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Duck.ai, Proton Lumo, and Brave Leo are useful privacy-conscious alternatives to mainstream AI chatbots, but none can be declared objectively “the most private” from the providers’ policies alone. Each makes different promises about training, retention, human access, metadata, encryption, and which model receives your prompt. Choose by the control that matters most to you rather than by a single privacy label.
The comparison below reflects the providers’ official policy pages as accessed in 2026. Those pages do not establish comparable independent audits or a cross-service privacy score, and settings can change by account, plan, model, or feature.
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Privacy is a set of separate questions, not a checkbox. A service can say it does not train on chats while still processing prompts on its servers, keeping temporary logs, allowing limited human review, receiving account metadata, or forwarding content to another model provider.
Evaluate these controls independently:
- Training: whether prompts and responses may be added to model-training datasets.
- Retention: whether the service stores conversation content, for how long, and whether deletion also removes copies held by model partners.
- Human review: whether staff or contractors can inspect conversations, and what exceptions apply.
- Metadata: whether IP addresses, account identifiers, device data, or other identifying details accompany a prompt.
- Saved-history protection: where history is stored and whether it is encrypted so the provider cannot read it.
- Model routing: which company’s model processes the request and under which provider’s terms.
The services below describe these controls differently. A provider’s statement is not the same as independent verification, so treat the policies as commitments to examine and keep checking.
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How private is Duck.ai?
DuckDuckGo says Duck.ai does not record or store chats by default, removes personal metadata such as your IP address before a prompt is sent to model providers, and has agreements requiring those providers to delete prompts and responses after generating a reply and not use chats for training. Read the service’s current terms before relying on any one exception or model.
Duck.ai’s privacy help page documents a specific qualification: certain requests to OpenAI models may be cached for up to one hour. That is a temporary processing exception, not a contradiction of the default no-storage claim, but it matters if your threat model rules out any short-lived copy.
Duck.ai acts as a layer between you and several model providers. The model you select can therefore change the processing path and the applicable limitation. Check the model selector and the linked policy at the time you use it rather than assuming every model has identical handling.
Its metadata-removal claim is distinctive among the three alternatives discussed here. Removing an IP address before forwarding a prompt reduces direct network identification at the model provider, but it does not make the text itself anonymous: names, account numbers, locations, or distinctive events typed into the prompt can still identify someone.
Source: Duck.ai privacy help.
What privacy protections does Proton Lumo provide?
Proton says Lumo does not use chats to train its models, erases logs after each chat, and protects saved chat history with zero-access encryption. “Zero-access” describes stored history: Proton says the encryption is designed so the provider cannot read the saved content.
That protection does not mean a prompt is never visible to processing infrastructure. Proton says prompts are processed on its own GPU servers, so the text must be available to the service while it generates a response. Distinguish the short processing window from the encrypted history that you choose to save.
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Lumo’s public privacy explanation does not establish a comparable duration for every operational log, nor does it provide a cross-service audit result. If you need a precise deletion guarantee for a regulated workflow, ask Proton for the current account- and feature-specific terms and document the answer.
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Saved-history encryption is useful when an attacker or an unauthorized employee obtains the storage system, but it cannot protect information from the model during inference. Avoid placing secrets in a prompt simply because a later history view is encrypted.
Source: Proton Lumo privacy.
How does Brave Leo handle chats and model choices?
Brave describes Leo as an AI assistant integrated into its browser and says, in its overview, that chats are not retained or used for training. Its model-specific help page adds an important qualification: conversations using listed third-party Claude models may be retained for no more than 30 days, while Brave-hosted models are described separately.
Therefore, “Leo does not retain chats” is too broad without naming the model. Before sending a sensitive prompt, identify whether Leo is using a Brave-hosted model or a third-party option and read the current terms for that route.
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Leo’s browser integration can be convenient because the assistant is available beside the page you are reading. Convenience also creates a context risk: prompts can include text copied from open tabs or browsing activity. Select and paste only the minimum text needed, and review the model choice before submitting.
Sources: Brave AI overview and Brave’s model differences.
How do these services compare on the controls that matter?
The table records what the cited provider pages say, not an independently measured outcome. “Not stated” means the reviewed material did not establish a comparable control.
