This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend I built EchoNote AI for my friend Anshumita Ray.
Anshumita records her college professor's lecture on her phone during class. She does this because she cannot catch everything in real time. Sometimes a side conversation distracts her. Sometimes she forgets an important word, or misses a whole part of the lesson. Later, she has to listen to hours of audio again just to write her notes.
EchoNote AI fixes this. She uploads her recording or records live in the browser. The app writes the full transcript, then makes a clean summary with key definitions and exam questions. If she forgot something, she can ask the AI a question about the lecture and get an answer based only on what the professor said.
It runs fully on a normal laptop. No API keys. No internet after setup. Her notes are stored in an encrypted local database on her own device.
100% Local CPU · No API Keys · AES-256 Encrypted · Offline-First
Watch Demo · ** Features** · ** Setup** · Deploy
EchoNote AI is a professional, Claude & NotebookLM-inspired audio intelligence studio that converts any recording into structured, encrypted notes — all running entirely on your own laptop CPU, with zero API keys and zero internet dependency after setup.
Designed for college students, school kids, teachers, working professionals, recipe keepers, and voice note creators.
Upload a lecture. EchoNote AI transcribes it, detects what it is, writes you a tailored summary with exam questions, and lets you chat with Gemma AI about its content — forever stored privately in your encrypted local database.
Watch EchoNote AI in action:
| Feature | Details |
|---|---|
| ⚡ Auto GPU / CPU Detection | Automatically uses the best |
Every important part is open source:
The app checks the hardware when it starts. It uses an NVIDIA GPU or Apple Metal if they exist, and falls back to CPU on any laptop with 4 GB RAM. I picked the small 1B model on purpose, because a student laptop must be able to run it.
It also detects the type of audio. A college lecture gets exam questions. A meeting gets action items. A recipe gets ingredients and steps.
Here is the thing. A closed API would have failed Anshumita in three ways.
Open weight models made all three possible. I chose a model small enough for her laptop, ran it myself, and changed how it writes notes for each type of audio. With a closed API I could not have done that for free.
Best Use of Gemma. EchoNote AI runs Gemma 3 1B locally on CPU. It writes all summaries and exam questions, and it powers the chatbot that answers from the lecture transcript.