Provides on-device voice AI and local large language model (LLM) platforms that enable enterprises to process data securely and comply with privacy regulations. These tools support applications like meeting transcription, virtual assistants, and legal e-discovery by offering low-latency, scalable, and customizable AI solutions without relying on cloud infrastructure.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises face challenges in processing sensitive data securely while adhering to stringent privacy regulations. Traditional cloud-based AI solutions require data to be sent to third-party servers, creating potential compliance risks and latency issues. This limits the adoption of AI-powered applications in industries with strict data governance requirements.
Solution
Picovoice provides on-device voice AI and local large language model (LLM) platforms that enable enterprises to process data securely within their own infrastructure. The platform offers a suite of modular tools for speech-to-text, text-to-speech, speaker recognition, and noise suppression, as well as LLM inference and compression. By running AI models locally, Picovoice eliminates the need to send data to the cloud, ensuring compliance with privacy regulations and reducing latency. This allows enterprises to build and deploy AI-powered applications such as meeting transcription, virtual assistants, and legal e-discovery solutions with greater security and control.
Target Audience
The primary target audience includes enterprises in industries such as finance, healthcare, legal, and government that require secure, compliant, and low-latency AI solutions for processing sensitive data.
Features
- Leopard Speech-to-Text: High-accuracy speech recognition for on-device transcription.
- Cheetah Streaming Speech-to-Text: Low-latency speech recognition for real-time applications.
- Orca Text-to-Speech: On-device text-to-speech synthesis for natural-sounding voice output.
- Koala Noise Suppression: Noise reduction algorithms to improve speech recognition accuracy in noisy environments.
- Eagle Speaker Recognition: Speaker identification and verification for access control and personalization.
- Falcon Speaker Diarization: Speaker diarization to identify who spoke when in a conversation.
- Octopus Speech-to-Index: Speech-to-index for fast and accurate audio search.
- Porcupine Wake Word: Customizable wake word detection for hands-free activation.
- Rhino Speech-to-Intent: Speech-to-intent engine for understanding user commands.
- Cobra Voice Activity Detection: Voice activity detection to identify speech segments in audio.
- picoLLM Inference: On-device LLM inference for natural language processing tasks.
- picoLLM Compression: LLM compression techniques to reduce model size and improve performance on resource-constrained devices.
- Cross-platform support: Compatibility with various operating systems, including mobile, web browsers, and embedded systems.