The First No-Code Voice AI Platform for Microcontrollers

Today we are announcing the public availability of Picovoice Shepherd: the first no-code platform for building voice interfaces on microcontrollers. Shepherd enables creating voice experiences similar to Alexa that run on microcontrollers — without writing a single line of code. Picovoice AI processes voice data entirely on-device, without sending any voice data to the cloud. Edge voice interfaces built with Picovoice are private, reliable, zero-latency, and cost-effective, distinguishing them from cloud-based alternatives.

Alas, the technical-complexities and various specialized skills needed to train and deploy voice AI into microcontrollers have limited their wide adoption for speech recognition. Today, only a handful of tech giants have access to this technology.

Microcontrollers are small, low-power, and cost-effective compute modules. They have already been deployed into billions of devices. The ability to bring voice AI to microcontrollers unlocks numerous use cases that are otherwise infeasible. Alas, the technical-complexities and various specialized skills needed to train and deploy voice AI intro microcontrollers have limited their wide adoption for speech recognition. Today, only a handful of tech giants have access to this technology.

Shepherd — together with Picovoice Console — streamlines adding voice AI into microcontrollers. Shepherd dramatically simplifies a process that previously would have taken months of R&D by teams of scientists and engineers to what can be undertaken by a non-technical individual in under an hour. This significantly reduces risk and time to market. The no-code aspect of Shepherd empowers developers, product owners, and designers to create voice interfaces that run entirely on a power-efficient and bargain-priced microcontroller. No coding or machine learning expertise is required.

Customers can create voice models within their browsers instantly, using Picovoice Console. Once the models are trained, they can be downloaded and loaded onto a microcontroller using Picovoice Shepherd, without any embedded expertise. Shepherd supports popular Arm Cortex-M-based microcontrollers from ST and NXP, with additional support on the way.