Free
$0Free plan available.
Syntonym's face generation technology creates unique and anonymous faces in real-time, whether on mobile, cloud, or local platforms, ensuring individuals have a secure and reliable solution to safeguard their privacy and anonymity when required. Syntonym provides generative AI for privacy, offering hyper-realistic face anonymization for videos and images. It disrupts the way we are being recorded by cameras, allowing individuals to be seen on their own terms and lifting the privacy barrier. Syntonym integrates as a privacy layer into any video platform to enable interactive communication and open exchange. It ensures privacy compliance by removing biometrics to unlock unique video processing potential with real-time, lossless anonymization in a privacy regulation compliant way. It also enables analytics and training by processing recordings for analytics and turning real-world data into training data in a GDPR compliant way.
Upload your image or video to the Syntonym cloud or on-premise platform to download anonymized versions. Alternatively, integrate the Syntonym SDK into your existing pipeline for real-time anonymization.
Syntonym supports various platforms, including Cloud, On-Premise, Edge, Mobile SDK, and desktop applications (macOS and Windows).
Syntonym ensures privacy compliance by removing sensitive biometric data from images and videos while preserving analytical metrics for model training and video analytics. It also uses synthetic face indicators to notify users when a synthetic face is applied.
Syntonym enhances privacy, increases user engagement, enables analytics and training, and improves data security by protecting sensitive biometric information from potential data breaches.
Free plan available.
Use these comparison pages to understand the trade-offs between the models most relevant to Syntonym.
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Compare Gemini 2.5 Flash and Gemini 2.0 Flash across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
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