CNTXT AI unveils Munsit: The most accurate Arabic speech recognition model
Built in the UAE, Munsit sets a new global standard for Arabic speech recognition, powering seamless transcription across private and public services
DUBAI, UAE – CNTXT AI, the UAE-based Data and AI company, today announced the launch of Munsit — a next-generation Arabic speech-to-text model that outperforms every global model on Arabic, including those from OpenAI, Meta, Microsoft and ElevenLabs.
Munsit' — derived from the Arabic root for 'to listen' — symbolizes a breakthrough in voice technology that truly listens with attentiveness and understands the richness of Arabic speech. Developed entirely in the UAE, Munsit sets a new benchmark for transcription accuracy across Modern Standard Arabic and 25+ dialects, enabling seamless Arabic voice data processing across real-world applications.
This breakthrough reflects CNTXT AI's mission to build sovereign technology — AI built in the region, for the region — that competes globally. The model is available now via API, and on-premises deployment for organizations seeking full data control.
How Munsit Powers Arabic Voice Solutions
Munsit is designed to deliver highly accurate Arabic transcription across diverse, real-world scenarios. Addressing the increasing demand for reliable Arabic language solutions, Munsit empowers essential applications, including: Subtitling for Content Creators: Automatically generates precise Arabic subtitles for films, videos and podcasts.
Meeting Notes and Minute-Taking: Transcribes meetings and discussions into Arabic, supporting official documentation and efficient record-keeping.
Call Center Support: Converts voice messages and chatbot interactions in Arabic into text, streamlining feedback and quality assurance processes.
Government and Public Services: Offers transcription and dialect comprehension services tailored for public sector needs, such as processing citizen requests and ensuring accessible communication.
Built for Arabic, Trained on Real Voices
To create Munsit, CNTXT AI processed over 30,000 hours of Arabic audio, refining it into a high-quality 15,000-hour dataset that captures a wide range of dialects, accents, age groups, and environments.
Munsit is powered by advanced AI and high-performance NVIDIA infrastructure, delivering fast, accurate transcription for a variety of Arabic-speaking use cases — from call centers and public services to education and media.
Leading Global Performance in Arabic AI
Benchmarking on Hugging Face leaderboard confirmed that Munsit-1 outperformed leading global speech recognition systems — including OpenAI's Whisper and GPT-4o Transcribe, Meta's SeamlessM4T, ElevenLabs' Scribe, and Microsoft Azure's Speech-to-Text —on Arabic datasets.
CNTXT AI has also released a detailed research paper, outlining the model's architecture, training methodology and evaluation results.
'Munsit is more than just a breakthrough in speech recognition — it's a declaration that Arabic belongs at the forefront of global AI,' said Mohammad Abu Sheikh, CEO of CNTXT AI. 'We've proven that world-class AI doesn't need to be imported — it can be built here, in Arabic, for Arabic. This launch sets a new standard for sovereign technology, made in the UAE and ready for the world.'
A Strategic Step Toward Arabic-Language AI Leadership
Munsit-1 is the first step in a broader roadmap toward a full suite of Arabic voice technologies — from TTS to AI voice assistants.
'This is only version one,' added Abu Sheikh. 'What comes next will redefine how Arabic is understood, spoken, and processed by machines — on our terms, in our language.'
ABOUT
CNTXT AI is a UAE-based Data and AI company that enables organizations to prepare, build, test, deploy, and scale sovereign AI solutions while maintaining full data control.
Our comprehensive suite of solutions transforms data into actionable AI applications—seamlessly, securely, and without compromising sovereignty. From AI-ready data pipelines to scalable deployment and industry-standard validation, we ensure AI adoption is practical, compliant, and optimized for real-world impact.
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