The Tough Tech problem we are solving
Financial institutions, healthcare providers, and government agencies want to run AI on their most sensitive data, but every standard approach exposes it at some point in the process. Cloud inference decrypts the data inside the cloud instance before a model can read it. Confidential computing narrows that exposure to a hardware enclave, but still requires trusting the enclave and its vendors. Building everything on-premises avoids both problems but comes with cost and complexity most organizations cannot absorb.
About our solution
CipherSonic Labs builds encrypted computing infrastructure that lets AI models run inference directly on encrypted data, using fully homomorphic encryption and lattice-based cryptography, without ever decrypting it. The process runs in three steps: encrypt the data before it leaves the customer's environment, run inference on the encrypted version through the company's CipherCloud service, then return only the encrypted result. Nothing is decrypted along the way, not by the model, not by the cloud provider. GPU and FPGA acceleration keep the computation fast enough for close to real-time use, aimed at regulated environments: fraud detection and risk modeling in finance, clinical diagnostics under HIPAA, and government and defense workflows where the data has to stay usable without ever being exposed.