API Comparison Table

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Speech-To-Text

Migrating from Azure Speech to Gladia: a step-by-step switching guide

TL;DR: Migrating from Azure Speech to Gladia removes the overhead of custom training pipelines and fragmented per-feature billing. Azure routes diarization, translation, and sentiment through separate services with separate billing meters. We bundle all audio intelligence into one per-hour rate on Starter and Growth plans. Solaria-3 ranks #1 for real-world European business audio, Solaria-1 covers 100+ languages with native code-switching. Both deliver out-of-the-box accuracy that eliminates custom training for most production audio. Most engineering teams complete the API refactoring in under 24 hours.

Speech-To-Text

How to evaluate a speech-to-text API: a technical buyer's framework

TL;DR: Choosing an STT API on vendor benchmarks alone is how teams end up with transcription that looks fine in staging and breaks on production audio. A rigorous evaluation requires building a test set from your own calls, measuring word error rate (WER) on your specific audio distribution, stress-testing latency under concurrent load, and auditing data retraining terms before signing. This guide gives you a reusable engineering blueprint to run that evaluation end-to-end, the same methodology behind our own open async benchmark, which covers 7 datasets and 74+ hours of audio across 8 providers.

Speech-To-Text

The contact center QA scorecard: what to measure and how transcription feeds it

TL;DR: Manual QA teams review as little as 1% to 2% of contact center calls, leaving the vast majority of interactions unreviewed and exposing systemic compliance risks that sampling never surfaces. Scaling to automated coverage requires transcription accurate enough to power LLM-based scoring without silent failures. If your speech-to-text engine misattributes a speaker or drops a compliance disclosure, every downstream scorecard, CRM entry, and coaching flag is wrong. French CCaaS platform Gravite cut per-call review time from 15 minutes to 1 minute (93% reduction) while automating coverage across their full 50,000 hours of annual call volume on infrastructure built for real-world contact center audio.

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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