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| Service and route | Training use | Retention | Human review | Metadata before model provider | Saved history and protection | Model or provider processing the request |
|---|---|---|---|---|---|---|
| Duck.ai | DuckDuckGo says chats are not used for training under its provider agreements. | No recording or storage by default; certain OpenAI requests may be cached for up to one hour. | Not stated as a comparable, universal rule; check the current model terms. | DuckDuckGo says personal metadata such as IP addresses is removed before forwarding. | Default chats are not stored; saved-history details depend on the feature and current policy. | Third-party model providers selected through Duck.ai; routing varies by model. |
| Proton Lumo | Proton says chats are not used to train its models. | Proton says logs are erased after each chat; exact operational-log details are not stated. | Not stated in the cited privacy explanation. | Not stated. | Saved chat history uses zero-access encryption. | Prompts are processed on Proton’s GPU servers. |
| Brave Leo, Brave-hosted model | Brave’s overview says chats are not used for training. | Brave describes chats as not retained in its overview; model-specific terms apply. | Not stated in the cited pages. | Not stated. | Storage and encryption details depend on the feature and model route; not fully specified in the cited pages. | Brave-hosted models, subject to the selected model’s terms. |
| Brave Leo, listed third-party Claude model | Read the model-specific terms rather than applying the overview to every route. | Conversations may be retained for no more than 30 days. | Not stated in the cited pages. | Not stated. | Not stated as a separate, comparable control. | A listed third-party Claude model. |
| Google Gemini Apps (comparison point) | Training and review controls depend on Gemini Apps Activity settings and Google’s current terms. | Signed-in activity defaults to 18-month auto-delete, with three-month, 36-month, and indefinite options. Chats reviewed by human reviewers and related data may be retained for up to three years and are not deleted when a user deletes activity. | Google documents reviewer-related retention; this does not mean every chat is reviewed. | Not comparable to Duck.ai’s stated stripping process in the cited page. | History is governed by Gemini Apps Activity settings; the cited page does not establish zero-access encryption. | Google’s Gemini models and services. |
Policy durations in this table are limits or settings stated by the providers, not measured privacy results. Availability and wording can change, so use the linked pages as the starting point for a current check.
Is “not used for training” enough to protect a conversation?
No. It answers only one question: whether the provider says your content is added to training. It does not answer how long the prompt is held while generating a response, whether abuse or safety teams can inspect it, what metadata accompanies it, or whether another model company receives it.
For example, Duck.ai’s no-training position coexists with a documented up-to-one-hour cache for certain OpenAI requests. Lumo’s zero-access encryption protects saved history but does not prevent Proton’s servers from processing a live prompt. Leo’s headline no-retention statement needs the 30-day qualification when a listed third-party Claude model is selected.
Use a four-part reading habit: identify the training rule, find the retention period and exceptions, look for human-review language, and trace the model route. Only then decide whether the service fits the sensitivity of your task.
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There is no proven overall winner in the cited material. Match the service to the control you value most.
When stripping network identifiers is your priority
Duck.ai is the clearest fit among these pages because DuckDuckGo explicitly says it removes personal metadata such as IP addresses before sending prompts to model providers. That does not anonymize information voluntarily typed into the prompt, and the temporary caching exception still applies to certain requests.
When encrypted saved history matters most
Lumo is the only option here whose cited policy specifically describes zero-access encryption for saved chat history. Remember that encryption of stored history and confidentiality during prompt processing are different protections.
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When you want a browser-integrated assistant
Leo is designed to sit inside the Brave browser. Choose the model deliberately: the no-more-than-30-day retention qualification applies to listed third-party Claude models, while Brave-hosted models are covered by separate descriptions.
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When you need configurable account deletion
Gemini is included as a comparison point rather than a recommendation for privacy. Its signed-in activity setting offers three-month, 18-month default, 36-month, or indefinite auto-delete choices, but reviewer-related data can remain for up to three years and is not removed when activity is deleted.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you use a privacy-focused chatbot safely?
Service policy cannot compensate for unnecessary disclosure. Apply these steps before and during a session:
- Classify the prompt. Do not paste passwords, private keys, medical records, unredacted legal documents, customer lists, or confidential source material into a hosted chatbot unless your organization has approved that exact service and route.
