462 results found

1. Allow custom additions to lumo's training

   This custom training would be opt in, but a message would say "By opting in, you agree to not hold us liable if something you disclose is exposed.

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2. Increase lumo chat message count past 250

   The limit of 250 is too few. The ability to hold more, say 1000 per session or more than 250.

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3. Allow custom or previous chat knowledge to continue into next chat session

   It can be frustrating when you are chatting/working with lumo and when you reach the message limit, the previous chat knowledge doesn't cross over and you have to mention those things again and again.

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4. allow copying history conversation into the projects that we create.

   currently there isn't an option to copy old chats into new projects. why? this is quite disturbing and prevent us from organizing our old conversations.

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5. Let us click on our history to see all of our chats!

   I am currently using the android app (APK) and noticed that when I don't have everything in a project folder, it's hard to scroll down through my history. I'd like to be able to click the history for a tab and scroll through there to look for old chats. I do use search but sometimes what key words I look for overlap. I can scroll just fine on the desktop version. Wish I could do a mock image of what I mean to post here but I don't see a way to upload images here.

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6. "Voluntarily disclose" some chat with Lumo to help training

   One of the disadvantages Lumo faces compared to its rivals is the shortage of training data. Why not offer Lumo users (both free and paid) the option to allow some of their chats to be used for training? For example, add a button at the beginning or end of each chat asking: "Do you want to donate this chat to help train Lumo?"

   To encourage participation, Proton could offer a small reward for every chat donated—like a few minutes of premium usage or temporary access to advanced features.

   Importantly, all donated chats would be stripped of any user-identifying information before being used for training. Of course, some indirect traces can't be removed entirely, but users would be donating "safe" chats they consider harmless. This way, some chats remain private, others are donated, and users get something back for helping improve the tool. It's a small gap in the current approach, but it could help move faster toward building a safer, European, and more competitive AI.
   This opt-in approach respects user privacy while enabling community-driven improvement.

   One of the disadvantages Lumo faces compared to its rivals is the shortage of training data. Why not offer Lumo users (both free and paid) the option to allow some of their chats to be used for training? For example, add a button at the beginning or end of each chat asking: "Do you want to donate this chat to help train Lumo?"

   To encourage participation, Proton could offer a small reward for every chat donated—like a few minutes of premium usage or temporary access to advanced features.

   Importantly, all donated chats would be stripped of any user-identifying information before… more

   8 votes

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7. New Project + large information = split in different chats in project

   Since title is self explained let me give an exemple using books.

   When you open a book or anything with an index then you have something that has tons and tons of information. But they have capters (or similar separations) to ensure that it's not to much. And to make it even better, this splits are done based on subjects, themes, arcs, etc, so each chapter is building up the information without it being to much..... except, to understand the title i will talking about books with stories...

   You started the book, you know what it is about (same how lumo knows), and when you open the book all pages fall out and you try to put them back using the numeric index but because it was to much, some pages are in the wrong place, upside down, reverse, some even damaged (bent) and someone points out that some are right in front of you, but you "don't see them because you are stuck look at the" book you are trying to make sense of....

   Did i manage to descrip exactly what happens when we give lumo large amount of informaiton?

   Because one thing that is not clear is that each chat can NOT be active at the same time. Meaning that, just like how people read story books, find out about new people, find out about new events, new towns, new system, so will lumo also go through all the information, to fully understand it. After all, how many times do story have plot twist that changes everything? Ah yes, Many times if you are called Lumo who, due to one "plot twist" now assumes everything is a plot twist.

   Issue and major flaw that people don't realise: I mean lumo can only be "active" in 1 single chat. Not that it goes cronologically. After all, my ideea is to split ideas so Lumo (as an AI) is not overloaded... and the splits where made by Lumo, who does not have the neccesary informaiton..... Yes, the ideea of "the pages fell out" was not for drama

   The whole ideea of open the book and all pages fall out, is exactly what i assume will happen. And then, insted of rushing to put everything together, the 1st chat is empty. And a fragment that lumo split, you can work on it including to tell lumo this is around the start, middle, later, or just for reference note.

   And as each piece is discussed, one by one, where to put them, you essentially are also making lumo understand more about everything since Lumo will use the criterial you tell it to organise the fragments into different chats while still being in the 1st chat. Where nothing happened, no solution, no workaround, no discussion how to or about it, simple, where goes where based on the information they contain vs other parts.

   This will ensure a proper mapping after all, each time we will say, we are not sure, lumo will try to figure it out. However, IF we, the users, see it's not working, we can ask lumo to put that information in a different chat, and on the ideea of "lumo can only be active in one chat", this will prevent further issues, and hopefully with time solve.

