SonaFact

Everything between the recording and the finished document

One file, as far as you want to take it: a transcript you can trust, minutes with receipts, a scored call review, subtitles translated into four more languages — or simply a clean DOCX.

Upload & processingTranscript editorAI documentsCall analyticsSubtitles & glossaries
Upload & processing

Drop a file and watch it work

One recording at a time, up to ten hours long, audio or video. It reports the stage it is in and how much is left — no spinner that tells you nothing.

The language is recognised for you across all hundred, or you name it yourself when you already know.
Speaker count: automatic, or an exact number if you know it.
An account glossary of your own names, passed to the engine as a hint.
Plain-language errors with a fix, not a code.
MP3 · WAV · M4A · MP4 · MKV · OGG · FLAC · WMARetry and logs per file
Queue3 files
42:10product-review.mp4Transcribing · 64% · ~2 min leftProcessing
18:24interview-01.mp3Separating speakers · 88%Processing
07:55support-call.m4aChinese (94%) · 2 speakersDone
old_tape.wmaAudio file not found — locate fileError
Stages: decoding → speakers → language → transcription → word alignment → glossary → utterances.
Transcript editor

Fix a word, rename a speaker everywhere

Playback that highlights the line being spoken, inline editing of the text, and one click to move a line to the right speaker.

Click a line to play from it; click the text to edit it.
Low-confidence words are underlined so you know where to look.
Find and replace across the whole transcript, with word timings kept.
Speaker panel with speaking time and share; move a line to another speaker or merge two into one.
Search & replaceFollow playbackMerge speakers
product-review · utterances9 utterances · 142 words
00:00Anna WhitfieldGood morning, Ms Weber. Thanks for making time today.OK
00:10Speaker 2I do have a few questions about the schedule.Edited
00:27Speaker 2We need to check invoicing in KSeF.Suggestion
00:44Anna WhitfieldYeah.Low conf.
Short interjections like “yeah” or “ok” are the most common thing to correct.
AI documents

Minutes, action items, chapters — with receipts

Generate a document from one of six built-in kinds. Every item carries a clickable timestamp, and anything the transcript does not support is removed before you see it.

Meeting minutes, action items, summary, chapters, sales and support call reviews.
Verification line: “Removed 2 items not supported by the recording.”
Documents mark themselves outdated when the transcript changes.
Output language independent of the recording language.
DOCX · PDF · Markdown · CopyEdit as markdownRegenerate
Action itemsMeeting minutes · up to date
01:01Anna WhitfieldSend the migration summary to all participantsToday
00:23James CarterConfirm the Munich data hand-over date18 Sep
00:52unassignedBook the follow-up meeting in two weeks
🛡 Removed 2 items not supported by the recording.
Call analytics

Scorecards for sales and support calls

Talk share, pace, longest monologue, interruptions and questions, plus a criterion-by-criterion scorecard with justification and the moment each one was met.

Built-in BANT and support standard scorecards, or your own criteria.
Roles per speaker with an AI suggestion you can override.
Objections with the response given, and next steps with owners.
Sentiment at the start, middle and end of the call.
Editable criteriaRegenerate after role changes
Sales call · BANTScore 72%
04:12BudgetCustomer named a range for the 2027 budgetMet
07:48AuthorityDecision maker mentioned but not confirmedPartial
11:02NeedTwo concrete problems with the current workflowMet
TimelineNo date discussed for the decisionNot met
Roles changed — regenerate to update the score.
Subtitles & glossaries

Subtitles reviewed sentence by sentence

SRT and WebVTT with readability rules, up to four translated languages per recording, and glossaries that keep names and jargon spelled your way.

Up to 42 characters per line, 17 characters per second.
Status per sentence: OK, edited, needs review, outdated.
Only changed sentences are re-translated after a transcript edit.
Your own glossary of names and jargon, kept per language or used for all of them.
SRTWebVTTGlossary hinted to the engine before it listens
Subtitles · Chinese (Simplified)14/16 · 1 needs review
00:12Anna我们先从迁移状态开始。OK
00:19James第一阶段将在十月完成。Edited
00:27James我们需要检查 KSeF 中的发票。Needs review
00:41Anna我今天就发送摘要。Outdated
18 cues · 4 too fast — fix before export.

It tells you where it is unsure

Every automatic transcript has weak spots — a name said quickly, a word lost under a cough. Most tools hand you a clean-looking wall of text and let you find them yourself. SonaFact marks them.

Underlined where it matters

Words the engine was not confident about carry a dotted underline. You proofread those, not the whole hour.

A number for this recording

Each transcript states what share of its words were marked — usually a few percent on clear audio, more on a noisy phone call. It is measured on your file, not quoted from a brochure.

The same in every language

All one hundred languages go through the same engine and the same marking. A recording in Tamil gets its share of uncertain words stated just like one in English.

Try it on a recording you already have

The free plan is enough to judge accuracy, speaker separation and the editor.

Start transcribing for free