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What did you just agree to?

Paste a meeting transcript. It finds every promise made in the room, yours and theirs, and shows which ones are about to be forgotten.

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  • No account
  • Your transcript is not stored
  • Answers in seconds

Paste your transcript

Zoom, Google Meet, Otter, Granola, Fathom — any export with names on the lines. Timestamps are fine.

Nothing pasted yetNothing leaves your browser until you press the button

Which one are you?

So it can separate what you owe from what you're owed.

Names appear here as soon as you paste a transcript.

Find what was promised

Takes about a second. Your transcript is not stored.

Paste a transcript to begin

How it works

Three steps, no sign-up

  1. Paste the transcript

    Any export with the speaker's name at the start of each line: Zoom, Google Meet, Otter, Granola, Fathom, Fireflies, or notes you typed yourself. Timestamps are fine.

  2. Say which speaker is you

    That is what splits what you owe from what you are owed. The names are read from the lines in your browser, so nothing has been sent yet.

  3. Read what was promised

    Each promise comes back with a risk band, the deadline if the sentence had one, whether it is clear who owns it, and the exact words behind each call, underlined.

What you get

What each part of a result is

Every field on a result is either read from the transcript or judged by a model. The table says which, so you know what to check.

What each part of a result is
PartWhere it comes fromWhat it tells you
Who said itRead from your textThe name on the line. Attribution is parsing, so it cannot tell you that you owe something you never said.
Is it a promiseModel judgementWhether the speaker took on an obligation. Questions, suggestions nobody accepted and “someone should…” are dropped.
How firmModel judgementFirm, hedged or vague. A vague line, or one said as “we”, shows the owner as unclear instead of naming the speaker.
DeadlineRead from your textA day, date or phrase in the promise's own sentence. If that sentence names none, the card says Not stated.
HedgesRead from your textSofteners in the sentence, such as “probably” or “hopefully”, underlined in amber.
AdmissionsRead from your textPhrases like “I keep forgetting” or “I'm behind”, underlined in red. An acknowledged debt is usually the most fragile promise in the room.
Risk bandModel judgementLikely to slip, could slip or on track. A judgement about how the promise was made, not a forecast of what happens next.

Background

Why it works this way

What counts as a commitment in a meeting?

A commitment is a line where a speaker takes something on: “I'll send the draft Thursday”, “I'll ping legal today”. A question, a suggestion nobody accepted, or “someone should look at that sometime” is not one, because nobody owns it.

The ones that matter most are usually the untidy ones: an acknowledged debt (“I owe him an intro, I keep forgetting”) or a promise with no date at all. Those are what this tool flags first.

Why read a transcript at all?

The transcript that would tell you what you agreed to already exists, and nobody reads it, because reading a 4,000-word transcript costs more than the meeting did. This reads all of it in a few seconds and hands you back the list.

Limits

What it cannot tell you

Every tool here is a first pass with edges. These are this one's.

  • It cannot tell you whether a promise was kept. The band describes how the promise was made. Nothing here follows up afterwards.
  • Deadlines come from one sentence only. If someone says “Thursday” in the line before, the promise that follows still shows Not stated. A wrong deadline does more harm than an empty one.
  • It is only as good as the transcript. Speech-to-text mistakes carry through, and a transcript with no speaker names cannot be read at all. The page says so as soon as you paste, rather than guessing.
  • Long meetings are cut. One run reads up to about 400 lines, roughly a two-hour meeting.
  • Runs are limited. Twelve an hour from one connection, so a free tool cannot be run thousands of times.

Your data

What happens to what you give it

Read off the code that does it, not written from memory.

In your browser
Speaker names and line breaks are worked out as you paste.
Sent to our server
The transcript, when you press the button. It is held in memory for that one request, up to about 400 lines.
Sent on to a model
Yes. Each line is put to three questions by Jev, a decision model, through OpenRouter.
What we keep
Nothing you paste. A request counter tied to your IP address (12 runs an hour) holds no content.

Questions

Questions people ask, answered plainly

16 answers, grouped. Each one is written against what the tool actually does.

Using it

Which transcripts work?

Any export where each line starts with the speaker's name: Zoom, Google Meet, Otter, Granola, Fathom, Fireflies, or notes you typed yourself in the form “Sarah: I'll send it Thursday”. Timestamps are fine and are ignored. A block of text with no names cannot work, because everything depends on knowing who said what, and the page tells you that the moment you paste.