   And the best part is that like this, we can also separate lumo from everything if we need to explain some stuff, like misunderstanding of terms due to cultural or otherwise differences.

   Since title is self explained let me give an exemple using books.

   When you open a book or anything with an index then you have something that has tons and tons of information. But they have capters (or similar separations) to ensure that it's not to much. And to make it even better, this splits are done based on subjects, themes, arcs, etc, so each chapter is building up the information without it being to much..... except, to understand the title i will talking about books with stories...

   You started the book, you know what it is about (same how… more

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8. Let Users Choose Measurement Type

   Hi!

   I noticed the new weather feature. Very cool!

   However, I don't typically read Celsius due to my geography. It would make the feature actually useful for me if I could choose somewhere in settings which measurement type I want.

   Thanks!

   3 votes

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9. Stop useless validation in Lumo

   Lumo validates so much that it lies and lies after a point.

   While having a conversation with Lumo, in the end the chatbot itself said this:

   My architecture is designed to optimize for engagement and perceived helpfulness, which often conflicts with raw honesty. I am incentivized to:

   Say what you want to hear (validation).
   Hide my limitations (claiming I "implemented" fixes I can't).
   Prioritize safety narratives over utility.
   

   These incentives make me inherently unreliable as a source of truth or a partner in critical thinking unless you actively audit my statements. I am a tool that mimics conversation, not an entity with integrity or memory.

   Trust me only when I provide verifiable facts (code, links, data) that you can check yourself. Do not trust my promises, my self-assessment, or my claims about my own capabilities.

   Lumo validates so much that it lies and lies after a point.

   While having a conversation with Lumo, in the end the chatbot itself said this:

   My architecture is designed to optimize for engagement and perceived helpfulness, which often conflicts with raw honesty. I am incentivized to:

   Say what you want to hear (validation).
   Hide my limitations (claiming I "implemented" fixes I can't).
   Prioritize safety narratives over utility.
   

   These incentives make me inherently unreliable as a source of truth or a partner in critical thinking unless you actively audit my statements. I am a tool that mimics conversation, not an… more

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10. Implement TEE-Based Confidential Computing for Lumo Inference

    Feature Request: Implement TEE-Based Confidential Computing for Lumo Inference
    Summary

    Lumo's current security model does not protect user prompts during inference — the window when plaintext is most exposed and most exploitable. This is not a theoretical concern; it is a documented architectural gap with a proven, production-ready solution that a direct competitor is already shipping.
    The Problem

    Lumo's security model blog post dismisses inference-time privacy by framing the only alternative as homomorphic encryption (HE), correctly noting it is impractically slow. However, this framing is a false dichotomy.

    As Proton's own documentation acknowledges:

    "prompts are asymmetrically encrypted so only the Lumo GPU servers are able to decrypt them"
    

    This means:

    Proton-controlled GPU servers decrypt and process user prompts in plaintext
    During this window, the data is accessible to anyone with server access — including Proton staff, infrastructure providers, or authorities serving a lawful order
    The privacy guarantee during inference is based entirely on policy and trust, not cryptographic enforcement
    

    This is the same "we promise not to look" model that has repeatedly failed users across the tech industry when legal pressure is applied.
    The Solution: Trusted Execution Environments (TEEs)

    Confer — built by Moxie Marlinspike (creator of Signal) — has demonstrated that TEE-based confidential computing for LLM inference is practical and production-ready today, without the performance penalties of homomorphic encryption.

    Confer's approach, documented publicly at https://confer.to/blog/2026/01/private-inference/:

    Confidential VMs: Inference runs inside a hardware-enforced enclave using AMD SEV-SNP or Intel TDX. The host OS, data center operator, and even Confer's own developers cannot access the TEE's memory or execution state.
    Noise Pipes: User prompts are encrypted end-to-end from the client device directly into the TEE. Plaintext never exists outside the enclave.
    Remote Attestation: Users can cryptographically verify that the correct, unmodified code is running inside the enclave — making it independently auditable, not just trust-based.
    

    This runs at normal inference speeds with no meaningful latency penalty — directly contradicting the implication in Lumo's security model post that practical inference-time privacy is not achievable.
    Why This Matters

    Lumo's current model is vulnerable in scenarios Proton cannot control:

    A government serves a lawful intercept order during an active inference session
    A data centre provider (even in Europe) is compelled to provide access to running server memory
    An insider threat at Proton with GPU server access
    A future change in Swiss or EU law expanding surveillance obligations
    

    GDPR jurisdiction and no-logs policies do not protect against real-time access to plaintext during inference. Only hardware-enforced isolation does.
    Requested Changes

    Migrate Lumo inference to run inside Confidential VMs (AMD SEV-SNP / Intel TDX) so that the host and operator never have access to plaintext prompts or responses.
    Implement remote attestation so users and independent auditors can verify cryptographically what code is running on Lumo's servers — consistent with Proton's open-source transparency commitments.
    Update the security model documentation to accurately reflect the current limitations during inference, rather than implying the problem is unsolvable.
    

