Voice AI startup Subtle has introduced a new pair of wireless earbuds designed to improve call clarity and produce more accurate voice transcription in noisy environments.
The earbuds, unveiled ahead of the Consumer Electronics Show (CES) in Las Vegas, are priced at $199 and are expected to ship in the U.S. in the coming months. Each purchase includes a one-year subscription to Subtle’s iOS and Mac app.
The companion app lets users take voice notes and chat with an AI assistant hands-free, without pressing any buttons. Subtle says the earbuds use a chip capable of waking a locked iPhone to enable this interaction.
The company is positioning the product as an alternative to AI-powered voice dictation services such as Wispr Flow, Willow, Monolouge, and Superwhisper. Paired with its earbuds, Subtle claims it can deliver five times fewer transcription errors than using AirPods Pro 3 with OpenAI’s transcription model.
In a demo viewed by TechCrunch, the earbuds captured speech clearly over loud background noise and successfully transcribed a voice note even when Subtle co-founder and CEO Tyler Chen spoke in a whisper.
“We are seeing that there is a huge move towards voice as a new interface that a lot of folks are adopting. You can do much more with voice in a natural way than with a keyboard. However, we saw that voice is rarely an interface people use when others are around. So that using our noise isolation model, we will give consumers a way to experience a voice interface in the form of our earbuds,” Chen said in an interview.
Chen contrasted Subtle’s approach with recent hardware experiments such as note-taking rings from Sandbar and Pebble. By combining the earbuds with its software, Subtle aims to bundle dictation, AI chat, and voice notes into a single system.
Customers can pre-order the earbuds now via the startup’s site. The “Voicebuds” will be available in black and white.
Subtle has raised $6 million to date and has worked with consumer electronics companies including Qualcomm and Nothing to deploy its noise isolation models.