Descript
The AI-powered media editor that allows you to edit video and audio as easily as a text document.
AI-driven transcription and subtitling engine for high-speed content localization.
Izitext is a high-performance AI transcription and subtitling platform designed to streamline the workflow for content creators, journalists, and legal professionals. Built on a proprietary neural processing architecture, Izitext excels in multi-speaker diarization and automated punctuation, supporting over 100 languages with high semantic accuracy. By 2026, the platform has solidified its position in the market by offering a unique 'Interactive Correction Interface' that reduces manual editing time by up to 50% compared to traditional legacy software. The technical infrastructure leverages distributed GPU clusters to ensure near real-time processing speeds, even for long-form 4K video files. Positioned as a direct competitor to Otter.ai and Rev, Izitext focuses on high-precision French and European language processing while maintaining a global reach. Its market strategy revolves around removing technical barriers for non-technical users while providing robust export options (SRT, VTT, DOCX, JSON) for developers and professional editors. The platform emphasizes data security and compliance, making it a viable choice for sensitive corporate and legal transcriptions.
Uses acoustic fingerprinting to distinguish between multiple voices even in low-quality audio environments.
The AI-powered media editor that allows you to edit video and audio as easily as a text document.
AI-powered text-based audio editing that turns high-fidelity production into simple document editing.
The knowledge-focused podcast player for capturing and sharing insights in real-time.
The AI-powered communication platform for customer-obsessed sales and support teams.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Proprietary editor that highlights words in real-time as the audio plays, allowing for instantaneous correction.
Algorithmic splitting of text based on character counts and reading speed standards for Netflix/YouTube.
Allows users to upload technical terms, brand names, or jargon to bias the speech recognition engine.
Concurrent generation of multiple file types from a single master transcript.
Asynchronous processing of up to 50 files simultaneously using cloud-native scaling.
AI-powered noise reduction filters applied during the transcription phase to improve recognition.
Manually listening back to hour-long episodes to find key segments for summaries.
Registry Updated:2/7/2026
Costly court reporting services and slow turnaround for transcripts.
Creating subtitles for multiple languages to increase global reach.