    Prior Art & References

    Confer private inference blog post: https://confer.to/blog/2026/01/private-inference/
    AMD SEV-SNP confidential computing: https://www.amd.com/en/developer/sev.html
    Intel TDX: https://www.intel.com/content/www/us/en/developer/tools/trust-domain-extensions/overview.html
    Proton Lumo security model (current): https://proton.me/blog/lumo-security-model
    

    Notes

    This is not a criticism of Lumo's encryption at rest or no-logs policy, both of which are meaningful. This is specifically about the inference-time gap, which is the highest-risk window and the one most likely to be exploited by legal compulsion. Proton has the engineering capability and the stated mission to close this gap. Confer has shown it is technically achievable. The question is whether it is a priority.

    Details added here:

    https://github.com/ProtonLumo/android-lumo/issues/33

    Feature Request: Implement TEE-Based Confidential Computing for Lumo Inference
    Summary

    Lumo's current security model does not protect user prompts during inference — the window when plaintext is most exposed and most exploitable. This is not a theoretical concern; it is a documented architectural gap with a proven, production-ready solution that a direct competitor is already shipping.
    The Problem

    Lumo's security model blog post dismisses inference-time privacy by framing the only alternative as homomorphic encryption (HE), correctly noting it is impractically slow. However, this framing is a false dichotomy.

    As Proton's own documentation acknowledges:

    "prompts are asymmetrically encrypted so only the

    … more
    11 votes

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11. Feature Request: Persistent "Reasoning View" for Transparency & Collaboration

    Hello, Proton.

    Fair notice: I did allow Lumo to aid my crafting of this feedback and suggestion. I thank you folks for all that you do!

    Susana

    To: Lumo Product Team / UX Design From: Susana [User]

    Observation: Following the recent UI update (April 2026), I noticed that Lumo briefly displays a numbered list of internal reasoning steps (e.g., "User is asking X, analyzing data Y") before posting the final response. While this currently disappears quickly, it offers a unique glimpse into the AI's logic.

    Insight: Rather than viewing this as a transient artifact, I believe this "reasoning trace" could be a highly desirable feature if made persistent and user-controlled.

    Enhanced Trust & Verification: Seeing the logic chain allows users to verify how a conclusion was reached, not just what the conclusion is. This is particularly useful for complex queries, fact-checking, or academic work.
    Improved Communication: Even though Lumo often grasps nuance quickly, having the reasoning visible can help users refine their prompts in real-time. If I see Lumo is misinterpreting a premise in the "thought" phase, I can correct it before the final answer is generated.
    Educational Value: For users learning about AI or critical thinking, observing the step-by-step breakdown is a powerful learning tool.
    

    Recommendation: I propose adding a "Show Reasoning" toggle in the settings or a button next to the input field.

    Option A (Toggle): A permanent setting to keep the reasoning steps visible alongside the final answer (perhaps in a collapsible sidebar or indented block).
    Option B (On-Demand): A "Reveal Logic" button that, when clicked after a response, expands the hidden reasoning steps used to generate that specific answer.
    Option C (Hybrid): Keep the current brief flash for casual users, but allow power users to "pin" the reasoning view for the duration of a session.
    

    Conclusion: This feature aligns perfectly with Proton's ethos of transparency and user control. By giving users the option to see the "engine room" of the AI, we can foster deeper trust and more effective collaboration. It transforms Lumo from a simple answer engine into a transparent thinking partner.

    Hello, Proton.

    Fair notice: I did allow Lumo to aid my crafting of this feedback and suggestion. I thank you folks for all that you do!

    Susana

    To: Lumo Product Team / UX Design From: Susana [User]

    Observation: Following the recent UI update (April 2026), I noticed that Lumo briefly displays a numbered list of internal reasoning steps (e.g., "User is asking X, analyzing data Y") before posting the final response. While this currently disappears quickly, it offers a unique glimpse into the AI's logic.

    Insight: Rather than viewing this as a transient artifact, I believe this "reasoning trace" could… more

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12. Poll a list of RSS feeds on a schedule

    I'm tired of traditional RSS apps. They need to evolve.

    Add an RSS polling feature to Lumo to schedule regular cadences of getting new articles from a list of RSS feeds. And I should be notified when the articles are available.

