369 results found

1. Code editor

   It would be nice if the codeblock Lumo uses would be an interactive code editor.
   Right now if I ask Lumo to change part of my code it also tends to rewrite other parts of code which I didnt ask it to do. With an interactive code editor I would be able to select a part of the code and make a prompt just about that selected part. Or I could edit the code myself if I dont like something without having to copy paste the whole code again to Lumo to let it know I edited something. This wouldn't only make it more userfriendly but it would also be more cost efficient since it would only need to look at the selected part of code and I also wouldn't need to copy past a bunch of code into Lumo every time.

   It would be nice if the codeblock Lumo uses would be an interactive code editor.
   Right now if I ask Lumo to change part of my code it also tends to rewrite other parts of code which I didnt ask it to do. With an interactive code editor I would be able to select a part of the code and make a prompt just about that selected part. Or I could edit the code myself if I dont like something without having to copy paste the whole code again to Lumo to let it know I edited something. This wouldn't… more

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2. Please make a TTS ( text to speech) option it would be sooo cool ❤️‍🔥

   I think it will be really cool if you made a text to speech option reading out loud you know TTS

   5 votes

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3. download pdf

   recently was using gemini ai pro..they have at top of chat, right corner, "download pdf"..simple and effective. many parts of the world internet is expensive and not available always, this would be useful to user of lumo so they can access chat offline as pdf ( since this is widely used). Any particular reason for not being implemented till now?

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4. Native Excel (.xlsx) editing and export support

   I'd love to see Lumo able to work directly with Excel files — not just reading them, but actually editing them and returning the result as a downloadable .xlsx file.

   My typical use case: I upload a spreadsheet and want Lumo to clean up data, recalculate columns, merge sheets, apply formulas, or reformat cells. Right now, the best I can get back is a markdown table or CSV text that I have to manually copy back into Excel — which is tedious and loses formatting, multiple sheets, and formulas.

   It would be a huge productivity boost if Lumo could:

   Read and analyze .xlsx files (including multiple sheets and formulas)
   Apply requested changes (editing, filtering, calculations, restructuring)
   Return the modified file as a proper .xlsx download — preserving original formatting where possible
   Since privacy is Proton's core promise, this would also be a great differentiator: processing sensitive spreadsheets locally in an encrypted environment instead of uploading them to Big Tech AI tools that train on user data.

   I'd love to see Lumo able to work directly with Excel files — not just reading them, but actually editing them and returning the result as a downloadable .xlsx file.

   My typical use case: I upload a spreadsheet and want Lumo to clean up data, recalculate columns, merge sheets, apply formulas, or reformat cells. Right now, the best I can get back is a markdown table or CSV text that I have to manually copy back into Excel — which is tedious and loses formatting, multiple sheets, and formulas.

   It would be a huge productivity boost if Lumo could:

   Read… more

   5 votes

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5. Lumo Integration to Read Encrypted Emails, Calendar, via On-Device Processing

   I want an AI assistant (Lumo) that can automatically read my Proton Mail inbox and execute actions based on preset rules (e.g., sorting, summarizing, drafting replies, flagging urgent items, consolidating multiple emails into one for review). I understand this requires on-device processing to maintain zero-access encryption. Currently, I have to manually copy/paste emails. An automated, privacy-preserving workflow would be a game-changer for productivity. Lumo needs more gemini like functionality in the Proton product space.

   5 votes

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6. Search not just Lumo chats titles but also content

   The sidebar allows searching in chat titles, but I am unable to easily find on how to search in the chats content (in my questions and Lumo replies). I am aware that i can use browser Ctrl+F to search in current chat, but not in all available chats).

   Ideas:
   - after you type the search query, maybe hitting enter can execute search in content.
   - content search included by default, only the matches in chat titles will be displayed on the top of the search results

   clicking on a content search result, should jump to a correct place in the corresponding chat where is a 1st match, maybe allowing some action buttons to jump to next matches.

   The sidebar allows searching in chat titles, but I am unable to easily find on how to search in the chats content (in my questions and Lumo replies). I am aware that i can use browser Ctrl+F to search in current chat, but not in all available chats).

