API Comparison Table

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Speech-To-Text

Microsoft Teams transcription via API

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.

Speech-To-Text

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.

Speech-To-Text

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.

Gladia selected to participate in the 2024 AWS Generative AI Accelerator

Published on Sep 18, 2024
Gladia selected to participate in the 2024 AWS Generative AI Accelerator

We’re proud to announce that Gladia has been selected for the second cohort of the AWS Generative AI Accelerator, a global program offering top early-stage startups that are using generative AI to solve complex challenges, learn go-to-market strategies, and access to mentorship and AWS credits.

This opportunity will help Gladia build, train, test, and launch products such as agent assistance for contact center platforms, sales enablement tools and AI meeting assistants, and enable voice-first platforms to deliver more value to their users across borders.

“The new generation of startups is at the forefront of a transformative new wave, pushing the boundaries of what’s possible with artificial intelligence while bringing exciting new solutions to market,” said Jon Jones, Vice President of Go-to-Market at AWS and executive sponsor of the program.
“Expanding the cohort for our Generative AI Accelerator is a testament to the potential we see for startups to usher in new innovations for customers in an increasingly AI-driven world. AWS is committed to fostering groundbreaking technologies and supporting visionary founders on their journey to solve the world’s biggest challenges.”

Gladia is one of 80 global startups from around the world selected for the program, and we’ll attend and showcase our solutions to potential investors, customers, partners, and AWS leaders in December at re:Invent 2024 in Las Vegas.

For more information on the Generative AI Accelerator, visit AWS Generative AI Accelerator.

About Gladia

Gladia provides a speech-to-text and audio intelligence API for building virtual meeting and note-taking apps, call center platforms, and media products, providing transcription, translation, and insights powered by best-in-class ASR, LLMs, and GenAI models.

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