Every meeting starts with re-explaining the last meeting. Action items get sent in a Slack message that scrolls away. By Friday, half are forgotten. By next quarter, the meeting might as well not have happened.
Meetings work. The thread between them doesn't. We didn't build another notetaker — we built the part teams keep forgetting they need: the bridge from this meeting to the next one. Some people will call this AI meeting notes. We call it team memory.
The notes live in someone's head, not in the archive. Action items live in chat, not in a system that surfaces them when their context returns. The transcript exists somewhere — Otter, Zoom, the Notion page nobody reopens — but it's archive-shaped, not memory-shaped.
The instinct is to optimize the meeting itself: better agendas, better templates, better notetakers. But the meeting isn't where the loss happens. The loss happens in the seven days between meetings, when the action item drifts out of someone's tab pile, the decision fades from the room's collective memory, and the next call has to start from "remind me where we left off."
The unit of work isn't the meeting. It's the thread between meetings. And no notetaker on the market is shaped like a thread.
AI captures the conversation while it happens — voice transcribed, structured by speaker. After the call, AI Transforms extracts agenda, decisions, action items, and owners. You edit, confirm, and move on. Listening and writing stop competing for the same attention.
Then the threading begins. Action items link to your decision log and surface in their owner's home view. Decisions link to the project they belong to. Recurring meetings link to their prior counterparts. When the next call opens, last meeting's outcomes are already loaded — no one has to re-explain anything.
We don't call this AI meeting notes. We call it the memory layer the team didn't have.
The meeting that picks up where the last one left off.
Three meetings most teams know by heart. Pick one — the archive lights up the part of itself it would actually use. No live data, no signup; the moves are real, the notes are illustrative.
Voice transcribes both speakers — what you raised, what your manager replied. Eyes up, not in a notebook.
After the call, AI extracts your topics, the feedback, and any commitments — labeled by speaker, edited in twenty seconds.
Last 1:1's open thread surfaces — the growth conversation isn't restarted, it's continued.
Both of you open the next 1:1 with the same context loaded. No one re-explains last month.
Most apps optimize for one of the four. We built for the loop — because the loop is what the team forgets.
A meeting note isn't a transcript and isn't a checklist — it's the bridge between two conversations. Here's which features carry which part of the bridge, mapped to the elements on the periodic table at /features.
Get the conversation out of the room and into a structured note — without anyone typing during the call.
Real-time transcription, structured by speaker.
An assistant's chat about the meeting, saved as a real entry.
Paste a Loom or call recording link — source attached, transcript ingested.
The transcript becomes a meeting note: agenda, decisions, action items, owners — extracted, not typed.
Agenda, decisions, action items, owners — pulled from the transcript.
Every meeting links to its project, decisions, attendees — both directions.
Recurring meetings rise; one-off threads stop drowning out the load-bearing ones.
Action items flow to the decision log, owners' home views, and the project. The meeting stops being an island.
Past decisions surface alongside the new one — precedents do the talking.
"We discussed this in February" surfaces unprompted, with a link.
Meetings within a project form a sub-graph you can actually look at.
Next meeting opens with prior outcomes loaded. New joiners get one URL. Claude reads the archive between sessions.
Find any decision in any meeting — keyword and meaning together.
Claude reads your meeting archive between sessions — natively.
A new joiner reads the project in one URL — public, private, or workspace-only.
The meeting note arrived as a formal artifact in the nineteenth century. The thread between meetings — the part teams forget — has been left to memory ever since. Knovya is the latest answer to a very old question: how does a meeting matter a week later?
A US Army engineer codifies parliamentary procedure into a single book. For the first time, a meeting has a shape — motion, second, debate, vote — and a written record (the minutes) becomes the proof that it happened.
Boards adopt Robert's format; corporate law starts to require it. A secretary types, distributes, files. The meeting becomes a paper trail. The thread between meetings still lives in someone's head.
Meeting notes become searchable, cross-linkable, owned by the team rather than the secretary. Templates appear. But someone still has to write the page — and most pages are written, then never reopened.
Real-time speech-to-text becomes cheap and ambient. Suddenly every meeting has a transcript by default. The new problem: a transcript isn't a meeting note. The structure is still missing.
LLMs make extraction trivial: agenda, decisions, action items, owners — pulled from the transcript automatically. Beautiful summaries, every time. The new problem, quietly: each meeting is still an island. The thread is still on you.
Capture is solved. Structure is solved. Knovya bets the next move: meetings linked into the work. Action items thread to the decision log. Recurring meetings open with their prior outcomes loaded. MCP exposes the whole archive to Claude, Cursor, and ChatGPT. The thread between meetings, finally something the team doesn't have to remember.
Every app in this category wagered on a piece of the meeting workflow. The honest comparison isn't features. It's which move each one decided to be best at, and which it left to you — and to last week's tab pile.
The bet The transcript is the artifact. Speech-to-text in real time, captioned, searchable. If a meeting happened, Otter can give you back the words.
What's left to you Structure and threading. A transcript isn't a meeting note. What gets decided, who owns what, where it goes next — all that work is still on you, after the call.
The bet The template is the discipline. Pre-built agendas for 1:1s, retros, performance reviews, kickoffs. If your team will follow a script, Fellow holds the script.
