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OCR extracts business names, formation dates, and addresses from uploaded documents automatically. But users still need to trust what the system found before anything gets submitted.
We designed the confirmation flow around editable fields that surface extracted data clearly. Users review what the system found and correct where needed, rather than typing everything from scratch. The design choice was to make the AI output feel transparent and controllable.
The design choice was to make the AI output feel transparent and controllable. The result is a flow that reduces data entry to the minimum while keeping users fully in control of what gets submitted.
Great work!
Editable-by-default beats a blind accept/reject toggle here — it keeps the correction cost at one field when OCR gets a formation date wrong, instead of forcing a full manual re-entry the moment trust breaks on a single value.
Confirmation flows for OCR-extracted data are so easy to get wrong, either too much friction re-verifying everything or too little and errors slip through. Did you test how far you could push toward minimal review before people stopped trusting the auto-fill entirely?
The editable-fields approach is smart, letting people verify OCR output instead of trusting it blindly probably saves you a ton of support tickets down the line.
Looks good. I like the minimalist approach. Nice and clean.
This is great tho
Making AI output editable rather than just showing a result is such a smart trust-building move. Users feel in control instead of just hoping the system got it right.
The editable confirmation step does more than correct OCR errors. It creates an audit boundary between machine extraction and user intent. I’d surface confidence selectively by flagging uncertain fields instead of asking users to distrust every value equally. Strong product thinking.
Good work
Love this approach Making AI-generated data editable and transparent is such a smart UX decision. It reduces friction while still giving users full control. Really clean work!
The UX tension you've solved here is the right one. AI does the extraction but the user has to own what gets submitted, so locked read-only fields would create exactly the wrong feeling. Editable fields that surface the extracted value flip the dynamic from rubber-stamping to...
I like the clean interface + UX decision you made.
Goated work
One detail I would want in this review step is a link from each extracted value back to the source region. A wrong date can still look perfectly plausible in an editable field. Did you include a document crop or highlight beside the field, and how did you balance that extra context against keeping the form compact?
This is a smart UX pattern letting users review and edit AI-extracted data builds trust without adding extra friction.
Editable fields are the right call. OCR is never perfect, so letting people correct the extraction keeps trust instead of forcing a restart.
Nice Design
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Paws & Pour: 3D Interactive Booking for Experiential Cafés 🐾
Business Name: Paws & Pour Cat Café
Location: Kemang, South Jakarta
Archetype: Appointment-based Experiential Café
Realistic Problems:
The solo owner is drowning in WhatsApp DMs and playing "table tetris" every single day. Customers don't just want any table; they want to sit near specific resident cats (like Mochi or Pepper). Additionally, due to high demand, the café strictly caps visits at 30, 60, or 90-minute sessions. This causes endless back-and-forth messaging, manual double-booking errors, and frustrated walk-ins.
I transformed a chaotic, manual DM-based reservation process into a self-serve, mobile-optimized 3D map, allowing guests to independently secure their exact table, time slot, and preferred cat companion instantly.
Fixing the Front Door :
To turn an inbound inquiry into a confirmed booking with zero effort from the owner, I completely redesigned the customer-facing booking flow. Instead of a boring, standard form, I built an immersive 3D seating map where customers can:
- Pick Their Vibe: Visually explore the café layout and select a specific cozy corner. See where their favorite resident cats are currently hanging out on the map.
- Lock in the Rules: Select precise session lengths (30, 60, or 90 minutes) during the booking process, automatically setting expectations.
- Book Anywhere: Experience a flawless, fully mobile-optimized booking journey directly from their phone.
The Impact:
The owner’s manual work goes from hours of coordinating schedules, answering DMs, and managing table assignments to zero. The real-time admin portal automatically handles availability, updates the seating chart, and tracks guest sessions. The owner can finally focus on running the café and taking care of the cats instead of staring at a screen.
Lovable Public Link: https://paws-and-pour-cafe.lovable.app/
Social Post: Check on twitter!
#lovable #catcafe #cat #webdesign
3D interaction while booking looks great!
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