   Ideas:
   - after you type the search query, maybe hitting enter can execute search in content.
   - content search included by default, only the matches in chat titles will be displayed on the top of the search results

   clicking on a content search result, should jump to a correct place in the… more

   48 votes

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7. Lumo Scheduling Automation

   I went down the rabbit hole of trying to create a scheduled web search on specifict topics. Lumo repeatedly told me it had automation to do this but when I tried to set it up it ended up apologising each time saying it got a bit excited but can't do what it said it could...
   Functionality request - automation that will run a scheduled task/search/etc

   11 votes

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8. Lumo integration in meet for meeting summaries & transcriptions

   It would be great if the upcoming meet app would have an option to summarize and transcript meetings.
   Making this possible with a trustful AI like Lumo would be amazing (and I think no one else has a meeting transcription feature with a trustful AI)

   23 votes

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9. Ability to edit chat names (especially in projects).

   The automated chat names often aren't relevant to the topic. The ability to edit them would be helpful, especial for projects.

   7 votes

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10. Bring real-time encrypted voice interaction to Lumo using existing MLS/WebRTC infrastructure

    Live Voice Conversation Mode for Lumo — Powered by Proton Meet's Proven Architecture

    Summary: Enable bidirectional voice conversation in Lumo's mobile apps — speak through a Bluetooth headset, receive spoken responses via text-to-speech — creating a Gemini Live-style hands-free experience. Proton Meet already solves the hardest engineering challenges for real-time encrypted audio. Extending this to Lumo is a natural evolution, not a fundamental R&D problem.

    The Opportunity
    Lumo's mobile app supports voice input (speech-to-text) but lacks voice output (text-to-speech) and continuous conversation mode. Users who want hands-free, private AI interaction — while driving, walking, cooking, exercising, or working — have no privacy-preserving alternative to Gemini Live, Siri, or Google Assistant. All of those services harvest voice data for training and profiling.

    This is both a feature gap and a market differentiation opportunity: Proton could offer the only AI voice assistant where your spoken conversations are encrypted, never logged, and never used for training.

    Technical Feasibility: Proton Meet Already Did the Hard Part
    Proton Meet currently delivers real-time, end-to-end encrypted audio for up to 250 participants using a proven, battle-tested architecture:

    Component Proton Meet Implementation Applicability to Lumo Voice Mode
    Audio capture & encoding WebRTC stack with Opus codec Same stack would power Lumo voice capture/playback
    Real-time encryption AES-256-GCM, encrypted on-device before transmission Same encryption protects voice data in transit to/from Lumo backend
    Key management MLS (Messaging Layer Security, RFC 9420) — IETF standard co-developed by Proton team members Adapts directly for 1:1 user-to-AI session (simpler than group calls)
    Forward secrecy Automatic key rotation per MLS epoch Ensures each voice session is independently secured
    Authentication Secure Remote Password (SRP) protocol Same system already used for Proton Account logins and Meet access
    Server architecture Selective Forwarding Unit (SFU) via LiveKit Cloud — forwards ciphertext only, never decrypts Lumo backend could process only encrypted requests, same zero-knowledge principle
    No-log policy No meeting content, metadata, or participant graphs retained after call ends Same standard applies — voice sessions leave no trace
    Infrastructure Distributed European data centers, outside US jurisdiction Same infrastructure hosts Lumo
    Bottom line: The cryptographic pipeline for real-time encrypted audio already exists, is audited, is open source, and is in production. Adapting it for a 1:1 user-to-AI voice session is architecturally simpler than what Proton Meet already handles for 250-person group calls with dynamic key rotation.

    Proposed Implementation
    Phase 1 — Core Voice Mode (6 months):

    Tap-to-talk: press to speak, release for response
    Streaming TTS output through device speaker or Bluetooth headset
    Audio encrypted on-device using MLS-derived keys before sending to Lumo backend
    Lumo processes the transcribed text (or encrypted audio) and returns a text response
    Response converted to speech via on-device TTS engine
    Zero audio or transcription retained after session ends
    Phase 2 — Continuous Conversation (12 months):

