u/tremendousquotes

I’ve been building Humla, an open source (MIT) meeting-notes app for macOS — it records mic + system audio separately, transcribes, separates speakers, summarizes.

Last week I added chat over your own notes, and the app turned from useful, to insane value.

How it works:
- Notes get split into ~750-token chunks on paragraph breaks. Your typed notes, the transcript, and the summary are chunked separately, so each chunk never mixes context.

- Search runs keyword (SQLite FTS5) and semantic (embeddings) side by side, then merges the two ranked lists with Reciprocal Rank Fusion — chunks that score well on both signals float to the top.

- No vector database. Vectors live as blobs in the same SQLite file and cosine similarity is just brute-forced over the chunks in scope. For a few hundred meetings that’s plenty fast I think.

- Embeddings are cached per chunk by content hash, so editing one paragraph re-embeds one chunk instead of the whole note.

- You don’t pick an embedding model — it follows your chat provider (OpenAI, or Ollama if you want it fully local). No key configured? It quietly falls back to keyword-only rather than breaking.

- The chat is agentic — three tools (search_notes, get_note, list_notes), capped at 6 steps. local models needed some fine-tuning: they’ll retry a failed search forever unless you explicitly tell them to stop. Also, short tool descriptions definitely work better than detailed ones, small models argue with long instruction lists.

This also had to work for two different setups at once. Personal notes retrieve entirely on-device against local SQLite, but shared notes in a cloud team workspace get retrieved server-side. Same three tools, same citations, same “this note / this folder / everything” scope rules — but two completely separate places the search actually runs, and a hard guarantee that a query can never cross from one team’s notes into another’s.

Repo: https://github.com/michaelwilhelmsen/humla

If anyone has suggestions on how to improve the system, useful tool suggestion or especially how to deal with the UI, I’d be grateful! chat currently lives inside a single note, which makes cross-meeting questions feel undervalued, when it’s probably what users would use the most.

Humla is a meeting-notes app for macOS, inspired by the likes of Granola, Otter, Notion AI Meeting Summaries. You take freeform notes during your meeting; Humla records the audio, transcribes it, separates speakers, and creates AI summaries.

What separates this app from the others, is that it's completely open-source / free.

I only charge for an adjacent product - Humla Cloud, built on top of the open-source application.

Appreciate any activity on the product hunt listing :)

https://www.producthunt.com/products/humla

Notion ran me through the AI Meeting Notes flow, then dropped this at the upgrade step: $861.81 today, $1,200 a year after that. AI Meeting Notes is gated behind the Business plan.

Most of my meetings are in Norwegian, so I checked language coverage before paying for any of them. Granola is $14 per user per month and only supports a few languages. Norwegian was not one one of them. Otter, Fathom, Fireflies all wanted to send a "Notetaker" bot to join my calls as a participant.

I wanted something simpler and private. So I started building Humla. It's a Mac meeting recorder, MIT-licensed, code on GitHub. Still very much a work in progress.

Transcription runs locally with Whisper on Apple Silicon (one-time Whisper download from Hugging Face), or against OpenAI if you paste in your own API key. Each note has its own language. After every recording there's a short polish pass that catches mispronounced words and tidies the chunk boundaries, and on Norwegian that step does most of the cleanup where Whisper mishears a name or technical word.

Summaries work the same way: OpenAI through your key, or a local Ollama model.

Speakers get labelled after the meeting ends. That part still needs the most work. It works, but you'll see mislabels. Labels are editable, and if one person ends up split across two speakers you can merge them.

Humla doesn't join your meetings. It pulls system audio off your laptop, so the attendee list stays however many people you actually invited.

Notes live in SQLite and plain markdown on your machine.

Right now it's macOS only and single-user, with rough edges I'm working through as I use it daily. Feedback is welcome, contributors more so. There's a long backlog and the repo is MIT, so all PRs are welcome.

https://github.com/michaelwilhelmsen/humla/releases to download.