Munsit
Arabic-first transcription from Abu Dhabi, trained on 15,000 hours
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Munsit is the speech-to-text system from CNTXT AI in Abu Dhabi, built for Arabic rather than adapted to it. Its technical paper describes training on roughly 15,000 hours of Modern Standard Arabic and dialect audio, and the company says the product covers more than 25 dialects. It ships as an API, a web app and a mobile app, with cloud, private-cloud and on-premises deployment.
In CNTXT's own benchmark it averaged a 26.7% word error rate against 36.9% for the largest Whisper model, and on the Saudi SADA dataset it scored 27.7% where Whisper scored 56%. The same test put Azure, ElevenLabs and OpenAI's transcription model between 40% and 46%. These are vendor-run numbers, but they are the only published head-to-head on Saudi broadcast audio.
Pricing is not public; you talk to sales.
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Why we picked it
A Gulf-built system that published its Saudi-dataset numbers instead of a marketing percentage. The lack of public pricing keeps it out of reach for individuals, but for a GCC organisation that needs dialect accuracy and on-premises deployment, Munsit is one of two regional options worth a sales call.
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