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Nabla has launched Nabla Dictation for Mac, the first fully on-device clinical dictation app designed natively for macOS. The product combines on-device speech recognition with Epic integration, extending AI capabilities beyond patient encounters to support tasks like managing inbox messages and drafting referrals. The application processes all speech on-device using Apple's Core ML and Neural Engine, eliminating cloud dependency whilst maintaining compatibility with existing dictation hardware including PowerMic and SpeechMike microphones. The company rebuilt its entire speech stack using Apple native technologies like Swift and Core ML. Forty-four per cent of Nabla's active clinicians work on Apple devices. The platform is trusted by over 100,000 clinicians across 190 health systems, including M Health Fairview, and supports more than 35 languages whilst integrating with all major electronic health records systems.

Nabla launches Dictation for Mac. Nabla, providers of artificial intelligence assistants in clinical care, has introduced a fully on-device clinical dictation app, Nabla Dictation for Mac, combining on-device speech recognition with deep Epic electronic health record integration. For health systems operating on Apple devices, Nabla is combining ambient documentation with medical-grade dictation on Mac in a single AI-native experience. The offering supports documentation, communication, and care coordination tasks through one unified voice layer while maintaining compatibility with existing dictation hardware, including PowerMic and SpeechMike microphones. "For decades, clinicians have been forced to adapt their workflows to software," said Laurent Landowski, chief product officer of Nabla, in a statement. "We believe it's time for software to adapt to clinicians. Voice is becoming the most natural interface for clinical work, but healthcare has been held back by fragmented tools and workflows that weren't designed for the AI era. Our vision is a future where clinicians can move through their entire day using a single, intelligent voice layer built around how care is actually delivered." To deliver the Mac app, Nabla rebuilt its full speech stack, including voice activation, speech-to-text, and medical post-processing using Apple native technologies like Swift and Core ML, and taking advantage of the power of Apple silicon. Using Apple's Core ML Tools, the team migrated years of PyTorch-based speech models onto Apple Silicon. On-device, the models are optimized for the Apple Neural Engine. This enables the low latency and efficiency required for medical-grade dictation, with no audio sent to servers and no cloud dependency. "Core ML and the Apple Neural Engine made it possible for us to bring our entire speech pipeline on-device for Mac without compromising the performance clinicians expect from medical-grade dictation," Landowski said. "That means clinicians get the speed and responsiveness they need, while keeping speech processing entirely on their device."

Nabla launches Medical-Grade Dictation Product built for Apple devices. July 28, 2026 NEW YORK, July 28, 2026 /PRNewswire/ - Nabla, one of the most widely adopted AI assistants in clinical care, today announced the first fully on-device clinical dictation app, Nabla Dictation for Mac, designed natively for macOS. By combining on-device speech recognition with deep Epic integration, the solution represents the next step in Nabla's vision for a more seamless, voice-driven future that extends AI beyond the patient encounter and enables clinicians to spend more time focused on their patients. Bringing Ambient Documentation Together with Medical-Grade Dictation for Mac Much of a clinician's day is still spent on administrative work that happens outside the visit itself. While ambient AI has helped streamline documentation during the patient conversation, providers still spend significant time managing inbox messages, drafting referrals, coordinating follow-up care, and completing other tasks throughout the day. Many of these activities still rely on traditional dictation tools and fragmented workflows, creating additional complexity across the broader care experience. For health systems operating on Apple devices, Nabla is combining ambient documentation with medical-grade dictation on Mac in a single AI-native experience. The offering is designed to support documentation, communication, and care coordination tasks through one unified voice layer while maintaining compatibility with existing dictation hardware, including PowerMic and SpeechMike microphones - allowing health systems to modernize without replacing established infrastructure or disrupting the workflows clinicians already rely on. "For decades, clinicians have been forced to adapt their workflows to software," said Laurent Landowski, Chief Product Officer at Nabla. "We believe it's time for software to adapt to clinicians. Voice is becoming the most natural interface for clinical work, but healthcare has been held back by fragmented tools and workflows that weren't designed for the AI era. Our vision is a future where clinicians can move through their entire day using a single, intelligent voice layer built around how care is actually delivered." Delivering On-Device Clinical Dictation Nabla's dictation capabilities are the result of more than two years of investment in speech recognition technology, shaped by feedback from thousands of practicing clinicians and purpose-built for the complexity of medical language and documentation. To deliver the best experience and performance on the Mac, Nabla rebuilt its full speech stack - voice activation, speech-to-text, and medical post-processing - using Apple native technologies like Swift and Core ML, and taking advantage of the power of Apple silicon.[1] Using Apple's Core ML Tools, the team migrated years of PyTorch-based speech models onto Apple Silicon. On-device, the models are optimized for the Apple Neural Engine. This enables the low latency and efficiency required for a medical-grade dictation experience, with no audio sent to a server and no cloud dependency. "Core ML and the Apple Neural Engine made it possible for us to bring our entire speech pipeline on-device for Mac without compromising the performance clinicians expect from medical-grade dictation," said Landowski. "That means clinicians get the speed and responsiveness they need, while keeping speech processing entirely on their device." Designed to run entirely on-device, the new dictation experience is built to deliver the speed, privacy, and responsiveness clinicians expect while keeping clinical conversations under the clinician's control. By bringing enterprise-grade clinical dictation directly on Mac and processing all speech on-device, Nabla enhances privacy, gives clinicians greater control over their data, and eliminates the need to send audio to the cloud. Leveraging Core ML and the Apple Neural Engine, Nabla also reduces the cloud infrastructure and token costs associated with server-based speech processing while delivering a fast, responsive experience. As one of the few healthcare AI companies developing fully on-device clinical dictation integrated with Epic, Nabla aims to bring together native Apple performance and the EHR workflows clinicians already rely on every day. For health systems that have historically lacked enterprise-grade dictation options, the collaboration also provides a modern, AI-native alternative without requiring clinicians to change how they work on a Mac. Forty-four percent of active clinicians using Nabla today work on Apple devices, including significant adoption among Epic organizations and virtual-first care providers. Trusted by clinicians and healthcare organizations nationwide, this announcement builds on Nabla's growing adoption as a trusted enterprise partner for health systems modernizing care delivery workflows. Organizations such as M Health Fairview have already deployed Nabla at scale, demonstrating demand for an AI-native, unified voice experience that reduces administrative burden and supports clinicians and care teams across the patient journey.