API Comparison Table

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Product News

Gladia to join OVH Groupe, accelerating Europe's sovereign voice AI ambitions

PARIS, France — Sept 21, 2026 — Gladia, the AI audio infrastructure provider trusted by more than 300,000 developers and 2,000 enterprise customers worldwide, announced July 31st, that it has been acquired by OVH Groupe, the parent company of OVHcloud and Europe's leading sovereign cloud provider.

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.

Ebook: Ultimate guide to using LLMs with speech recognition

Published on Jan 7, 2025
Ebook: Ultimate guide to using LLMs with speech recognition

Large Language Models (LLMs) have enabled businesses to build advanced AI-driven features, but navigating the many available models and optimization techniques isn't always easy.

If you’re looking to combine speech recognition (STT) and LLMs for cutting-edge voice apps, look no further! Our ultimate guide is finally here, and it’s filled with valuable strategies and hands-on insights from our work with hundreds of audio-first companies and extensive interviews with experts in AI note-taking, sales enablement and customer support.

What you'll learn:

  • The pros and cons of open-source vs proprietary models;
  • Best practices for optimizing LLM performance;
  • Key metrics and indicators to measure the success of STT systems;
  • A checklist for evaluating LLM and STT vendors for voice apps
  • ... and much more!
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