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TL;DR: Native Microsoft Teams transcription via the Graph API delivers transcripts only after a meeting ends, provides utterance-level (not word-level) timestamps, and degrades sharply on accented or multilingual speech. For any product that routes Teams audio to downstream AI systems, the more reliable architectural pattern is capturing raw audio via a custom WebRTC bot and routing it to a managed STT engine, one that delivers word-level timestamps, accurate multilingual handling, and predictable per-hour costs, none of which the native Graph API provides. Solaria-1 covers real-time streaming and broad language support. Solaria-3 is optimised for European business audio.
Podcast transcription at scale: an API workflow for media platforms
TL;DR: Podcast audio is invisible to search without accurate, word-level transcripts, and transcription quality sets the ceiling for everything downstream, from content discovery to AI-generated show notes. A production-grade async pipeline (decoupled webhook ingestion, pyannoteAI-powered diarization, word-level timestamps) is what separates a searchable audio library from a title-and-description catalog. At 10,000 hours monthly, a managed API costs $2,000–$6,100 depending on plan.
HIPAA-ready meeting assistants for healthcare and therapy sessions
TL;DR: Building a HIPAA-ready meeting assistant requires more than a generic transcription wrapper. Any API that processes Protected Health Information on your behalf must sign a Business Associate Agreement (BAA) before PHI flows to it, and transcription accuracy matters more than most teams expect: word error rate can more than double in noisy, multi-speaker clinical environments compared to controlled recordings, meaning errors compound into every SOAP note and EHR entry downstream. This guide covers the BAA requirements, encryption controls, and unit economics product teams need to evaluate before committing to an audio infrastructure provider for clinical or therapy use cases.
How to integrate live transcription API with Twilio to transcribe calls in real time
Published on Sep 28, 2023
Twilio, used by hundreds of thousands of businesses and more than ten million developers worldwide, can now integrate with our live transcription API. The integration makes it easier for users to natively transcribe any phone call in real time while using Twilio. With transcribed text at your disposal, you'll then be able to analyze, archive, and act upon voice data more effectively.
Below, you’ll find a step-by-step guide on setting up the Twilio integration with Gladia API in JavaScript for free.
What can you do with Twilio integration?
Any developer can use this integration to transcribe phone calls in real-time.
How to implement Twilio + Gladia real-time transcription integration
Step 1: Set up your Gladia account
If you haven't already, sign up for our Speech-to-Text API at app.gladia.io and obtain your API key.
Step 2: Create and parametrize your Twilio account
Get a phone number, following the first step of the main page to connect to your Twilio account.
On the left panel Develop > United States (US1) > Phone Numbers > Manage > Active numbers.
Click on the phone number you just created.
In 'Configure' panel, 'Voice Configuration' section, 'A call comes in' field, choose 'Webhook' with URL = 'http://[your-id-address]:[your-app-port-number]' and HTTP = 'HTTP POST'
Step 3: Configure your server and install dependencies
In .env file, add GLADIA_API_KEY var with your API key obtained from Gladia’s website and PORT var, the port you used to configure your phone number in above section (default is 8080)
Feel free to check out the video version of the tutorial for a step-by-step walkthrough with one of our software engineers, Antoine.
We hope you enjoyed this how-to tutorial! Given how much audio data still goes to wasted, we’re always curious to explore the many ways in which transcription tech can be used to remedy that. Let us know if you end up using our API with Twilio, Discord, or other, we’d love to hear from you.
About Gladia
At Gladia, we built an optimized version of Whisper in the form of an API, adapted to real-life professional use cases and distinguished by exceptional accuracy, speed, extended multilingual capabilities and state-of-the-art features, including speaker diarization and word-level timestamps.
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Speech-To-Text
Microsoft Teams transcription via API
Speech-To-Text
Podcast transcription at scale: an API workflow for media platforms
Speech-To-Text
HIPAA-ready meeting assistants for healthcare and therapy sessions
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