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I built a toy that plays grandma's stories when my daughter hugs it

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I built a toy that plays grandma's stories when my daughter hugs it

This was a project I built for my daughter's first birthday present. For context, I'm a surgical resident in the UK by background and am currently taking a year out of training to study a masters in computer science. My daughter just turned one. There are two things she really loves: the first is particular soft toy that she just can't live without, and the other is a good story book. Her grandparents live hours away and I didn't want her to forget what they sound like between visits. I wanted her to hear them whenever she missed them. My parents brought my brother and I up with incredible stories and books from all sorts of cultures, many of the stories being passed down from their parents before them. I didn't want my daughter to miss out on that. Finally, I was sick of missing storytime with her when I had to leave for night shifts. I wanted her to hear my voice before she slept every night. For all these reasons, I decided to build Storyfriend. It's her favourite soft toy with a custom made speaker-module inside. I combined my surgical skills with the skills I was learning as a CS student. Along the way I dipped my toes into the world of 3D printing, CAD and electronics design. When she hugs the toy, it plays stories read by her grandparents. She can take the toy with her anywhere and hear the stories anytime she wants - it works offline and has internal storage. It meets my wife's strict no-screen rule (which is getting harder to stick to as the days go by). I've recorded some of the stories that we would read together, so that on nights when I'm working she still has me there to read her a bedtime story. The bit I'm most pleased with: grandparents don't need an app. They just call a phone number. The audio routes through my server and pushes to the toy over WiFi. My own 86-year old grandmother in a rural village in another country can do it by just making a regular call via her landline, as she has done for many years - no help needed, no apps required, no smartphones involved. Hardware is a BLE/wifi module with a MAX98357 chip and custome battery management system, all soldered together, placed in a 3D printed enclosure and placed into a compartment that I stitched into her cuddly toy. Firmware pulls new messages when connected to WiFi and stores them on an SD card. So far I've sold a few hand-made units to parents and grandparents who resonated with the project. Site: https://storyfriend.co.uk Would love feedback on the technical approach, the product itself, or anything else. Happy to answer questions about the build

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Indie HackersFits the IH revenue-focused audience · Strong signals: wife · Missing: supports, reddit linkedin, podcasting
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, computer, new · Missing: mac, agents, macos
71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio, smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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