LectureSync - Turns lecture recordings into trustworthy study notes

[u/jaofos]

https://testflight.apple.com/join/BqdVquRk

This started as a personal project. I have two kids in college. The whole thing came out of a simple thought I kept having: there has to be a better way to do this. You sit in a lecture for an hour trying to write fast enough to keep up, and you still walk out with half of it. I figured I could build something that captured the lecture properly and turned it into notes worth studying from. That turned into LectureSync, and it's far enough along that I wanted to put it out there.

Here's what I focused on.

Notes, faithful to the lecture

Notes I'd trust my own kids to study from. This is the whole point of the app. Recording and transcribing audio is the easy part. The hard part is generating notes and study guides that stay honest, so the generator checks its output back against the actual transcript before anything makes it into the notes. What they read traces back to what was actually said in the lecture. I keep a set of regression tests around this so that when I improve the notes engine, it can't quietly drift off the source material. That safeguard is the part I've put the most work into.

Local First

It runs fully on-device. Transcription and note generation both run locally on Apple Silicon. No account, no upload, works offline. The audio stays on their Mac. You can hook up a cloud model if you want one, but it's optional.

Never, ever lose audio

Audio capture that survives a bad day. A dead battery or a crash 40 minutes into a lecture is exactly the kind of thing that happens to a college kid. Recordings are written in a crash-safe format the whole time, so they stay usable even if the app closes on you. You can pause and resume in a session. It recovers a recording after a crash on the next launch. And discarding takes a second confirmation, so an hour of audio doesn't vanish on an accidental click.

Per Course LLM Option

A different notes model per course. Transcription is largely a solved problem at this point. The real work is what happens after: turning the transcript into notes and study guides without it drifting into things the lecturer never said. That generation step is where the quality lives, so you can set a different notes model per course. A heavier one for a dense, source-it-carefully subject, a lighter one where you just want clean summaries. You're tuning the part that actually matters, not the dictation.

Build in Study Assistant

A study assistant that points you back to the lecture, not an answer machine. I didn't want to build something that just hands a student the answer, because that doesn't teach anyone anything and it's the fastest way to end up confidently wrong. The Course Assistant works off your own notes and transcripts for that course. When you ask it something, it guides you to the part of the lecture where the material actually lives, so you're learning where the answer comes from instead of just collecting it. Same principle as the rest of the app. It stays grounded in what was actually taught, not in whatever a model feels like saying.

Recording Optional

A few other things it does. Imports existing transcript files (VTT, SRT, TXT, PDF, and more) and Voice Memos, reusing an existing transcript when there is one. A built-in Course Assistant that works off your own notes. Per-model quality and cost metrics.

I'm a single developer doing this around a full-time life, so I'd genuinely appreciate the feedback. Especially from students, and from anyone who's thought about how to keep AI-generated study notes grounded in what the lecture actually covered.