CipherSonic provides an encrypted AI infrastructure that lets enterprises run machine‑learning models on sensitive data without ever exposing the raw information.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises in regulated industries must apply machine‑learning models to highly sensitive data such as financial transactions, patient records, or proprietary research, but traditional AI pipelines require decrypting data, creating exposure risks and compliance challenges.
Solution
CipherSonic offers an encrypted AI infrastructure that allows models to be trained and executed on data that remains encrypted at rest, in transit, and during inference. The platform uses homomorphic encryption and secure hardware acceleration (GPU/FPGA) to perform near real‑time inference without ever revealing plaintext. By exposing only encrypted tensors through a simple API, CipherSonic eliminates the need for data de‑identification or separate secure environments, enabling privacy‑first AI deployments that maintain model accuracy while meeting regulatory requirements. The solution is designed for scalable, cost‑efficient operation across cloud and on‑premises deployments.
Target Audience
Primary customers are financial institutions, healthcare providers, and life‑science companies that need to run AI on confidential data while complying with strict privacy and regulatory standards.
Features
- Homomorphic encryption that keeps data encrypted throughout the entire AI pipeline
- GPU and FPGA acceleration for low‑latency, near real‑time inference on encrypted inputs
- Zero plaintext exposure guarantee (0% exposure) with no accuracy trade‑off
- Simple REST/SDK API for seamless integration into existing applications
- Scalable architecture optimized for cost‑efficient operation at enterprise scale
- Support for common use cases such as fraud detection, risk modeling, compliance, and clinical analytics