Real-time Arabic transcription at 150 ms on a standard iPhone, with audio that never leaves the device, bringing sovereign Arabic voice AI to phones, cars, and homes across the Arab world.
Abu Dhabi, UAE – May 13, 2026 - CNTXT AI today announced the launch of Munsit Edge, one of
the first Arabic speech-to-text systems to run fully on-device, with no cloud
connection required.
Built on the same Munsit Arabic ASR
(automatic speech recognition) model that has set a global benchmark for
transcription accuracy across major Arabic dialects, Munsit Edge delivers
real-time Arabic transcription on consumer hardware.
For the first time, the Arabic
speech-to-text model runs entirely on the device, where the conversation
happens: on a phone in Riyadh, in a car in Cairo, in a home in Dubai, in a
contact center in Manama. Nothing leaves the user's hands.
“Until today, the Arab world has
never had Arabic speech recognition that truly ran on the devices people use,”
said Mohammad Abu Sheikh, CEO of CNTXT AI. “With Munsit, we proved you can
build an Arabic‑first model that beats generic systems on accuracy. With Munsit
Edge, we’ve moved that model out of distant data centers and onto the devices
themselves. Your calls, your cars, your homes – all of them can now understand
Arabic in real time without sending a single second of audio to a third‑party
cloud.”
A first for Arabic speech recognition
Until now, all Arabic STT systems
have depended on cloud inference. Audio is streamed to remote servers,
processed on GPUs, and returned across the network, introducing latency,
privacy exposure, and infrastructure cost at every interaction. The linguistic
complexity of Arabic (rich dialect diversity, frequent code-switching with
English, demanding real-world acoustic conditions) has made on-device
deployment particularly difficult.
Munsit Edge solves it. Through a
foundation-trained Arabic ASR model and runtime optimization tuned for everyday
consumer hardware, Munsit Edge runs across iPhone, Android, MacBook, Windows
and Linux PCs, in-car systems, smart home devices, and embedded IoT, at speeds
and accuracy levels that, until today, required server infrastructure.
Performance highlights:
●
Around
24% word error rate (WER - accuracy metric in speech
recognition), across major Arabic dialects: Gulf, Egyptian, Levantine, MSA, and
Arabic-English code-switching
●
Latency
around 150 ms for real‑time streaming
transcription on a standard iPhone‑class device
●
Same
Arabic accuracy across cloud, on‑prem, and
on‑device deployments. No quality trade-off for moving on-device.
●
No
network connection is required for inference.
Transcription runs fully locally.
Why on-device matters
“Sovereignty isn't just where your
data is stored. It's where it's processed,” Abu Sheikh added. “For a bank
handling a customer's voice or a government running a citizen helpline, what
matters is that Arabic speech can be understood on their own infrastructure.
Munsit Edge makes it possible to do that on phones, PCs, and edge devices
across the region.”
Munsit Edge is purpose-built for
the use cases where on-device matters most:
●
Contact
centers, telco and IVR. Real-time
Arabic call transcription with zero per-minute server cost, deployed inside the
operator's own infrastructure.
●
Banking
and fintech. Voice transcription that meets
strict data-residency requirements.
●
Government
and public sector. Citizen-facing voice services on
sovereign infrastructure.
●
In-car
and embedded systems. Arabic voice interfaces that work
without a cellular connection.
●
Smart
home and consumer devices. Arabic
voice control without a cloud subscription, working offline.
Availability
Munsit Edge is available today
through three integration paths:
●
Native
SDKs for iOS, Android, macOS, Windows,
and Linux
●
On-premise
containers for private cloud and data center
deployment
●
Embedded
IoT builds for automotive, smart home, and
industrial hardware
The broader Munsit platform also
remains available via secure cloud API, web workspace, and mobile app, so
organisations can combine cloud and on‑device deployments based on their data
and latency needs.
Developers and enterprises can
request access at hello@munsit.com
-END-
About CNTXT
AI
CNTXT AI is
a UAE-based data and AI company that helps organizations prepare, build,
deploy, and scale sovereign AI solutions while maintaining full data control.
Its
enterprise services include high-quality training data through labeling and
annotation for AI labs, enterprise data teams, and robotics applications,
alongside custom AI solutions that integrate with clients' existing
infrastructure. Its proprietary AI product portfolio includes Munsit, the
leading Arabic voice AI platform.
From raw
data to production-ready AI, CNTXT AI helps organizations adopt AI faster
without compromising compliance, sovereignty, or real-world performance.
For more
information, visit https://www.cntxt.tech
For press
inquiries: rym.bachouche@cntxt.tech