Use case · Note-takers

Bad transcripts
don't just break your product —
they break trust.

When STT fails, every downstream workflow falls apart — notes, summaries, CRM syncs.

You've seen transcripts like this before...

Live feedback
Wrong name
Jon Smitht · Acmee Corp
Number unclear
eighteenn thousand
Field missing
Fridy · four-four-uhh
conversation
Initiating…
live
Spoke with Jon Smitht at Acmee Corp — they're ready to renew.
Nice. Did he confirm the numbers?
Yeah — eighteenn thousand, closing end of Q two.
Perfect. What are the next steps?
Send the contract by Fridy. Account is four-four-uhh.
On it, I'll update Salesforce now. ✓
transcript_export.json
writing…
01 Alex "Spoke with Jon Smitht at Acmee Corp…" ⚠ entity_err
02 Sam "Nice. Did he confirm the numbers?" ✓
03 Alex "eighteenn thousand, closing end of Q two…" ⚠ parse_err
04 Sam "Perfect. What are the next steps?" ✓
05 Alex "Send contract by Fridy. Account: four-four-uhh…" ⚠ field_err
06 Sam "On it, I'll update Salesforce right now." ✓
scanning…
The Problem
Bad STT doesn't just cause errors.
It breaks the entire workflow.
01
Notes become unreliable.
Missed names, wrong numbers, broken context.
02
Workflows stop working.
Summaries degrade. CRM syncs break.
03
Users stop trusting you.
Once trust is gone, churn follows quietly.
04
Your product looks broken.
Users blame the note-taker, not the STT.
The Solution

Stop letting bad STT sabotage your growth.

Reliable STT turns note-takers from fragile demos into products that scale with real users and real-world audio.

Production-grade transcription

Designed to hold up in real meetings — with noise, accents, crosstalk, and interruptions. Not just clean audio demos.

Best-in-class speaker diarization

Cleanly separates speakers so downstream summaries, action items, and CRM updates stay usable and correctly attributed.

High-precision entity recognition

Captures names, acronyms, numbers, and addresses accurately — so your CRM integrations and automations don't choke on bad data.

Multilingual STT with code-switching

Detects and transcribes multiple languages in the same conversation — no pre-configuration needed, no friction for your users.

This is the difference
production-grade STT makes

gladia — Q1 Sales Review — Live Transcript
Live · 00:24:38
Transcript
Diarized Entities on Multilingual
Sarah L.
Sarah L. 00:01:12
Okay, let's start with the Acme Corp deal. Marcus Chen confirmed the PO last week — final amount is $124,000.
James R.
James R. 00:01:34
Great. We should loop in Dr. Priya Nair from Vertex AI — she mentioned at NeurIPS they're evaluating STT vendors in Q2.
Marie L.
Marie L. 00:02:08
fr Oui, je suis d'accord — le budget est validé. On peut avancer dès lundi. en The legal team just needs the final scope doc.
Sarah L.
Sarah L. 00:02:41
Perfect. James, can you follow up with Marcus by Friday? Account number is ACM-2024-0091.
James R.
James R. 00:02:59
Absolutely, I'll reach out first thing
Speaker diarization
Sarah L.
45%
James R.
32%
Marie L.
23%
Languages detected
🇺🇸 English 🇫🇷 French
Entities recognized
Marcus Chen PERSON
Acme Corp ORG
$124,000 MONEY
ACM-2024-0091 ID
CRM sync
Contact updated ✓
Deal updated — $124k ✓
Meeting note created ✓
Follow-up task fired ✓

Your note-taker is only as good as its transcripts.

One API. Production-grade accuracy, diarization, and entity recognition — so your product works as well as it demos.

Try it live Try it live Talk to us Talk to us