Lens
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  • Year
    2026

    Role
    Product designer

    Team
    May Choy, Yutong Wang, Yichen Wang

    Type
    Mobile, B2C, Design Delivered

    Recognition
    FigBuild 2026 Hacker
    Lens is a mobile tool to help to amplify the sense of seeing in the conversations with loved ones. It uses audio analysis to understand Intimate Subtext Perception, the ability to sense the hidden meaning behind words. Not what was spoken, but what was meant.








    Target User
    People who deeply care about a relationship, whether romantic, friendship, or family, and find themselves lost not in what was said, but in what was meant. Problem
    The biggest damage in close relationships rarely comes from major conflicts. It comes from small misreadings that accumulate over time. 
    SolutionLens is a mobile app that uses audio analysis to understand Intimate Subtext Perception, the ability to sense the hidden meaning behind words. Not what was spoken, but what was meant. By listening to conversations with loved ones, Lens surfaces the emotional subtext beneath everyday language.   User ExperienceAfter a conversation, Lens presents the subtext it sensed as a set of interpretive lenses. Users can edit, remove, or rephrase any lens that doesn't feel right. The interpretation is always yours. AI surfaces what it heard between the lines, but you decide what stays.  Human  in  the loopAI surfaces the lenses it sensed, but you decide what stays. Edit, remove, or rephrase any lens that doesn't feel right. The interpretation is always yours.









    User Case 01_Family
    User Case 02_Friendship
    User Case 03_Partner










    In-Conversation Feature

    Ambient Sensing




    Sensing, Not Recording
    LENS doesn't record what you say.
    It senses how you say it:
    Vocal tone, speech rhythm, pauses, intensity, the moments of overlap and silence, and how many words it takes you to say one thing.


    Emotional  Presence
    While you talk, a softly morphing halo responds to the conversation, revealing the hidden emotional cues.






    Post-Conversation Feature

    Conversation Analysis




    The Lenses You Shared
    After every conversation, Lens surfaces the lenses that emerged between you: the topics, moments, and themes you both moved through together.


    More inside each Lense
    Tap into any lens to see how it unfolded: how often it appeared, what words each person used, and where your subtexts aligned or quietly diverged.






    Long-term Feature

    The Relationship Gallery




    Every Relationship is Visualized
    Over time, your conversations with each person form a cumulative lens: a living portrait of how you see the world together. No two relationships look the same.


    A Map of How You Connect
    The colors and shapes of each lens reflect the unique dynamic between you and that person. This is not a score, but a feeling made visible.









    Long-term Feature

    Relationship Monitor




    Every Relationship is Visualized
    Over time, your conversations with each person form a cumulative lens: a living portrait of how you see the world together. No two relationships look the same.


    A Map of How You Connect
    The colors and shapes of each lens reflect the unique dynamic between you and that person. This is not a score, but a feeling made visible.








    Pre-Conversation Safeguard

    Dual-consent Acoustic Sensing







    Tap to Connect
    Bring your phones together to begin. 
This shared physical gesture is the only way to start a session, making consent impossible to fake or bypass.


    Synced from the Start
    When both phones connect, your lenses sync. 
Lens begins sensing only when both people are ready.






    Pre-Conversation Safeguard

    Human confirmed Lenses







    Human in the Loop
    AI surfaces the lenses it sensed, but you decide what stays. 
Edit, remove, or rephrase any lens that doesn't feel right. The interpretation is always yours.


    Lenses you Both Own
    Every lens is shared. Not just sensed by one, but confirmed by both. What gets added, edited, or removed reflects a mutual understanding, not just one person's interpretation.










    Collaborated withMay Choy, Yutong Wang, Yichen WangRoleDesigner



    FigBuild 2026

          1:35:40 PM 
    © 2026
    Lilith Ren®