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Remend is a consumer-first app for private, at-home movement practice on iPhone and iPad. It supports post-stroke recovery, Bell’s palsy, Parkinson’s, knee injuries, and shoulder, elbow, and hand mobility. On-device computer vision follows face, hand, upper- and lower-body exercises, calibrating progress to each person’s comfortable range. Optional local AI explains activity and organizes routines. Camera data stays on-device and isn’t stored by default. It does not replace professional care.
Hi Product Hunt
I’m Gage, the developer behind Remend.
I started building Remend because continuing physical rehabilitation can become difficult when appointments are limited by insurance, transportation, cost, or location. I wanted to explore whether the device people already carry could make regular movement practice easier to access at home.
Remend uses on-device computer vision to follow exercises involving the face, hands, upper body, and lower body. Instead of measuring everyone against one universal ideal, it calibrates supported activities around the range each person can comfortably demonstrate.
Privacy shaped the technical approach from the beginning. Camera inference happens directly on the iPhone or iPad, and Remend does not store raw video, camera frames, or raw movement landmarks by default. Optional local AI can help explain personal activity and organize routines without sending that information to a remote model.
I started building Remend during OpenAI's Build Week event and is still an early beta and is not a replacement for physical therapy or medical care.
I’m interested in learning where the experience feels genuinely helpful, where it remains confusing, and what would make it more accessible.
You can try it free through TestFlight. I’d be grateful for any honest feedback or questions.
Remend was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #58 on the daily leaderboard. Remend is a consumer-first app for private, at-home movement practice on iPhone and iPad. It supports post-stroke recovery, Bell’s palsy, Parkinson’s, knee injuries, and shoulder, elbow, and hand mobility. On-device computer vision follows face, hand, upper- and lower-body exercises, calibrating progress to each person’s comfortable range. Optional local AI explains activity and organizes routines. Camera data stays on-device and isn’t stored by default. It does not replace professional care.
On the analytics side, Remend competes within Health & Fitness and Artificial Intelligence — topics that collectively have 558.9k followers on Product Hunt. The dashboard above tracks how Remend performed against the three products that launched closest to it on the same day.
Who hunted Remend?
Remend was hunted by GVK. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Remend including community comment highlights and product details, visit the product overview.
GVK