· Court Transcript Platform
How it all began: reading someone else's words in court
A trusted transcript, a courtroom, and a paragraph attributed to the wrong speaker. The embarrassment that started Court Transcripts App, and why we publish our accuracy numbers.
Court Transcripts App did not start as a product idea. It started as an embarrassment in front of a judge.
The moment
We had a hearing recording that needed to become a transcript, so we did what most people do: sent the audio to Rev.com, a popular and well-reviewed service, and trusted what came back. It looked right. Clean pages, tidy speaker labels, testimony in neat paragraphs.
Then came the courtroom. Standing before the judge, reading the transcript aloud, the words coming out of my mouth stopped making sense. Mid-passage it became clear why: I was reading another person's words, mistakenly attributed to my name. The transcript had the right sentences and the wrong speaker, and I discovered it live, on the record, in the one room where that matters most.
What that mistake actually is
The transcription industry sells accuracy as a word count: 99 percent of the words correct. But a transcript can get every word right and still put those words in the wrong mouth. Lawyers call testimony by who said it. A judge weighs an admission differently from an accusation. Swap the speaker and you have not made a small error, you have changed what happened in the room.
Speaker attribution is genuinely hard: voices overlap, people interrupt, audio quality dips. That is exactly why it cannot be a silent guess. The failure was not that the service made an attribution error. The failure was that nothing in the transcript told us where it might have.
What we built because of it
That day set the two obsessions this platform is built on.
Accuracy where legal work actually lives. Multiple engines transcribe the same audio and vote word by word. Where they disagree, the platform does not pick quietly: it flags the word for a human, with the audio one click away. Speaker turns carry confidence, crosstalk is marked, and low-confidence attributions must be confirmed by a reviewer before the transcript passes its quality gate. The mistake that started all this is now a marked, reviewable, auditable event instead of a landmine.
Transparency you can check. We publish our benchmarks: the audio, the certified ground truth, the methodology, and the results, including the comparison against Rev.com on the same recordings and the attribution metrics that word-accuracy marketing leaves out. On our published leaderboard, our top mode with a human resolving its flags ranks first against every engine we tested and against the incumbent. We are number one on those benchmarks, and you do not have to take our word for it: the numbers, and how we got them, are on this blog.
Where this goes
We work every day to make this the most trusted and accurate legal transcription service available. Trusted is the word we care about most, because we learned the difference the hard way: trust is not a feeling a clean-looking page gives you. It is what survives being read aloud in front of a judge.
No one should find out about a transcription error the way we did. That is the whole company.