AI Transcription
Every recording becomes a searchable document
Upload audio or video and get a timestamped, speaker-labelled transcript you can search, summarise, quote and turn into subtitles.
What is the AI Transcription?
AI Transcription processes recordings into structured transcripts. It separates speakers, attaches timestamps, and gives you a document you can search rather than an audio file you have to scrub through. Once a recording is text, everything downstream becomes cheap: pulling a quote, finding the moment a decision was made, generating a summary, producing subtitles.
This is the workflow product of the audio family. Speech to Text is the quick converter for your own dictation. Transcription assumes a real recording with more than one person in it, and it optimises for what you do afterwards: reading, searching, citing and exporting.
Accuracy depends heavily on the recording. A clean remote call recorded per-speaker transcribes close to perfectly. Four people around a laptop in a room with an air conditioner will produce errors, particularly on names and overlapping speech. Budget a few minutes for review on anything you intend to quote publicly.
Capabilities
What you can do with the AI Transcription
How it works
Using the AI Transcription
- 01
Upload the recording
Audio or video, from a call recording, a phone, a camera or a podcast file. Higher-quality source audio produces meaningfully better results.
- 02
Set speakers and language
Tell it how many speakers to expect and name them if you know them. This improves labelling considerably.
- 03
Review the transcript
Scan for names, jargon and passages where people talked over each other, and correct them in place.
- 04
Work with the text
Summarise, extract decisions and actions, pull quotes with timestamps, or export subtitles.
Examples
What good input and output look like
AI Transcription
Live demoWriting the prompt1/2You record
customer-interview.mp3
AmmarAI writes
Customer interview
Input
Recording attached. Label speakers, add timestamps, then summarise the problems raised.
Output
[00:04:12] Participant: Honestly, the hardest part is the handoff. We finish a draft and then it just sits in someone's inbox for three days before anyone looks at it.
Video subtitles
Input
Walkthrough audio attached. Transcribe it and export subtitles aligned to the narration.
Output
[00:01:38] Now open the campaign tab. You'll see every variant listed here, and clicking one shows the exact version that ran, along with its results.
Key features
What the tool gives you
Speaker separation
Distinct speakers are identified and labelled so the transcript reads as a conversation.
Timestamped navigation
Click any sentence to hear it, which makes verifying a quote a two-second job.
Searchable archive
Find the phrase across every transcript in your workspace instead of remembering which call it was in.
Summaries and extraction
Produce meeting summaries, decisions and action lists from the transcript in one step.
Subtitle export
Generate caption files timed to the source video for publishing.
Who it is for
People who get the most from this
Researchers
Analyse interviews properly instead of relying on notes taken while trying to listen.
Journalists
Find and verify quotes with the timestamp attached, quickly and defensibly.
Podcasters
Produce show notes, chapter markers and quotable clips from the episode transcript.
Teams that meet a lot
Turn recurring meetings into a searchable record of what was actually decided.
Video publishers
Caption everything, which improves accessibility and how the content is discovered.
Workflows
Practical ways teams use it
Research synthesis
Transcribe every interview in a study, search across all of them for the recurring phrases, and build the findings on evidence you can cite to the second.
Meeting record
Record the weekly call, transcribe it, generate decisions and owners, and circulate that instead of half-remembered notes.
Content from recordings
Turn a webinar transcript into an article, a set of social quotes and a captioned highlight clip.
Tips that improve results
- Record each remote participant on their own track when the platform allows it; speaker separation becomes near perfect.
- Supply a list of names and product terms before processing so the model spells them correctly.
- Fix errors in the first few minutes early; the same terms usually recur throughout.
- Do not quote publicly from an unreviewed transcript.
- Keep the original audio; the transcript is a working document, not the source of record.
Mistakes worth avoiding
- Recording a group meeting on one laptop microphone and expecting clean speaker labels.
- Treating the summary as a substitute for reading the parts that matter.
- Ignoring consent. Tell participants they are being recorded and check the rules that apply where you operate.
- Exporting subtitles without reviewing them, which puts every transcription error on screen.
AI Transcription FAQ
How accurate is the transcription?
Clear single-track audio transcribes very accurately. Group recordings in noisy rooms, heavy crosstalk and specialist vocabulary all reduce accuracy, mostly on names and technical terms. Review before publishing.
Does it identify who is speaking?
Yes, it separates speakers and labels them, and you can rename the labels. Accuracy improves when you state how many speakers to expect.
Can I transcribe video?
Yes. Upload the video directly and export a subtitle file alongside the text transcript.
How long can a recording be?
Long recordings are supported, with per-file limits set by your plan. Very long sessions are easier to work with when split into logical parts.
Is it different from speech to text?
Yes. Speech to text is a quick converter, typically for your own dictation. Transcription is built for multi-speaker recordings and everything you do with them afterwards.
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Try the AI Transcription free
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