How long a meeting can it handle?

About 400 lines in one run, which is roughly a two-hour meeting, and up to 120,000 characters. If yours is longer, run it in parts. Long transcripts are read in parallel chunks, so a long meeting does not take proportionally longer than a short one.

What does “Which one are you?” do?

It splits the list into what you owe and what you are owed, and puts your promises first in the copied checklist. You can change the name after the results appear and the list re-sorts straight away. It does not change what was found.

Can I get the results out?

Yes. “Copy checklist” puts the visible promises on your clipboard as a checklist grouped by person, and each card has a copy button for its own line. There is no account, so nothing is saved for later: copy what you need before you close the tab.

It missed a promise I remember.

Four likely reasons. The line was phrased as a question or a suggestion, so it was not an obligation. The speaker's name was not on it. It fell past the 400-line limit. Or it was a restatement: when the same speaker repeats a promise a moment later (“I know. I'll do it.”), the two are shown as one card, keeping the longer line and the higher risk of the pair.

How it decides

How does it know what counts as a promise?

Each line is put to a decision model as three plain questions: is the speaker taking on an obligation, how firm is it, and how likely is it to be quietly forgotten. Questions, opinions and suggestions nobody accepted are not obligations, so they are dropped. An acknowledged debt, like “I owe him an intro, I keep forgetting”, counts, and is usually the most fragile one in the room.

How does it know who said what?

It reads the name off the line. Every meeting tool writes the speaker into its transcript, so attribution is parsing, not guesswork. That means it cannot get confused and tell you that you owe something you never said. The model is only asked the parts that genuinely need judgement.

What do the underlined words mean?

They are the evidence, read straight from the sentence and shown so you can check the call in a second. A plain underline marks a deadline, amber marks a hedge such as “probably”, and red marks an admission such as “I keep forgetting”. They sit beside the risk band as evidence you can check. They are not what produced it.

What does “likely to slip” actually mean?

It is a judgement about how the promise was made, not a prediction of what happens next. A commitment with a named date, a clear owner and no hedging reads as solid. One with no date, or one where the speaker admits they have already forgotten it once, reads as fragile. It is shown as a band rather than a percentage because there is no outcome data behind it, and a number like 68% would imply a precision it has not earned.

Why does a promise say “Not stated” for the deadline?

Because the promise's own sentence names no day or date, and the tool will not borrow one from a nearby line. If it did, it would sometimes put the wrong date on your promise, and a wrong deadline does more harm than an empty one.

What is Jev?

Jev is a decision model from TypeSafe, reached through OpenRouter. Instead of writing text, it answers questions put to it about a piece of text with a probability, a choice or a score. That is why nothing on a result is generated prose: the only model output is three answers per line.

Accuracy

How accurate is it?

We have not scored it against a labelled set of real meetings, so we will not quote an accuracy percentage. What we have tested is repeatability. In September 2026 we ran one 59-line meeting through it five times and got the same 15 promises every time, with risk scores that moved by at most 0.06 on a scale of 0 to 1. Treat it as a fast first pass to check against what you remember, not as a record of the meeting.

Your data

Do you store my transcript?

No. Speaker names and line breaks are worked out in your browser. When you press the button the lines go to our server, which holds them in memory for that one request and sends them on to the model to answer the three questions per line. Nothing is written to our database. The one thing we do keep is a request counter tied to your IP address, which limits runs to 12 an hour and holds no content.

Which companies see my transcript?

It goes from our server to OpenRouter, the service that routes the request to TypeSafe's Jev model. We do not control how those providers handle data. If a meeting is sensitive, edit out anything you would not send to a third-party service before you paste it.

Can other people see my results?

No. Results exist only in your browser tab, and there is no shareable link. “Copy a line to share” copies one sentence with the number of promises found, not the transcript or anyone's name.

Mailient

Is this what Mailient does?

It is one half of it. This page finds the promise. The product is what makes sure it happens: Mailient watches the threads those commitments live in and drafts the follow-up when one starts going quiet. The tool is that idea shrunk to something you can test in a minute without connecting anything.

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This finds the promise. Mailient makes sure it happens.

Mailient watches the threads your commitments live in and drafts the follow-up when one goes quiet, on your real Gmail, waiting for your approval.