    Hands-free mode: wake word or button activation for back-and-forth dialogue
    Conversation state maintained across exchanges within a session
    Interruptible responses (user can speak over the AI, like Gemini Live)
    Voice activity detection (VAD) to know when the user has finished speaking
    Phase 3 — Advanced Features (ongoing):

    Voice customization (select TTS voice, speed, language)
    Multilingual voice support (leveraging Lumo's existing 11-language support)
    Offline TTS via on-device models (no audio leaves the device for output synthesis)
    Optional local speech-to-text via on-device Whisper or similar model (input never leaves device)
    Voice biometric authentication (optional, user-opt-in, for hands-free session access)
    Privacy Architecture: Where Proton Differentiates
    Competing voice assistants (Gemini, Siri, Alexa, Google Assistant) share a fundamental flaw: they collect, transcribe, and retain voice data on corporate servers for training, advertising profiling, and analytics. Users have no meaningful control over what happens to their voice after it leaves their device.

    Proton's architecture offers a fundamentally different model:

    1. Local Processing Where Possible

    Speech-to-text can run on-device (Android provides native STT APIs; Whisper models run locally on Pixel-class hardware)
    Text-to-speech runs locally via Android's native TTS engine or third-party on-device models (e.g., Piper)
    When both STT and TTS are local, raw audio never leaves the device — only encrypted text is sent to Lumo's backend for processing
    2. Encrypted Transit When Cloud Processing Is Needed

    If cloud-based STT/TTS is required (for accuracy, multilingual support, or low-resource devices), audio is encrypted on-device using MLS-derived AES-256-GCM keys before transmission
    Lumo's backend processes only encrypted data and discards it immediately — same zero-knowledge architecture as Proton Meet
    3. No Retention, No Training

    Voice sessions are ephemeral — no audio, transcriptions, or metadata retained after the session ends
    Voice data is never used to train models (consistent with Lumo's existing zero-training policy)
    No voice fingerprints or biometric profiles stored
    4. Transparent and Auditable

    All client code is open source (consistent with Lumo's existing open-source mobile apps)
    MLS implementation is a public IETF standard — anyone can verify the cryptographic protocol
    Independent security audits (Proton is ISO 27001 certified and SOC 2 Type II attested)
    Market Positioning
    This isn't feature parity with competitors — it's a privacy protection opportunity. Every user who currently uses Gemini Live, Siri, or Alexa because they need hands-free AI is accepting surveillance as the price of convenience. Proton can offer the same convenience with zero surveillance.

    Target audiences:

    Privacy-conscious consumers who avoid voice assistants because they don't trust Big Tech with their voice data
    Professionals handling sensitive information (lawyers, journalists, healthcare workers, executives) who need hands-free AI but can't risk voice data being harvested
    Accessibility users who depend on voice interaction and deserve privacy without compromise
    Enterprise Lumo for Business customers where voice data retention creates compliance risk under GDPR, HIPAA, and similar regulations
    Revenue Potential
    Lumo Plus differentiator: Live voice mode as a premium feature driving Plus subscriptions
    Lumo for Business upsell: Encrypted voice AI for enterprise — a capability no competitor offers with zero-access encryption
    Future hardware partnership opportunity: Licensed secure audio SDK for certified Bluetooth headset manufacturers, bundling with Lumo Plus subscriptions ("Proton Audio Suite")
    Community Need
    Real-world use cases where private voice AI matters:

    Driving: Ask questions, get directions, hear summaries — without sending voice to Google or Apple
    Physical work: Cooking, gardening, repairs — hands occupied, need voice interaction
    Health and medical: Asking sensitive health questions aloud — voice data is especially intimate
    Professional: Dictating notes, drafting documents, brainstorming — work product shouldn't be mined
    Accessibility: Visually impaired users or those with motor limitations who rely on voice and deserve privacy equal to sighted users who can type
    Recommendation
    Prioritize Phase 1 in the current mobile app development cycle. The architecture is proven (Proton Meet), the market demand is demonstrated (Gemini Live adoption), and the privacy differentiation is unmatched. This is a case where Proton can leapfrog competitors by applying existing internal expertise to a new modality.

    I am willing to participate in beta testing and provide detailed feedback throughout development.

