This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
threadfork is a private second brain for meetings, notes, memory, and follow-up. It records on your Mac, turns conversations into transcripts, summaries, decisions, action items, and entities, then keeps everything searchable later.
I first launched threadfork here about six months ago with a simple belief: your AI workspace should be private, local, and fully under your control.
Since then, the product has become much more focused.
threadfork is now a local-first AI workspace for meeting memory. It helps you record and transcribe conversations, import existing transcripts as Markdown files, search across your archive, and build a knowledge graph that connects people, projects, topics, decisions, and follow-ups over time.
A few things that make it different:
Local transcription using Whisper-based tooling
Markdown transcript import, so you can bring your existing meeting history with you
Search across transcripts and notes
A knowledge graph that turns isolated meetings into connected memory
A private-first approach, so your raw conversations are not treated like disposable cloud data
The larger idea is still the same as the first launch: conversations are where a lot of our best thinking happens. But meeting notes should not disappear after the summary is generated. They should become a memory layer you can search, connect, and build on.
Would love feedback from founders, consultants, operators, and anyone who lives in meetings and wants more control over their transcript archive.
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About threadfork on Product Hunt
“A private second brain for your meetings”
threadfork was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #107 on the daily leaderboard. threadfork is a private second brain for meetings, notes, memory, and follow-up. It records on your Mac, turns conversations into transcripts, summaries, decisions, action items, and entities, then keeps everything searchable later.
threadfork was featured in Productivity (650.7k followers), Notes (8.3k followers) and Privacy (11.1k followers) on Product Hunt. Together, these topics include over 139.3k products, making this a competitive space to launch in.
Who hunted threadfork?
threadfork was hunted by Sid Mohan. 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.
Want to see how threadfork stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Sid Mohan
Hey all! Sid again, founder of threadfork.
I first launched threadfork here about six months ago with a simple belief: your AI workspace should be private, local, and fully under your control.
Since then, the product has become much more focused.
threadfork is now a local-first AI workspace for meeting memory. It helps you record and transcribe conversations, import existing transcripts as Markdown files, search across your archive, and build a knowledge graph that connects people, projects, topics, decisions, and follow-ups over time.
A few things that make it different:
Local transcription using Whisper-based tooling
Markdown transcript import, so you can bring your existing meeting history with you
Search across transcripts and notes
A knowledge graph that turns isolated meetings into connected memory
A private-first approach, so your raw conversations are not treated like disposable cloud data
The larger idea is still the same as the first launch: conversations are where a lot of our best thinking happens. But meeting notes should not disappear after the summary is generated. They should become a memory layer you can search, connect, and build on.
Would love feedback from founders, consultants, operators, and anyone who lives in meetings and wants more control over their transcript archive.