We enable cross-institutional collaboration on data without ever exposing or exchanging plaintext customer information to any organization or affecting data usability, thereby maintaining utmost customer data privacy.
Silent Compute ensures privacy in collaboration
Cryptographic guarantees
Data never leaves the source - Raw data is never moved, shared, or exposed
Data remains encrypted even during computation
Built for compliance
Meet data localisation requirements while enabling secure, global data collaboration
Supports data minimisation, encryption, purpose limitation, and other core privacy principles
Purpose bound computations
Control how data is used - Enforce pre-agreed computations and consent terms
Track, verify, and audit how data is used at every step
Data collaboration creates new opportunities
across multiple industries
PARTNERS & ALLIANCES
Silence collaborates with industry leaders
Silent Compute has a spectrum of capabilities
Secure Match
Find and search overlapping records across private datasets without accessing the lists
Secure Statistics
Perform privacy-preserving statistical computations on encrypted data points from multiple parties
Secure Data Structuring
Query, rank, compare or filter data based on specified criteria, without any exposure
Secure ML
Build and train Machine Learning models without learning anything about the underlying data
Secure Network Graphs
Identify trends and patterns across an aggregated network of individual private datasets
Secure Proofs
Cryptographic proofs of possession, identity and more without sharing the raw sources
Available for any construct
Two-Party
Two parties seeking to collaborate on their proprietary data or models without revealing their private inputs
Multi-Party
A consortium of financial institutions collaborating to enable secure, network-wide search, comparison, or deduplication
Delegated Analytics
Allow third parties to run analytics, apply models, and extract insights, all without ever accessing or moving raw data
Resources