What's left to you Capture and recall. The template assumes someone is typing during the call. The archive doesn't surface last quarter's similar meeting on its own.
The bet The summary is the deliverable. Quiet AI in the background of the call, beautiful extracted notes after — agenda, decisions, action items, owners. Polished surface.
What's left to you The thread. Each meeting is a polished island. Action items don't flow into a decision log; recurring meetings don't open with their prior outcomes loaded.
The bet Meeting notes as a row. A schema-shaped page in a database, with templates, views, and properties. Structure for those willing to model it.
What's left to you Capture and recall. Someone is typing. Search is keyword-only — last quarter's relevant page doesn't surface unless you remember the title.
The bet The loop is the product. Capture solved (voice + transcription). Structure solved (AI extraction). The bet is on the move everyone else leaves to you: action items thread to the decision log, recurring meetings open with their prior outcomes loaded, MCP exposes the archive to every assistant your team uses.
What's left to you Showing up. The thread is on the system. Recognition — the part teams are good at — is the only piece left for you.
The transcript is solved. The thread isn't. That's the bet.
A 1:1 in a coffee shop, a standup on Zoom, a retro on Google Meet, a question in Claude next week. Knovya works on every surface where those moments live, and threads them together afterwards.
In the coffee shop, on the walk, on the call — voice transcribes both speakers, structures itself into an editable note when the meeting ends.
Decisions, action items with owners, and the threads back to the project and the decision log — all extracted from the transcript, all linked both ways.
Calendar event, Knovya panel, the relevant prior outcomes — already on the screen before anyone says "remind me where we left off."
Through MCP, every assistant your team uses can read the meeting archive natively — no copy-paste, no exporting, no losing context between one call and the next.
Meeting notes aren't a feature — they're a thread that ties the rest of the team's work together. Here's the constellation around this page.
Real-time transcription, structured by speaker — no typing during the meeting.
See featureA chat about the meeting becomes a real note — saved, structured, linked.
See featureAction items thread to the decision log, the project, the owner — both directions.
See featureClaude reads your meeting archive between sessions — Cursor and ChatGPT, too.
See feature"Six months ago we decided not to go down this road. Last month we had the same debate again."
A team that remembers why, not just what — Experience Envelope surfaces precedents the moment a similar question returns.
See the workflow Problem 11 · Chapter II"The project context lives in Slack. The decisions live in a doc. The status updates live in a thread."
One project canvas — brief, kickoff, decisions, meeting notes, retro, all in the same archive, all linked.
See the workflowThe 150-year history from Robert's Rules to AI summaries — and the part each generation left to the next.
Read the primer DefinitionWhere the meeting archive eventually lives — the team's shared memory, indexed and reachable.
Read the primerA team's memory isn't built in one offsite. It's built one captured decision, one threaded action item, one re-opened retro at a time. The thread starts forming the moment you do.
Or scroll back to the diagnosis.
Eight questions we keep getting about meeting notes, AI notetakers, and the thread between meetings. If yours isn't here, the contact page reaches us directly.
Stop trying to listen and write at the same time. Let transcription run during the meeting, then let AI extract the structure afterwards — agenda, decisions, action items, owners. Your job is to read, edit, and confirm the structure is right. The meeting itself is for being present, not for typing.
Minutes are the formal, archival record — Robert's Rules of Order (1876) defined the format for parliamentary procedure, and corporations carried it into the boardroom. Meeting notes are the working record: less formal, more useful day-to-day, often kept by a participant rather than a designated secretary. Knovya treats notes as the canonical artifact and lets you generate minutes from them when audit or legal requires it.
The trap is treating each meeting as an island. Organize by linking, not by foldering — every meeting should connect to its project, the decisions it produced, the people who attended, and the prior meeting it follows. In Knovya, those links happen automatically; you don't maintain a folder hierarchy, you just let the archive form.
AI Transforms turns a transcript into a structured summary in three formats: a one-paragraph executive read, a decisions-and-action-items extract, and a thematic distillation across multiple related meetings. The summary lives as a child of the original note, so the long-form is one click away when context is needed.
Yes. Voice Notes captures the audio (in-app or via system recording), transcribes it, and routes the transcript into Knovya as a structured note. AI Transforms then extracts agenda, decisions, action items, and owners. The next meeting opens with the prior outcomes loaded — that's the part most AI notetakers leave on the table.
Otter optimizes for transcription, Fellow for templated agendas, Granola for AI summaries. Each one solves a single move well. Knovya's bet is on the move they all leave to you: threading. Action items thread to the decision log. Decisions thread to the project. The next meeting opens with the prior thread already pulled forward. The transcript is solved — the thread isn't.
Through MCP (Model Context Protocol), Claude, ChatGPT, Cursor, and other compatible tools read your Knovya archive natively. Ask "what did we decide about pricing in last week's call?" and the assistant queries your notes, returns the answer, and links to the source meeting — without copy-paste, without context-switching.
Yes. Knovya Free is forever-free with 50 notes, 50 AI credits per month, and 50 MCP calls per month — enough to run several weeks of meetings, see how the threading works, and decide whether the archive starts compounding for your team before paying anything.