Could AI turn a meeting transcript into usable minutes?

#Someone still has to reread the transcript

You recorded an hour-long meeting and got it transcribed. What you have now is dozens of pages of text. To find out what was decided, and who agreed to do what by when, someone still has to read it from the top and pull it together.

OwlAI does that work when the meeting ends. It builds the minutes from the transcribed speech and the notes taken during the meeting, and attaches to each to-do the owner and due date that were said out loud. The transcript is only the raw material.

#Minutes regroup what was said so people can use it

A transcript is what was heard, in the order it was heard. Minutes regroup those words so readers can act on them. The minutes OwlAI creates have four parts: summaries by subtopic, conclusions and agreements, an action plan, and the overall flow of the meeting.

Below the minutes sits a separate AI verification section. It takes claims made in the meeting without evidence, checks them against internal documents, databases and connectors, and marks each as true, false or needs checking. It also points out agenda items that reached no conclusion or never came up. The check uses only material that the person who created the meeting can view.

#During the meeting, a summary arrives every 5 minutes

Click New meeting and recording starts right away. The transcript usually appears on screen 1 to 2 minutes behind the conversation. Every 5 minutes, a summary of that segment appears alongside it, so someone who joins late can catch up quickly. At important moments you can leave a note tagged important, decision, action or question, and those notes feed into the minutes.

You can also upload an audio file you already have, or the recording of a video call. Once the upload finishes, the server takes over the processing, so you can leave the screen.

#The meeting survives a dropped recording

If the network drops during a meeting, the device holds the recording and uploads it once the connection is back. If the browser closes and recording stops, the meeting stays in a paused state; you can reopen it, or continue recording from another device. While a device is asleep, nothing is recorded, and the minutes mark that stretch as an "unrecorded portion." No gap goes unnoticed.

#Owners and due dates nobody stated stay blank

The action plan follows one rule: it carries over only what was actually said. If the meeting settled that "the production team will replace the sensor module by Friday," the action plan shows that owner and that due date. When a to-do had no owner or due date, those fields stay empty. Because no plausible name gets filled in, a blank tells you the meeting hasn't decided that yet, and it becomes something to raise next time. Conclusions work the same way. An agenda item that reached no conclusion has an empty conclusion field, and where people only reached consensus without a formal decision, it is marked separately as an agreement.

Notes taken during the meeting count for more than the transcript. A participant wrote each one at the moment they judged something important or decided, so the discussion around notes tagged important or decision is never left out of the minutes.

If the minutes aren't what you wanted, Regenerate creates them again with an instruction such as "focus on decisions" or "more detail." Click "Continue in chat" to build on that meeting's content and ask for a follow-up email draft or a task summary.

#Neither the speaker nor the original audio is kept

Only the person who created a meeting can view it. Administrators cannot open other people's meetings either. The recording is used only to produce the transcript and the minutes, and the original audio is deleted when the meeting ends. What remains is the transcribed text, the notes, the segment summaries and the minutes.

The transcript starts a new speech bubble wherever the voice changes, but it neither shows nor stores who was speaking. A voice is sensitive information that can identify a person on its own, and the minutes need to capture what was decided. Observed in production (August 2026), minutes generated with speaker labels and minutes generated without them showed no difference in structure or in how completely they covered the discussion. Minutes quality stays the same, and less personal information is retained.

Where speech recognition runs depends on how OwlAI is deployed. On-premises deployments by default use a speech recognition model on an internal server, so audio does not leave the company. OwlAI SaaS uses a managed speech recognition service and deletes the audio and transcript held by that service as soon as the result comes back. If you are evaluating OwlAI, start by deciding which of the two setups fits your company's security requirements.