Use case

Content & Media

Enhanced content creation and viewing experience

Create, edit, and distribute audio and video content more efficiently. Gladia API unlocks a number of features to optimizes editing and subtitle creation, while improving content searchability, SEO ranks and moderation.

social media
video production
news outlets
media conglomerates
sports networks
educational media

Top features

Audio Indexing & NER

Index every transcribed audio and video in your content library by topics and keywords for easy searchability and accessibility. Invaluable for companies that produce and distribute a large volume of content.

Online meeting
Key decision
Content value


Transcribe podcasts and video content quickly and accurately to streamline editing and improve on SEO scores. Variety of output formats optimized for subtitles. Word-level timestamp add-on is recommended for high-precision editing.


Reach a truly global audience with built-in translation to and from 99 languages. Invaluable for dubbing and subtitles. Multi-language live transcription available soon. A must-have feature for any global media company.


Identify and flag hate speech or other inappropriate and offensive verbal content according to pre-determined parameters, internal protocols, and external regulations.

Speech Analytics

Analyze speech patterns in audio and video content to identify keywords, topics, and themes. Gain in-depth insights into audience behavior and interests to optimize content creation and marketing strategies. Especially useful for companies that create and distribute large volumes of content.

Some stats on performance

boost in sales
saved processing calls
more informed decisions

for your needs


Gladia API utilizes automatic speech recognition technology to convert audio, video files, or URL to text format. It transcribes 1h of audio in less than 60s.


Based on a proprietary algorithm, automatically partitions an audio recording into segments corresponding to different speakers.

Topic classification

Refers to the process of categorizing content into one of the 698 predefined topic categories for content indexation.

Sentiment analysis

Determining the sentiment or opinion behind a piece of audio, such as a conversation or dialogue, using natural language processing.

Speech moderation

Allows to automatically identify and flag hate speech or other inappropriate and offensive verbal content according to pre-determined parameters.

Emotion detection

Our emotion recognition system is built upon the latest research and aims to accurately identify and distinguish between 27 human emotions.



Perfect for developers, early-stage startups, and individuals



(10h/month included)


Designed to grow with scaling digital companies



+ $0.144 / hour for live transcription


Custom plan tailored to the modern enterprise

Contact us

We initially attempted to host Whisper AI, which required significant effort to scale. Switching to Gladia's transcription service brought a welcome change.

Robin lambert, CPO LIVESTORM

Read more

Product News

What is summarization?

Summarization in speech-to-text (STT) AI is a popular feature that streamlines the extraction of essential information from spoken content. By condensing lengthy audio recordings or live conversations into concise summaries, STT summarization enhances user experience, facilitating quicker understanding and decision-making for the final users.

Case Studies

Opening up new markets for a sales meeting and CRM enrichment platform: Spoke's success story with Gladia

In the past, sales teams around the world were presented with a twofold challenge. In addition to showcasing their products in the best light to prospects, they needed to take detailed notes during the call and fill their CRM software manually afterward.

Product News

A new open-source developer app for AI translation, dubbing and lip synching to try

Text-to-speech, voice cloning, and visual dubbing are some of the hottest trends in AI at the moment. Used in tandem with AI transcription and translation, they make it possible to generate hyper-realistic voiceovers, indistinguishable from the sound of the speaker’s natural voice and speech patterns — including in entirely new languages.