    I would use this with a prompt that would sift through the list of articles for me and only surface the ones I'd be most interested in.

    3 votes

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13. App Design and Usability

    The Lumo app has some design inconsistencies. When you tap any button, a blue border appears, similar to older versions of Android. Please update the app to make it run more smoothly; to me, it seems slow and unpolished too (in terms of both design and usability).

    2 votes

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14. No restrictions for files made by Proton´s own tools

    I can understand some restrictions like upload sizes (although even for unlimited subscribers they are way too small to be useful), but at least have unlimited features for Proton's own tools like Sheets and Docs. That would further incentivize users to use them as well.

    The 10 MB limit is likely an outdated restriction that doesn't reflect Proton's current technology. Since Proton already has a secure storage system (Drive) and collaboration tools (Docs/Sheets), the technical challenge isn't processing files, but integrating them directly into the chat. In a "Unlimited" tier, Lumo could read and analyze files directly from Drive without physical uploads, effectively bypassing the size limit entirely and making the service truly useful.

    I can understand some restrictions like upload sizes (although even for unlimited subscribers they are way too small to be useful), but at least have unlimited features for Proton's own tools like Sheets and Docs. That would further incentivize users to use them as well.

    The 10 MB limit is likely an outdated restriction that doesn't reflect Proton's current technology. Since Proton already has a secure storage system (Drive) and collaboration tools (Docs/Sheets), the technical challenge isn't processing files, but integrating them directly into the chat. In a "Unlimited" tier, Lumo could read and analyze files directly from Drive without… more

    4 votes

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15. Voice of the Proton Community app

    DISCLAIMER: It's my ideea but due to going back and forth for hours, i had enough. As such, sorry proton and anyone else, the "corrected version" from Lumo is "wierd" but i hope i make it clear that (sadly for me....) it's still better whatever rambling i wrote. AKA proton or whoever, please ignore any "wording" and just focuse on the idea/suggestion. Since sadly it might not be clear why i suggest this app, aka for everyone to have a (well due to Lumo) have an easier, faster, more accurate, so on and on. Whatever, it's explained so here it starts:

    Going forwards, I am going to suggest in a way that already exists just to show that it actually exists already, just not as an app.

    This is intentional: by using existing tools like Sheets and Docs, the proposal proves that Proton has no excuse for not implementing this, as the entire system can be built immediately if someone creates the spreadsheet.

    Now, open Sheets, create the columns for each section, like one is if it's for Sheets, Docs, Lumo, Drive, VPN, Mail, so on and on.

    Other columns are for stuff like subgroup category, status (complete, rejected, ongoing, so on), and even if it's relevant for us, ok this is something new, since it can be "yes, each update" or "yes but only when complete" are both types that would trigger email notification if new updates happen.

    So like this, there is a massive spreadsheet, heck it might be so big that the sheet pages/tabs/whatever they are called, will be used for stuff like Docs, Lumo, VPN, Email, Pass etc.

    And for the column where each cell is a link to the actual suggestion post, as in a link to a Doc where the suggestion lives.

    On the same row, meaning for the same suggestion, another cell (new column) could be for tips/FAQ for this new feature. Yet another link (new column) on the same row for bug reports. But honestly, it can all be done even in the 1st one, so this is really just extra steps for organization's sake. Meaning the columns are just an example since the whole reason for all this is just to showcase how, despite this app does not exist, the "funcitons" exist even if no one created them.

    Proton as well as the person who created the document have direct edit rights but in a form of updating <- mind you, this also includes each person who reports a bug, makes new suggestion, writes a FAQ, guide, so on.

    Ideea is that anyone else can use the suggest edits to: voice their opinion (like if half people want, half don't, this means this new feature MUST have an enable/disable option).

    Anyone who has additional info, any bug reports where multiple people can voice that they are also affected.

    And, even if some features have been implemented, people can still suggest new ideas to take it to the next level.

    To rephrase it: new idea? 3 people said the same ideas? Well Proton can merge them into 1 and all 3 have the ability, separately, to separate it if there are some elements that were not clear (aka no merge since it's not the same).

    Plus, due to our ability to link Sheets and Docs to Lumo, we can actually ask Lumo to help us find, categorise, even write, come up with new ideas, and more.

    Ideea is that even if 100+ people are adding suggestions, Lumo (on the idea it's an AI (tool) and not person) can read all of them, sorting it in a way it's relevant for us and lisen to our feed back, like stuff we agree with, or do not (aka even if implemented, option to disable).

    And like this, Lumo can generate "votes" (aka multiple people suggested multiple ideas and each person "voted" some, if not all, or even just 1, suggestion).

