145 results found

1. Provide a way to keep accounts completely disconnected from AI

   No AI, nor company that integrates it, truly cares about user privacy and security. Frankly it makes me reconsider my choice to move to Proton. It's certainly prevented me from moving to any paid tiers

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2. binary file type parsing

   According to Lumo, uploaded binary files are only read as a first snippled, and this is no different in the Lumo+ version. Hence, an Excel table or a pdf cannot be parsed or only the first few lines, rendering the function useless. Pls, parse full files. Output of Lumo:

   File‑type handling: I can read the first few lines of a text‑based file (CSV, plain‑text, JSON) that you upload, but I cannot open binary formats (PDF, DOCX, XLSX) or run arbitrary parsing libraries. Your annual‑report PDFs and the Excel workbook itself are binary; I can see the file name and a tiny preview of a CSV‑style export, but I cannot extract tables or numbers from them.

   According to Lumo, uploaded binary files are only read as a first snippled, and this is no different in the Lumo+ version. Hence, an Excel table or a pdf cannot be parsed or only the first few lines, rendering the function useless. Pls, parse full files. Output of Lumo:

   File‑type handling: I can read the first few lines of a text‑based file (CSV, plain‑text, JSON) that you upload, but I cannot open binary formats (PDF, DOCX, XLSX) or run arbitrary parsing libraries. Your annual‑report PDFs and the Excel workbook itself are binary; I can see the file name and a… more

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3. 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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4. 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).

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5. is LUMO sharing details with US Government on for US defence industry?

   is LUMO sharing details with US Government for US defence industry? If this is the case, we'll stop using it. See Anthropois canceling..and Chat GPT, X Grok, AWS and Meta complying to US Government requests. Had Proton been getting these requests and what were their response?

   2 votes

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6. is LUMO sharing details with US Government on for US defence industry?

   is LUMO sharing details with US Government on for US defence industry? If this is the case, we'll stop using it. See Anthropois canceling..and Chat GPT, X Grok, AWS and Meta complying

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7. Calendar Booking buffers

   Calendar Booking. I just found this feature on Proton and LOVE it I've been trying to use 3rd party booking tools. The enhancement it needs is to be able to set buffers before/after events on the calendar so they are not back to back. Other booking tools have this feature and found it very helpful.

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8. "Terse" mode or "conversational" mode

   I often don't need 3-page instructions and checklists on the topic I've asked a question about. For example, it recently gave me instructions on how to set up an email. It can be a bit overwhelming and difficult to go back to important information in the conversation.

   6 votes

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9. Link to Lumo app on a F-Droid, .apk (Github)

   Since Google Play is not private, it should not be a big deal for a privacy company (Proton) to publish link to a Lumo Android .apk and a Github repository at https://lumo.proton.me/download and at https://protonapps.com (if that is official source). Also I would welcome F-Droid link.

   There is a Github repo at https://github.com/ProtonLumo/android-lumo but the parent user shows no signs of validation as a official Proton AG account, despite Lumo claims there should be some check-mark on the user page.

   3 votes

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10. Responsive email templates

    I'd like to be able to write beforehand email templates, or email paragraph templates, which once I select them Lumo would adapt to the person I'm sending the email to, based on the conversation history, the calendar app, and possibly other things I'm sure you'll figure out.
    e.g. : I have an appointment confirmation template ; Lumo will automatically adapt the tone, gender, name, date, time, place, etc.

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11. Reorder favorite chats

    Favorite chats cannot be reordered currently

    6 votes

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12. delete button (outside of settings)

    Can you please move the delete button out of the settings and into the sidebar, or somewhere? I know lots of people keep AI chats, I don't. It seems like extra steps to hide it in settings.

    2 votes

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13. First reply is occasionally given with no words

    I find on a fairly frequent reoccurrance that when I ask Lumo a question, it simply spits sources back at me with no words to explain the answer. I have to follow up with a "Please expand" reply in order for it to finally give me an answer. It's not the worst thing, but a little annoying

    5 votes

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14. Allow pasting underscores

    I want to paste a regex .*_([^_]+_[^_]+)$ into chat. As soon as I paste, the underscores are removed and my text is converted to italic. I am unable to create a fenced code block with triple backticks. If I create a code block with single backticks and then paste my regex inside, it breaks the code block in half and inserts non-code text.

    • If the chat box is going to magically remove characters, CTRL+Z should put them back
    • I should be able to create a code block, and paste text inside that code block without any magic
    6 votes

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15. STT voice transcription run on-device, not sent to Google.

    STT voice transcription run on-device, not sent to Google.

    4 votes

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16. proton needs to collab with greenpt

    proton needs to collab with greenpt.ai to make there AI more sustainable (there AI work now better then lumo)

    3 votes

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17. Great Potential the ability to use both Scribe & Lumo together, dream come true!

    I started with this in Scribe then copy & paste to Lumo Web Search & got the results further from Lumo.

    I’m happy to dive into the world of AI‑powered license‑plate readers (LPRs) and give you a clear picture of what’s possible, where the technology shines, and what you should keep in mind before using—or even just exploring—such tools.

