and which Gemini surface you are using. The cited notice is not a complete setting-by-setting comparison of training or retention choices. |
These policies are not interchangeable, and the table does not rank the services. A control documented for one account type or product surface may not apply to another. For any service, read the current terms and controls for the account and region you actually use.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose based on what you need to protect
For a hosted assistant with explicit retention statements
Compare Lumo’s description of query deletion and encrypted saved history with Duck.ai’s anonymization approach and its provider-specific exceptions. In both cases, the company’s published policy is evidence of its stated approach, not proof that every implementation detail has been independently audited. Decide whether your priority is how a service handles saved history, which companies receive a prompt, or how files are treated.
For a browser-integrated chatbot
Leo offers hosted models and a BYOM path. Hosted Leo and a local model have different processing locations; a remote BYOM endpoint has a different recipient again. Identify the endpoint before sending sensitive information, rather than assuming the browser integration determines the endpoint’s data practices.
For prompts you want processed on your own device
Consider local inference only if you can support the model with compatible hardware and are prepared to install and maintain the serving software. Brave’s published minimums—8 GB RAM and model files ranging from 829 MB to 40 GB—are a starting point, not a device recommendation or a promise of acceptable speed. The model’s size and the device’s processing capability matter.
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Do not infer legal compliance or suitability from consumer privacy pages. Review the exact service, plan, contract, jurisdiction, and organization policy that govern the information. If those requirements do not clearly allow a tool, use an approved system or ask the responsible security or privacy team before submitting the data.
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A practical checklist before sending a prompt
- Identify the product surface. Confirm whether you are in Lumo, Duck.ai, hosted Leo, a local Leo connection, or a remote BYOM endpoint. The endpoint determines which company or device processes the request.
- Check the current policy and settings. Look for retention, model-improvement, temporary-chat, history, and feedback rules. Confirm that the wording applies to your account type and location.
- Check whether the prompt includes a file. DuckDuckGo’s documentation identifies file moderation as an exception; avoid assuming an uploaded file follows the same handling as text.
- Decide whether you need saved history. A history feature may retain content differently from the transient processing needed to answer a prompt. Turn history off or use a temporary mode if that better fits your needs.
- Minimize what you disclose. Remove names, account numbers, secrets, and identifying details that the task does not require. Avoid entering credentials, private keys, or confidential work material into an unapproved chatbot.
- For local inference, verify the setup. Confirm that the selected model-serving framework is compatible, that storage and memory are sufficient, and that the endpoint is actually local rather than remote. Keep the computer and software protected and maintained.
Costs, availability, and changing features
The cited privacy documentation does not establish a current, comparable price for these services, so do not choose based on a price inferred from these privacy claims. Check each service’s current plan details, regional availability, and feature limits directly. Model rosters, settings, and endpoint options can change: Proton’s listed models are current-page examples, while Brave’s model list is dated October 6, 2026.
Availability and data handling may vary by location, plan, feature, or account type. Google’s Gemini notice specifically concerns signed-in Gemini Apps and says Google Ireland Limited serves the EEA and Switzerland while Google LLC serves elsewhere. That notice supplements its general privacy policy, and signed-out use is addressed separately. Check the terms that apply in your region rather than assuming one country’s policy describes every user.
What the published claims can—and cannot—tell you
Company documentation can help identify stated defaults and exceptions, but it is not a substitute for an independent security audit, hands-on testing, or legal advice. The available product descriptions do not establish model-quality benchmarks or a definitive privacy winner. Nor does a claim about not training on chats settle questions about access, security incidents, legal demands, or data handling beyond the specific policy language.
For the strongest control over processing location among these options, a properly configured local model avoids sending the prompt to a hosted model provider. That choice also requires trust in your device and setup. If you prefer a hosted assistant, compare the specific retention and training rules, understand every provider in the processing path, and avoid submitting information you cannot afford to expose.
Quick Recap
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.