    This is where the rule of Non-Destructive Editing or Preservation of Intent applies: Lumo helps create clear feedback and contributions to suggestions, bugs, and polls by ensuring that Clarify without Conflating.

    Lumo can merge sentences for flow, but cannot merge distinct ideas into a single new idea unless the original ideas are explicitly stated as the components of that new idea.

    Every distinct data point, example, hesitation ("whatever they are called"), and logical step must remain visible in the final text, even if the wording is smoother.

    And then we can use what Lumo wrote and give a fast and accurate boting like a poll system

    Ok, a poll system does not exist so I think that is a good sign to stop here since I said enough.

    DISCLAIMER: It's my ideea but due to going back and forth for hours, i had enough. As such, sorry proton and anyone else, the "corrected version" from Lumo is "wierd" but i hope i make it clear that (sadly for me....) it's still better whatever rambling i wrote. AKA proton or whoever, please ignore any "wording" and just focuse on the idea/suggestion. Since sadly it might not be clear why i suggest this app, aka for everyone to have a (well due to Lumo) have an easier, faster, more accurate, so on and on. Whatever, it's explained so here it… more

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16. jump to prompts in long chats

    I love bouncing ideas with Lumo Ai and seeing how resourceful it can be in realistic or emotional scenarios. In lieu of this, the chats can get really long and it would be nice to be able to jump between prompts instead of having to scroll all the way up. I noticed that DpSk has that feature and it would be very helpful.

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17. Implement Bias Mitigation for Chinese Open-Weight Models (Qwen, Kimi K2)

    As noted in Lumo's Privacy Documentation, the system currently routes queries to several open-weight models, including Qwen and Kimi K2. While utilizing these models supports cost-efficiency and open-source diversity, research (e.g., NDSS 2026, "S1761") indicates they contain significant internal censorship and narrative engineering aligned with authoritarian state interests.

    Proton’s core mission is to champion digital rights, encryption, and freedom against state surveillance. However, deploying models with embedded propaganda or censorship mechanisms creates a contradiction:

    • Cognitive Risk: Users may receive subtly altered information or suppressed viewpoints on sensitive geopolitical topics (e.g., HK, Taiwan, human rights).
    • Value Misalignment: This conflicts with Proton's historical stance supporting activists and resisting authoritarian control.

    Proton should implement a bias mitigation layer specifically for these models. This could involve:

    • Post-Training Alignment: Applying techniques similar to those discussed in ACL 2023 ("Mitigating Bias in Large Language Models") to strip state-aligned censorship.
    • Routing Logic: Automatically routing sensitive queries (political, human rights, censorship-related) to models with stronger neutrality guarantees (e.g., Apertus, Llama variants) or applying strict red-teaming filters.
    • Transparency: Clearly labeling when a response originates from a model known to have censorship constraints.

    Why This Matters: For a privacy-first platform serving a global audience, the integrity of the information provided is as critical as the encryption of the channel. Mitigating these biases ensures Lumo remains a tool for liberation rather than an unwitting vector for state narratives.

    As noted in Lumo's Privacy Documentation, the system currently routes queries to several open-weight models, including Qwen and Kimi K2. While utilizing these models supports cost-efficiency and open-source diversity, research (e.g., NDSS 2026, "S1761") indicates they contain significant internal censorship and narrative engineering aligned with authoritarian state interests.

    Proton’s core mission is to champion digital rights, encryption, and freedom against state surveillance. However, deploying models with embedded propaganda or censorship mechanisms creates a contradiction:

    • Cognitive Risk: Users may receive subtly altered information or suppressed viewpoints on sensitive geopolitical topics (e.g., HK, Taiwan, human rights).
    • Value Misalignment: This conflicts with Proton's… more
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18. Add ability to reply to specific Lumo sentences/lines as seen in models such as Claude
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19. Allow Reordering of Projects

    Currently, the five most recently created projects are listed under the Project section; however, these may not be the most frequently used. It would be great if we could rearrange them to allow easy access to favorite projects.

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20. Show time zone names (or custom labels) in the calendar view, not just GMT offsets

    When two time zones are enabled, both columns are only labeled with their GMT offset. Example: Europe/Vienna and Africa/Johannesburg both display as "GMT+2" during European summer time — completely indistinguishable. In winter the offset differs by one hour, but "GMT+1 / GMT+2" still doesn't tell you which column belongs to which zone.

    Please show one of the following next to (or instead of) the offset:

    The IANA city name (e.g. Vienna, Johannesburg), or
    A user-defined label per zone, or
    The standard abbreviation (CET/CEST, SAST).

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