Multi-Party Computation (MPC)
MPC uses a cryptographic primitive that Sedicii has substantially improved so that devices can contribute their data to computations without exposing or sharing this data. Sedicii has developed a solution that allows financial institutions to securely share the knowledge they have about clients or transactions, without disclosing the underlying data or information (PII). MPC may be used to prevent crime or improve the risk assessment through credit scoring for financial institution's clients.
Future Sample Use Cases
CCTV video camera

A CCTV video camera in a train station can match passengers' faces against a law enforcement database with faces of known terrorists and suspects. By virtue of this cryptographic primitive, the facial biometrics of the passengers never leave the camera, therefore complying with regulations and preventing this data from being leaked.

ATM machines

Nearby ATM machines "talk" to each other to figure out if the same person has drawn a substantial amount of money in a short period of time (maybe with different cards). By virtue of this cryptographic primitive, no customer information leaves the ATM’s.

Smartwatches and activity bands

A smartwatch or activity band constantly tracks your activity and registers health indicators such as your heart rate. This information never leaves the device, but using our cryptography the smartwatch company can run algorithms on this data without "seeing" it and produce recommendations and give you advice. Current situation: all this sensitive information goes to the cloud creating huge privacy risks.

Smart speakers

A grid of smart speakers in a house capture voice conversations. Using our cryptography, rather than sending the voice to the cloud (what currently happens), the cloud of an AI company jointly computes with a smart speaker the response to a voice command without receiving that command directly.

Self-driving cars, smart sensors, mobile devices and other IoT

Type A: A company can compute something using the information from one or several IoT devices without receiving or having access to that information.
Type B: Two or more IoT devices contribute information to an algorithm in order to jointly compute something without receiving or having access to the information that the other IoT devices feed into the algorithm.