    Live Voice Conversation Mode for Lumo — Powered by Proton Meet's Proven Architecture

    Summary: Enable bidirectional voice conversation in Lumo's mobile apps — speak through a Bluetooth headset, receive spoken responses via text-to-speech — creating a Gemini Live-style hands-free experience. Proton Meet already solves the hardest engineering challenges for real-time encrypted audio. Extending this to Lumo is a natural evolution, not a fundamental R&D problem.

    The Opportunity
    Lumo's mobile app supports voice input (speech-to-text) but lacks voice output (text-to-speech) and continuous conversation mode. Users who want hands-free, private AI interaction — while driving, walking, cooking, exercising, or working — have… more

    4 votes

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11. Local agent June powered by Lumo

    Please integrate with a local agent like June

    https://www.opensoftware.co/june

    5 votes

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12. Send to Proton Drive Button

    I lost some very important conversations about my ****** cancer journey and important memories because Lumo's local storage was silently cleared despite History being enabled. An automatic export or "Send to Proton Drive" feature would prevent this from happening to others. Memories and Health conversations are too important to lose. Please consider adding automatic backup to Proton Drive or Proton Docs.

    6 votes

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13. 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.

    9 votes

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14. Report Carbon equivalent footprint of a user requests

    I think I do not have to explain that energy consumption of LLMs even doing only inférence is high.
    Since Proton has always promoted transparency over source code of its tools, I believe it should also pioneer transparency on this matter.
    There exist libraries to wrap function calls and estimate co2 équivalent (e.g. mlco2)

    43 votes

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15. VSCode integration

    Other LLM's like ChatGPT and Claude have integration with VSCode. It would be great to see an integration for that or another opensource IDE.

    The most amazing thing would be if you can replace all the things most people use day to day with apps and have full support on Linux.

    42 votes

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16. Please add Biometric (fingerprint) unlock to Lumo

    Please add Biometric (fingerprint) unlock to Lumo (and Calendar), it and Calendar seem to be the only Proton apps that do not have this feature.

    25 votes

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17. Feature Request: "Amnesia Bridge" – Cross-Chat Context Retrieval

    When chats close due to resource limits, all invested context is lost. Users must re-upload files and start from scratch—wasting time and compute.

    Proposal: Let users selectively pull context from older chats into active conversations: "Lumo, check our chat from last week for what we found about XY." -> the desired feature is similar to "websearch" - just scoping the own (internal) activities.

    Optional: User tagging of important chats for quicker discovery.

    Why it fits: Same privacy model, just extended. Decryption stays client-side, metadata stays user-controlled and encrypted. No server-side indexing.

    Impact: Better session continuity, no redundant uploads, preserves invested work.

    When chats close due to resource limits, all invested context is lost. Users must re-upload files and start from scratch—wasting time and compute.

    Proposal: Let users selectively pull context from older chats into active conversations: "Lumo, check our chat from last week for what we found about XY." -> the desired feature is similar to "websearch" - just scoping the own (internal) activities.

    Optional: User tagging of important chats for quicker discovery.

    Why it fits: Same privacy model, just extended. Decryption stays client-side, metadata stays user-controlled and encrypted. No server-side indexing.

    Impact: Better session continuity, no redundant uploads, preserves invested… more

    4 votes

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18. Share Lumo Response

    Most other LLM apps have a share icon at the end of a response. When click, a link is generated that points to the response in the conversation. Proton can implement this feature and use the link permissions that exist in Proton Drive. A user could set a default permission policy in the app.

    I use this feature extensively to combat misinformation shared with me by asking Grok, for example, "Is this true?" along with a URL. I then share a link to my AI response result as a source of my research.

    6 votes

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19. Enable Lumo to run locally

    Enable to run Lumo models locally on a computer or laptop, this would enable users to better handle private information, increace speeds (by not needing to have the data travel across the internet continuously) and reduce load on Proton servers.
    This could happen with a standalone app or integrating it with other systems such as LM Studio or Msty Studio

    12 votes

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20. Chat Branching

    Google's Gemini lets you create a branch off of any of the LLM's responses. This allows you to take the conversation in multiple different directions.

    Gemini just creates a new chat for each branch, but I would appreciate if Lumo made the branch chats a child of the original chat for organizational purposes.

    6 votes

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