API Comparison Table

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Migrating from Rev.ai to Gladia: what global teams should know

TL;DR: At 10,000 hours of audio per month, Rev.ai's per-hour billing compounds quickly once you add diarization, translation, and sentiment as separate line items. Language coverage gaps surface silently in production when non-English or accented audio degrades without returning an obvious error. This guide gives you the exact API payload mappings, WebSocket transition logic, and a TCO model at realistic scale to make a defensible evaluation of switching. If you decide to migrate, our all-inclusive per-hour pricing bundles every audio intelligence feature at the base rate, and most teams complete the endpoint transition and initial production validation in under 24 hours.

Speech-To-Text

Switching your speech-to-text provider: A migration checklist for note-takers and contact center platforms

TL;DR: Switching your speech-to-text provider is a structural risk only if you skip the pre-migration audit. The real danger is not the cutover itself but continuing to run infrastructure that corrupts CRM entries, breaks LLM summaries, and inflates your per-hour cost with add-on fees you never modeled at scale. The four-stage phased cutover in this guide is designed to reach 100% production traffic without user-visible downtime, the same structural approach that let Aircall cut processing time by 95% and scale to over one million calls per week after adopting Gladia.

Speech-To-Text

How decision intelligence improves customer service consistency in contact centers

TL;DR: Contact centers fail to deliver consistent service when routing infrastructure runs on static rules engines that cannot handle the complexity of real human conversation. Modern speech-to-text infrastructure addresses this by processing raw audio and feeding structured outputs to your CRM, using machine learning to analyze intent, sentiment, and speaker characteristics. Transcription accuracy sets the ceiling for every downstream action: a wrong word silently corrupts a CRM entry, a missed intent misfires a routing decision, and a misread sentiment score delays escalation. This playbook covers how to build and deploy that architecture without blowing your latency budget or your unit economics.

Ebook: Ultimate guide to using LLMs with speech recognition

Published on Jan 7, 2025

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: