Wavify

Wavify: On-device Speech AI Platform

Wavify is an on-device speech AI platform that enables software engineers to embed speech recognition, wake word detection, and voice command capabilities directly into any application. It emphasizes blazing-fast performance, privacy by design, and cross-platform compatibility, allowing developers to deliver cloud-level speech features without sending user data to the cloud.

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Key Features

• On-device inference for speech-to-text (STT), wake word detection, and voice commands
• SOTA-quality performance with cloud-level capabilities while keeping data on-device
• Privacy by design: user voice data never leaves the device; GDPR-friendly
• Cross-platform support: Linux, macOS, Windows, iOS, Android, Web, Raspberry Pi, and embedded systems
• Multilingual support: 20+ languages
• Lightweight runtimes suitable for edge devices (example runtimes include Whisper.cpp and Wavify’s own engine)
• Quick integration with minimal code changes

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How to Use Wavify

1. Choose your integration approach: pick from the provided SDKs and demos that fit your tech stack (Python, Rust, etc.).
2. Initialize the SttEngine with your model path and API key (if required by your setup).
3. Run STT on audio files or streams: convert speech to text locally on the device.

Example (Python):

import os
from wavify.stt import SttEngine

engine = SttEngine(
 "path/to/your/model",
 os.getenv("WAVIFY_API_KEY")
)

result = engine.stt_from_file("/path/to/your/file")
print(result)

1. Extend with wake word and commands as needed for your product, leveraging the same on-device inference pipeline.

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Supported Use Cases

• Human voice as UI for various industries
• Healthcare: documentation, transcription, AI-assisted therapy
• Automotive: hands-free vehicle control, real-time navigation, in-car entertainment
• Legal: automate case documentation, transcriptions of court/meetings
• Consumer electronics: smart home, AI companions, voice control in apps and games
• Customer support: transcriptions for accurate record-keeping and faster issue resolution
• Education: interactive learning experiences with voice interaction

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SDKs and Developer Experience

• Cross-language support with ready-to-use SDKs
• Developer experience designed for fast integration and iteration
• Clear examples and demos to accelerate adoption

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How It Works

• Run on-device inference for STT, wake word detection, and voice commands
• Uses lightweight, efficient models suitable for edge devices
• Privacy-centric: no data leaves the user’s device

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Safety and Privacy Considerations

• Data never leaves the device; no need for Data Processing Agreements for basic on-device usage
• Ensure compliance with local privacy laws when deploying voice-enabled features

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Core Features

• On-device STT, wake word detection, and voice commands
• Lightning-fast performance and low memory footprint on edge devices
• Cloud-level quality while preserving user privacy
• Broad cross-platform support (Linux, macOS, Windows, iOS, Android, Web, Raspberry Pi, embedded)
• 20+ languages supported
• Simple integration with minimal code changes