Embed private voice AI into any product instantly

Private

Runs locally without an internet connection. Nothing is sent to the cloud to fully protect user's data.

Efficient

Uses proprietary deep learning technology that enables cutting-edge models to run on commodity (embedded) hardware efficiently.

Accurate

Resilient to noise, reverberation, and works across a variety of accents. Works everywhere for anyone.

Plug and Play

Enables customizations within seconds. Reduces time to market while promoting user's product, brand, and identity.

Cross-Platform

Runs across all major platforms. Linux, Mac, Windows, Android, iOS, watchOS, Raspberry Pi, ARM Cortex-A, ARM Cortex-M, and a growing number of embedded processors are supported.

Open Benchmarks

Picovoice empowers users to evaluate its technology independently. Facilitates data-driven decision making.

Zero Lead Time

Uses proprietary AI algorithms to build models for any custom wake word/command within seconds (instead of weeks). Removes the hassle of time-consuming and costly data gathering phase.

Multiple Phrase Detection

Can detect many hotwords (wake up words and commands) concurrently with no additional CPU or memory footprint.

Lightweight

Natural fit for IoT. Can run with as low as 17 KB of memory and 3.4% CPU usage on Raspberry Pi 3.

Highly-Accurate

Outperforms existing solutions with high margins in clean and noisy environments. Read more here.

Ease of Integration

Expedite your development by reusing the many available references designs. Bindings and demo applications for C/C++, Android (Java), iOS (Swift), Python, Rust, and Web Assembly are available.

Language Independent

Can create models for almost any phrase in any language.

Interactive Demo

This demo allows you to change the color of the smart lamp using Picovoice's voice control engine via any of the following commands. Note that you need a working microphone. This demo is running locally in the browser. You can turn off your internet connection and it will keep working.

• OK lamp, white.
• OK lamp, yellow.
• OK lamp, orange.
• OK lamp, purple.
• OK lamp, navy blue.

Start Demo

Natural Conversational Interface

Uses proprietary deep learning technology that allows inferring intent from conversational speech with extremely-limited memory and CPU usage.

Lightweight

Natural fit for IoT and embedded platforms. Runs with as low as 115 KB of RAM and 8% CPU usage on a Raspberry Pi 3.

Customizable

Can be readily customized for a given domain and product. Allows differentiation to promote your product, brand, and identity.

Interactive Demo

This demo allows you to issue voice commands to a smart coffee maker using natural speech. Note that you need a working microphone. You can ask the coffee maker (Alfred) to make you a coffee using voice commands such as

• Alfred, can I have a latte?
• Alfred, make me a single-shot espresso.
• Alfred, I want a triple-shot americano with milk.
• Alfred, may I have a large cappuccino with cream?
• ...

Note that you need a working microphone. This demo is running locally in the browser. You can turn off your internet connection and it will keep working.

Start Demo

Open Vocabulary

No limit on the size of vocabulary. Provides large vocabulary transcription capabilities on embedded platforms.

Continuous and Real-Time

Transcribes audio in real time. Reduces latency and improves the user experience.

Lightweight

Runs in real-time with only 5.6 MB of memory and 25% CPU usage on a Raspberry Pi 3. Natural fit for IoT platforms. Android, iOS, Raspberry Pi, and a growing number of IoT platforms are supported.