Gujarati is one of the great trade languages of South Asia, and that's exactly why generic tools under-serve it: the business that runs in Gujarati runs across a non-resident diaspora and mixes heavily with English, so a clean dictionary sentence is the least representative thing you can feed a recognizer. Gujarati also has its own script — related to Devanagari but missing the connecting top line, with its own letterforms and its own numerals — and under-resourced tools either tofu it into boxes or fall back to something that renders badly. Add the spoken-versus-formal register gap and the honorific tu/tame distinction, and "supports Gujarati" on a feature list tells you almost nothing. The language carries trade ledgers and family-business calls across Ahmedabad, London, and New Jersey in the same breath. Here's what actually decides whether a Gujarati meeting comes back usable.
A script tools quietly under-serve
Gujarati is written in its own Brahmic script. It's related to Devanagari, but with one immediately visible difference: it drops the connecting horizontal headstroke that runs across the top of Devanagari letters, so the letterforms sit as separate rounded shapes. It also has its own set of letters and its own native numerals. None of that is exotic — it's the everyday script of a major language — but it is under-resourced compared to the scripts tools are tuned for, and that shows up as mis-rendering: empty boxes where conjuncts should be, dropped vowel signs, or a fallback font that mangles the shapes. A transcript that a Gujarati reader can't read cleanly isn't a transcript; it's a guessing game.
Gujlish is the trade-and-diaspora register
The professional register of Gujarati is Gujlish — Gujarati grammar carrying English content words, dropped straight into the frame. In trade talk and in the large NRI diaspora, this isn't sloppy speech; it's the normal way business gets done. "Aa quarter nā targets finalize karva padshe" is one ordinary sentence: English nouns and verbs, Gujarati frame, Gujarati verb endings doing the grammatical work. A tool that detects "Gujarati" may leave the English untranslated; one that detects "English" leaves the Gujarati. Neither reader gets a whole sentence. Each one needs the line rebuilt complete in their own language, not handed half of it with the other half left as-is.
Register and respect
Gujarati marks respect in its pronouns: tu is the familiar second person, tame the respectful or plural one, and the choice carries real social weight in a business setting. Spoken Gujarati and formal Gujarati also pull apart — the way a cousin's call sounds and the way a board note reads are different registers of the same language. A tool that flattens all of this into one neutral output can make a deferential speaker read as blunt, or render a casual aside in stiff formal phrasing. In a transcript that someone forwards, that flattening reads as wrong — sometimes as rude — even when every individual word is technically correct.
Why "supports Gujarati" isn't enough
A tool can list Gujarati, transcribe a clean sentence, and still fall apart on the script rendering, the Gujlish your team actually speaks, and the register the room actually used. The feature list won't tell you which. One real call will: does a native speaker read the captions and transcript and recognize how the meeting actually sounded — the script clean, the English kept whole, the respect markers intact? For why this pattern repeats across Asian languages, see real-time translation for remote teams.
How to do it with Sageio
- Add
bot@sageio.netto your Google Meet calendar invite. It joins on its own — no extension, nothing to install. - Each participant picks their caption language. The Ahmedabad team reads clean Gujarati, a colleague abroad reads clean English — both from the same spoken Gujarati, at the same time. (Sageio translates into 20+ languages.)
- Everyone speaks naturally — Gujlish, the tu/tame of it, all of it. Translated captions appear in about two seconds.
- Afterward, a searchable transcript and an AI summary arrive within about five minutes, shared at the host's discretion.
(Today this runs on Google Meet; Zoom and Microsoft Teams support is coming soon.)
How to test any tool in five minutes
Say a normal Gujlish line — something like "aa deal māre next week sudhī close karvi chhe" ("I have to close this deal by next week") — and check two things: do the English words come back whole, and does the Gujarati render in clean Gujarati script rather than boxes or a mangled fallback? Then say the same idea once with tu and once with tame and see whether the output preserves the difference in register. If the script breaks, the English garbles, or the respect marker vanishes, the tool wasn't built for spoken Gujarati.
Is it private?
For anything that joins your meetings: Sageio doesn't use your meeting content to train AI models, and its AI vendors are contractually restricted from doing the same. Audio is processed in memory and discarded — only the text transcript and summary are kept, encrypted, in the region you choose (US, EU, or APAC). Enterprise customers can self-host the entire stack.
Frequently asked questions
Why does Gujarati script matter for a transcript? Gujarati uses its own Brahmic script — related to Devanagari but without the connecting top headstroke, and with its own letterforms and numerals. Under-resourced tools mis-render it into empty boxes, dropped vowel signs, or a mangled fallback font. A transcript a Gujarati reader can't read cleanly is useless, so correct script rendering is the baseline, not a bonus.
What is Gujlish? Gujarati grammar carrying English content words, with the verb endings still done in Gujarati — the normal professional register in trade and across the NRI diaspora. Tools that assume one language per sentence translate only half. Correct handling rebuilds a complete sentence in each target language instead of leaving the other half untranslated.
Why do the tu/tame pronouns matter? Gujarati marks respect in its second-person pronouns — tu is familiar, tame respectful or plural — and the choice carries social weight in business. A tool that flattens register can make a polite speaker read as blunt in the transcript, which is exactly the kind of error people notice when a summary gets forwarded.
How fast are the translated captions? About two seconds, fast enough to keep a live conversation moving, with a searchable transcript and summary within about five minutes after the call.
What does it cost to try? Every plan starts with a free 60-minute trial, no credit card required. After that, Professional is $49/month and Teams is $99 per seat/month (annual billing includes 2 months free); Enterprise is custom-priced.
If your team works in Gujarati, the honest test is whether a native speaker reads the live captions and transcript and hears the actual meeting — the script clean, the English kept whole, the tu/tame respect intact. Add the bot to your next call and let them judge.