    How modern AI‑based LPRs work
    Image capture – A camera (often a dash cam, security cam, or a handheld device) records video or still frames of vehicles. Many systems use infrared illumination to see plates in low‑light or nighttime conditions.
    Pre‑processing – The raw image is cleaned up: contrast is boosted, noise is reduced, and the region that likely contains a plate is isolated.
    Plate detection – A convolutional neural network (CNN) scans the frame for the rectangular shape and reflective characteristics of a license plate. This step narrows the field to a small crop of the image.
    Character segmentation & recognition – Another neural model (often an OCR‑style architecture such as a CRNN) splits the cropped plate into individual characters and translates them into alphanumeric text. Modern models can handle variations in fonts, angles, and partial occlusions.
    Post‑processing – The raw string is cleaned up using country‑specific rules (e.g., known patterns for state or regional codes) and sometimes cross‑checked against a database of known plates for faster lookup.
    Because each stage is driven by deep learning, the overall pipeline can achieve 95 %+ accuracy under good lighting and a clear view, and many commercial solutions claim respectable performance even in challenging conditions (glare, motion blur, night).

    Where the technology really shines
    Parking‑lot management – Automated entry/exit logging, fee calculation, and spot‑finding.
    Toll collection – Seamless billing without requiring RFID tags.
    Law‑enforcement & traffic monitoring – Detecting stolen or wanted vehicles, identifying violators of red‑light cameras, or tracking traffic flow for city planning.
    Private‑property security – Gated communities or corporate campuses can log visitor plates automatically.
    In all these cases the AI reduces manual labor, speeds up data capture, and improves record‑keeping consistency.

    Practical considerations before you dive in
    Factor Why it matters Typical mitigation
    Lighting & weather Glare, rain, snow, or darkness can degrade image quality. Use infrared LEDs, weather‑sealed housings, and cameras with high dynamic range.
    Angle & distance Extreme tilt or long range makes character segmentation harder. Mount cameras at optimal height (≈3–4 ft for dash cams) and keep the focal length moderate; consider multiple viewpoints.
    Plate variability Different jurisdictions use distinct fonts, colors, and layouts. Train or fine‑tune models on local plate datasets; incorporate country‑specific regex filters.
    Processing latency Real‑time alerts require fast inference. Deploy edge devices (NVIDIA Jetson, Coral TPU) that run the model locally, avoiding cloud round‑trips.
    Data storage & retention Storing raw footage plus recognized strings raises privacy concerns. Encrypt data at rest, limit retention periods, and purge images once the plate is logged (unless legally required otherwise).
    Legal & ethical landscape
    License‑plate reading sits at the intersection of public safety and privacy. Regulations differ widely:

    United States – Some states treat LPR data as “personal information” subject to data‑protection statutes; others allow broader use for law‑enforcement. Many municipalities require signage indicating that LPRs are in operation.
    European Union – GDPR classifies a vehicle’s registration number as personal data. You need a lawful basis (e.g., legitimate interest for security) and must be transparent about collection, storage, and sharing.
    Other regions – Local traffic or privacy laws may impose additional constraints, especially concerning cross‑border data transfers.
    Before deploying any LPR system, it’s wise to:

    Check local statutes – Look up whether your jurisdiction requires consent, signage, or permits.
    Define a clear purpose – Document why you’re collecting plates (e.g., security vs. revenue) and stick to that scope.
    Implement safeguards – Access controls, audit logs, and regular privacy impact assessments help demonstrate compliance.
    Choosing a solution
    If you’re just experimenting, a few off‑the‑shelf options can get you started quickly:

    Open‑source kits – Projects like OpenALPR (now part of Rekor Systems) provide a community edition that runs on a Raspberry Pi or similar hardware.
    Commercial SDKs – Companies such as Plate Recognizer, Sighthound, and Anyline sell APIs that handle the heavy lifting (cloud or edge). They usually offer free trial tiers for limited daily reads.
    DIY with deep‑learning frameworks – If you enjoy building the pipeline yourself, you can train a YOLO‑v5 model for plate detection and pair it with a CRNN for OCR. TensorFlow Lite or ONNX Runtime can then run the model on embedded devices.
    When evaluating, compare:

    Accuracy claims (especially under low‑light or angled shots)
    Latency (does it meet real‑time needs?)
    Pricing model (per‑read, subscription, or one‑off license)
    Privacy features (on‑device processing, data‑deletion options)
    Bottom line
    AI‑driven license‑plate readers are powerful tools that can automate many mundane or safety‑critical tasks. Their effectiveness hinges on good hardware placement, robust model training, and a solid grasp of the legal framework governing personal data. If you decide to move forward, start with a modest pilot—perhaps a single camera in a controlled environment—to gauge accuracy, tune the model for your local plates, and verify that your data‑handling practices align with applicable privacy regulations.

    Let me know if you’d like deeper technical guidance (e.g., sample code for an edge deployment) or help navigating the regulatory requirements for a specific country or state. I’m here to help you build a responsible, effective solution.

    I started with this in Scribe then copy & paste to Lumo Web Search & got the results further from Lumo.

    I’m happy to dive into the world of AI‑powered license‑plate readers (LPRs) and give you a clear picture of what’s possible, where the technology shines, and what you should keep in mind before using—or even just exploring—such tools.

    How modern AI‑based LPRs work
    Image capture – A camera (often a dash cam, security cam, or a handheld device) records video or still frames of vehicles. Many systems use infrared illumination to see plates in low‑light or nighttime conditions.
    Pre‑processing… more

    3 votes

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18. Sometimes Lumo creates tables with columns which are too small making the table hard to read. Is an adjustable ui possible?
    4 votes

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19. Make it easier to navigate. I have quite some open queries that I go back to and at least on firefox it is very hard to find the slider

    The slider on the side is really hard to find when you have a long query. But I would like to go up and down to see earlier answers and it is really hard to do. Not even the middle button (roll) on the mouse works to go up and down.

    5 votes

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20. Please make the "ask anything" section shrink down after a user presses "send". Very good AI responses so far though, thanks!
    6 votes

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