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Hushh
AI baby cry analyzer that runs entirely on your device
Hushh is a privacy-first AI baby cry analyzer that runs entirely on your device. Using on-device AI, it analyzes baby cries directly in your browser - no cloud uploads, no server-side processing. Install it as a PWA and explore how modern browser AI can help parents while keeping sensitive audio private.
Hushh – An AI-powered baby cry analyzer that runs entirely on your device 👶🔒
Hi everyone! 👋
A few days ago, while waiting to pick up my daughter from summer school, I noticed a mother trying everything she could to calm her crying baby. It reminded me of when my daughter was an infant.
Every parent knows this game:
* Is the baby hungry? * Tired? * Needs a diaper change? * Feeling uncomfortable? * Or... something else entirely?
Unless babies could talk, we're all just making educated guesses.
That moment made me wonder:
With today's on-device AI models, could we build an app that listens to a baby's cry and suggests the most likely reason?
The privacy requirement immediately became my top priority.
I didn't want parents uploading recordings of their babies to a cloud server. Sensitive data like a baby's voice should stay on the family's own device whenever possible.
So I built Hushh.
## What is Hushh?
Hushh is an experimental Progressive Web App (PWA) that analyzes baby crying sounds using AI entirely on-device.
That means:
✅ No audio leaves your device
✅ No server-side inference
✅ Works directly in your browser
✅ Privacy-first by design
## Why a PWA?
I wanted something parents could open instantly without installing a native app.
Modern browsers are becoming surprisingly powerful, and on-device AI is opening exciting possibilities for privacy-preserving applications.
Hushh is also an experiment to see how far we can push AI inside a browser.
## Tech highlights
* Progressive Web App (PWA) * On-device AI inference * Privacy-first architecture * No cloud processing for baby audio * Runs locally in the browser
## This is still an experiment
I don't claim that Hushh can replace parental judgment or medical advice.
The goal is to explore whether on-device AI can become a helpful assistant for parents - not a decision maker.
I'd love feedback on:
* Accuracy * UX * Performance * Device compatibility * Ideas for future features
If you're a parent, an AI enthusiast, or someone interested in privacy-preserving machine learning, I'd really appreciate your thoughts.
Thanks for checking it out! ❤️
About Hushh on Product Hunt
“AI baby cry analyzer that runs entirely on your device”
Hushh was submitted on Product Hunt and earned 3 upvotes and 5 comments, placing #111 on the daily leaderboard. Hushh is a privacy-first AI baby cry analyzer that runs entirely on your device. Using on-device AI, it analyzes baby cries directly in your browser - no cloud uploads, no server-side processing. Install it as a PWA and explore how modern browser AI can help parents while keeping sensitive audio private.
On the analytics side, Hushh competes within Parenting, Privacy, Artificial Intelligence and GitHub — topics that collectively have 532.8k followers on Product Hunt. The dashboard above tracks how Hushh performed against the three products that launched closest to it on the same day.
Who hunted Hushh?
Hushh was hunted by Nhat Nguyen. 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 Hushh including community comment highlights and product details, visit the product overview.
Nhat Nguyen
Hushh – An AI-powered baby cry analyzer that runs entirely on your device 👶🔒
Hi everyone! 👋
A few days ago, while waiting to pick up my daughter from summer school, I noticed a mother trying everything she could to calm her crying baby. It reminded me of when my daughter was an infant.
Every parent knows this game:
* Is the baby hungry?
* Tired?
* Needs a diaper change?
* Feeling uncomfortable?
* Or... something else entirely?
Unless babies could talk, we're all just making educated guesses.
That moment made me wonder:
With today's on-device AI models, could we build an app that listens to a baby's cry and suggests the most likely reason?
The privacy requirement immediately became my top priority.
I didn't want parents uploading recordings of their babies to a cloud server. Sensitive data like a baby's voice should stay on the family's own device whenever possible.
So I built Hushh.
## What is Hushh?
Hushh is an experimental Progressive Web App (PWA) that analyzes baby crying sounds using AI entirely on-device.
That means:
✅ No audio leaves your device
✅ No server-side inference
✅ Works directly in your browser
✅ Privacy-first by design
## Why a PWA?
I wanted something parents could open instantly without installing a native app.
Modern browsers are becoming surprisingly powerful, and on-device AI is opening exciting possibilities for privacy-preserving applications.
Hushh is also an experiment to see how far we can push AI inside a browser.
## Tech highlights
* Progressive Web App (PWA)
* On-device AI inference
* Privacy-first architecture
* No cloud processing for baby audio
* Runs locally in the browser
## This is still an experiment
I don't claim that Hushh can replace parental judgment or medical advice.
The goal is to explore whether on-device AI can become a helpful assistant for parents - not a decision maker.
I'd love feedback on:
* Accuracy
* UX
* Performance
* Device compatibility
* Ideas for future features
## Try it
🌐 Live Demo:
https://tryhushh.vercel.app/
💻 GitHub:
https://github.com/nhatnx/hushh
If you're a parent, an AI enthusiast, or someone interested in privacy-preserving machine learning, I'd really appreciate your thoughts.
Thanks for checking it out! ❤️