Wispr Flow is getting ready to launch a meeting notetaker for Mac computers, according to updated Terms of Service published July 25 and an email to customers, as reported by TechCrunch on August 5, 2026. The product, called "Notetaker," listens to the audio coming through your computer to write down what everyone says during a meeting. It does this without joining the call as a visible participant, which is how most competing tools work.

After the meeting, Notetaker cleans up the transcript, creates a list of action items, and lets users search through past meetings using AI. The company's Terms of Service describe Notetaker as a tool for transcription, note-taking, summarization, speaker identification, and action item generation. The updated terms specify that Notetaker input may include meeting audio, participant information, meeting metadata, speaker labels, transcripts, and other meeting-processed information. Output may include AI-generated transcripts, summaries, action items, meeting insights, speaker attribution, and other meeting-related content TechCrunch. The privacy policy, also updated July 25, states that Wispr processes Meeting Data to generate those outputs.

Wispr Flow's Notetaker product page explains how the tool figures out who is speaking. It uses your calendar invite, a personal dictionary, and conversational clues, such as when someone says "thanks, Priya." During a meeting, Notetaker provides a live transcript that separates you from other speakers. After the meeting, it produces a polished transcript with full name labels. Speaker labels are most accurate on video calls where each person joins from their own device. In shared conference rooms, Notetaker relies on conversation context to identify people when they are mentioned. If a speaker is unlabeled or mislabeled, you can fix the name once and the correction applies throughout the entire transcript.

The notetaker also provides a live transcript view during the meeting and lets users ask AI to catch them up on what they missed. Beyond the meeting itself, Wispr Flow's documentation, published August 4, describes connecting Flow to AI tools like Claude and ChatGPT, enabling queries such as "What were the action items from my meetings this week?" Wispr Flow Docs. This connection uses something called Model Context Protocol, or MCP, which is an open standard that lets AI assistants pull information from other apps and services.

The launch extends Wispr Flow's path from AI-powered dictation into meeting intelligence. The company released an iOS dictation app on June 3, 2025, followed by a Series A funding round of $30 million from Menlo Ventures later that month. In November 2025, Wispr secured $25 million from Notable Capital as the dictation app gained traction. An Android app launched February 23, 2026, supporting translation in over 100 languages and cross-app functionality TechCrunch. Wispr Flow's free tier allows up to 2,000 words per week, with an unlimited plan at $12 per month or $144 per year TechCrunch.

In total, Wispr Flow has raised more than $81 million and was valued at $700 million at its last funding round. Bloomberg reported in May 2026 that the company was in talks for a new round valuing it at $2 billion TechCrunch. Co-founder Tanay Kothari had previously discussed building an AI assistant, and the Notetaker product appears to be the realization of that vision.

The system-audio approach sets Notetaker apart from most AI meeting tools. Competing products like Otter, Fireflies, Read, and others send a bot that joins the call as a visible participant. That model has known problems: participants sometimes object to a bot in the room, IT policies may block external bots from joining, and the bot can draw unwanted attention to the fact that a meeting is being recorded. Capturing audio locally on the user's Mac avoids those issues, but it means the tool can only capture what the user's computer can hear, which may affect how well it can tell speakers apart in shared conference rooms.

The speaker-identification approach deserves a closer look. By combining calendar information, a personal dictionary, and conversational clues, Wispr Flow is making educated guesses about who is speaking rather than using voice fingerprinting, which matches a person's voice to a stored recording. The product page is upfront about the limitations, acknowledging that shared conference rooms reduce accuracy. The one-touch correction that applies throughout a transcript is a practical design choice that handles the inevitable mislabeling without requiring the user to fix every instance manually.

The MCP integration tells us something about where Wispr Flow sees the product heading. Meeting transcripts are only useful if you can search them, and connecting Notetaker to Claude and ChatGPT positions meeting data as fuel for broader AI workflows rather than a document you read once and forget. Whether companies will be comfortable sending their meeting audio and transcripts through a startup's systems is a separate question from whether the technology works.

Wispr Flow is entering a crowded field. Otter, Fireflies.ai, Read AI, tl;dv, and Microsoft's own Copilot in Teams all offer some combination of transcription, summarization, and action item extraction. The differentiation Wispr Flow is betting on is the no-bot approach combined with cross-meeting AI searching and the company's existing dictation app. The $2 billion valuation reportedly under discussion suggests investors are pricing in the broader assistant vision, not just a notetaker.

The product has not launched yet. What is confirmed is updated terms, a product page, MCP documentation, and a customer email signaling that release is imminent.