Which are you?
Train models with more features or more samples by leveraging sensitive data across multiple privacy zones – from within or across organizations – without guaranteeing localization and privacy-preservation.
Access data from your notebook and popular ML frameworks. Our Python library and REST API enable advanced cryptographic functions with minimal code changes.
Secure your models from various privacy attacks such as inference and reconstruction. Unlock multiple ML use cases like secure federated learning and encrypted model serving for compliant data processing.
TRUSTED BY GLOBAL INNOVATORS
“We are excited to support Inpher as they continue to pioneer Secret Computing®, further improving consumer and client confidence in data privacy and security controls.”Paul BernardDirector of Amazon Alexa Fund
“Advances in data science and cryptography mean that we no longer have to accept the traditional tradeoff between security, privacy and usability when handling data of any kind. Inpher is at the vanguard of this revolution.”Samik ChandaranaHead of Data & Analytics J.P.Morgan Chase
“The ‘bad guys’ have all the same technologies we do. But the one thing they cannot obtain is the scale of training data we could through collaborative sharing, such as through the potential Inpher offers.”Hays W. “Skip” McCormickData Science Lead BNY Mellon