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Trint adds live 40-language transcription to desktop and mobile apps

Trint adds live 40-language transcription to desktop and mobile apps
trint

Trint updated its desktop and mobile applications with live transcription in over 40 languages, AI-powered summarization, and cross-platform sync for recording, editing, and collaborating on audio and video transcripts, targeting broadcast and virtual meeting workflows.

Key Takeaways

  • Live transcription supports 40+ languages with automatic speaker differentiation; detecting multiple languages within the same document is an enterprise-only feature
  • Desktop app can capture and transcribe on-screen content including videos, broadcasts, and virtual meetings, or input from device mic and camera
  • AI highlights surface key moments in real time; transcripts can be summarized via prompt and translated into 70+ languages
  • File-based transcription handles audio and video in 50+ languages with cross-transcript quote search
  • Edouard Guihaire, Deputy Technical Editor-in-Chief at Agence France-Presse, cited speed and accuracy for live event transcription as a core need the tool addresses

Why It Matters

Trint is positioning its apps as a real-time transcription layer for broadcast and virtual-meeting workflows, not just a post-production tool. The ability to capture and transcribe on-screen content live — including broadcasts — combined with cross-platform sync and collaborative editing, directly targets newsroom and sports media teams that need verified quotes during live events. In a fragmented transcription market where Otter.ai dominates corporate meeting capture and Verbit targets broadcast compliance, Trint's multilingual depth (40+ live languages vs. Otter's four) and ISO 27001-certified no-training data policy give it a distinct wedge with media enterprises. Watch whether Trint's upcoming MLTT Live feature — a real-time multilingual transcription and translation tool backed by an Innovate UK grant — extends the 40-language live capability into simultaneous translation, which would push the platform closer to a must-have for international broadcast operations.

Additional Context

Trint reached $11.3M ARR in July 2025 with a $34M valuation and 103 employees, having raised capital from investors including Edge Investments and The New York Times Company in an August 2024 round valued at approximately GBP 50.8M, per Preqin. The company reported 250,000+ users and 125 million transcribed minutes in 2024, according to a Trint blog post dated January 28, 2025. Trint also won an Innovate UK Smart Grant in October 2024 to develop MLTT Live — a tool for real-time multi-language transcription and translation that would automatically recognize and transcribe multiple languages spoken in the same live audio stream. The broader transcription software market was valued at approximately $4.4 billion in 2024 and is forecast to reach $9.7 billion by 2031 at a 12% CAGR, per QYResearch data cited by GII Research. The market remains fragmented, with Trint competing against Otter.ai (which focuses on corporate meeting capture across four languages), Rev (hybrid human-AI transcription), Verbit (broadcast compliance via its Captivate product supporting 50+ languages with low-latency live captions), and Descript (text-based video editing). Trint differentiates primarily through its 40+ live language support, ISO 27001 certification, and a policy of never training AI models on user transcripts — a posture that has attracted media clients including Agence France-Presse, Politico, and BILD. Trint's active product cadence through 2025 — including iOS speaker editing, a home-screen Live widget, and admin dashboards for enterprise usage tracking — signals continued investment in mobile parity with its web experience. The company's integrations with AP ENPS, Octopus, and Mimir news production systems, established in 2024, further embed it in existing broadcast workflows rather than requiring a standalone tool shift. Whether MLTT Live ships as a production feature will determine whether Trint can close the gap between transcription and real-time translation for multilingual broadcast environments.


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