threadfork - A private second brain for your meetings
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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.
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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.
Replies
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.