Picovoice delivers simultaneous speech-to-speech translation with on-device AI, eliminating network delays, protecting privacy, and supporting custom language needs.
Two people speak different languages—need seamless conversation.
Tourists use a handheld device that listens and translates signs or speech.
Healthcare professionals converse with patients in different languages.
Picovoice delivers real-time, sub-second translation speeds by using on-device processing and compact large language models (LLMs). Unlike cloud-based solutions, there's no delay from server round-trips, which makes live conversations feel smooth and natural. Whether switching between English and Spanish or Korean and French, the speed supports truly fluid multilingual interaction.
Yes. Through the Picovoice Console, teams can train custom models to recognize and translate specialized vocabulary in fields like medicine, law, or manufacturing. This ensures accurate handling of technical terminology that generic translation engines often miss, making the tool suitable for enterprise, clinical, and regulated environments.
Yes. The translation engine operates fully on-device—no cloud or internet is required for real-time usage. Whether offline in remote areas or inside secure environments, it works reliably. Note: Internet is only required for licensing and usage tracking.
All processing occurs locally on the device—voice, text, and translations are not transmitted to external servers. This ensures conversations remain secure and aligned with privacy standards. It's well-suited for sensitive use cases like telehealth and legal interpretation.
Yes. Picovoice offers live translation across a wide range of languages and dialects, with the ability to expand to new language pairs as needed. Customization is also available for regional speech patterns and pronunciation styles, making it more inclusive and effective than one-size-fits-all models.
Picovoice is optimized to run on a variety of platforms including smartphones, tablets, laptops, and embedded edge devices. It requires no specialized hardware or GPU, which keeps integration simple and cost-effective—just deploy the model and go multilingual instantly.