- Minimize identifiers. Replace names, email addresses, account numbers, exact addresses, and unique dates with neutral labels. Keep only the details needed for the answer.
- Select the model consciously. In Duck.ai and Leo, the chosen model can change the provider receiving the request and the applicable retention terms.
- Check account and history settings. Disable saved history when you do not need it, and understand whether a deletion control covers only your account view or also partner copies.
- Review browser context. With an integrated assistant such as Leo, avoid sending full pages or open-tab content when a short excerpt will do.
- Record the policy date. For workplace or regulated use, save the relevant policy URL and the date you checked it. Recheck after a model, plan, or feature change.
- Delete local copies. Clear downloaded transcripts, screenshots, clipboard managers, browser history, and team documents that may preserve the conversation outside the chatbot.
What can go wrong, and how can you recover?
You chose a different model than expected
Stop sending additional content, note the selected model and time, and read that model’s policy. If the service provides a deletion request, submit it with the conversation identifier; do not assume deleting the visible thread removes a partner’s temporary cache.
A prompt contains personal information
Use the service’s deletion controls immediately, then rotate exposed credentials, notify the affected person or security team when appropriate, and preserve only the minimum incident details. A chatbot deletion confirmation is not proof that every downstream copy has already disappeared.
You need an audit trail
Capture the policy version or page date, account setting, model name, and retention statement before production use. If the provider cannot state who can access prompts or how long operational logs remain, classify that uncertainty explicitly in your risk record.
The answer is sensitive or wrong
Privacy and accuracy are separate. Verify legal, medical, financial, security, and employment advice through an authoritative source, and avoid adding more confidential context merely to improve a speculative answer.
Why does the Gemini example change how you read deletion promises?
Google’s Gemini Apps policy illustrates why “auto-delete” and “deleted” are not interchangeable. For signed-in users, Gemini Apps Activity defaults to 18-month auto-delete, with three-month, 36-month, and indefinite alternatives. Google also says chats reviewed by human reviewers and related data may be retained for up to three years, and that this reviewer-related data is not deleted when a user deletes activity.
This is not a claim that every Gemini chat is reviewed. It is a reminder to ask whether a deletion setting covers reviewer copies, safety records, backups, or model-provider transfers. Apply the same questions to any alternative, even when its headline language sounds stronger.
Source: Google Gemini Apps Privacy Hub.
How should you monitor these services over time?
Privacy terms are feature-specific and can change when a provider adds a model, introduces memory, changes account plans, or reroutes requests. Review the policy whenever one of those events occurs rather than relying on an old screenshot or a general product slogan.
- Confirm the current model name and whether it is hosted by the chatbot company or a third party.
- Look for new language about temporary caching, abuse monitoring, safety review, or support access.
- Check whether saved history, memory, voice, image, and file features have separate retention rules.
- Verify that account deletion and conversation deletion describe the same scope.
- For organizational use, obtain written terms or a data-processing agreement instead of inferring guarantees from consumer help pages.
The official pages cited here did not provide a common independent audit or a defensible privacy ranking. A careful choice is therefore a documented match between your data risk and the provider’s stated controls, with uncertainty treated as a limitation rather than silently assumed away.
Frequently Asked Questions
Can a chatbot keep a copy even when chat history is turned off?
Yes. History controls can govern what appears in your account while temporary caches, abuse-prevention logs, reviewer copies, or a downstream model provider follow separate rules. Check the service’s retention exceptions and model route before assuming that an empty history means zero copies.
Is an encrypted chat history safe to use for confidential work?
Encryption reduces the risk from unauthorized access to stored history, but the service still has to process a live prompt to answer it. Remove direct identifiers and obtain organizational approval before entering confidential material.
What should I check when a chatbot adds a new model?
Confirm who operates the model, whether prompts leave the chatbot company, the maximum retention period, human-review exceptions, and whether metadata is forwarded. A new model can change the applicable terms even when the assistant’s name and interface stay the same.
Should I trust a privacy policy without an independent audit?
Treat it as the provider’s stated commitment, not a measured guarantee. For high-risk use, request current contractual terms, document the policy date and settings, and prefer a service that can answer your retention and access questions precisely.
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