Silence Laboratories offers a managed cryptographic platform that enables secure multi‑party computation and privacy‑preserving inference without moving raw data. Its Silent Shard service delivers high‑performance MPC, while Silent Compute allows encrypted data analytics with auditable consent and policy enforcement, supporting on‑premise or cloud deployments for regulated industries.
Funding
$1.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises in finance, digital assets, telecom, and adtech must collaborate on sensitive data while complying with strict privacy regulations, yet traditional computing requires moving or exposing that data, creating security and compliance risks.
Solution
Silence Laboratories provides an institutional-grade cryptographic infrastructure that enables secure multi-party computation (MPC) and privacy‑preserving inference without moving raw data. Its Silent Shard service delivers high‑performance MPC as a managed service, offering algorithms that are 15–30× faster than competing solutions and the first production implementation of OT‑based DKLs23 MPC‑TSS protocols. Silent Compute extends this capability to distributed datasets, allowing inference directly on encrypted data while enforcing auditable, consent‑bound usage policies. The platform is delivered via a Cryptographic Computing Virtual Machine (CCVM) that manages secret keys, distributes authorization signatures, and enforces policy and consent rules with full audit trails, supporting on‑premise or native cloud integration for simplified risk assessment and compliance.
Target Audience
Primary customers are financial institutions, digital asset custodians, telecom operators, and adtech platforms that need to process sensitive data collaboratively while meeting privacy and regulatory standards.
Features
- Silent Shard: end‑to‑end MPC as a service with 15–30× faster algorithms and OT‑based DKLs23 MPC‑TSS protocol
- Silent Compute: privacy‑preserving inference on distributed data with no data movement
- Cryptographic Computing Virtual Machine (CCVM): distributed secret management, token‑based authorization, and trustless policy engine with auditability
- Native integration and on‑prem deployment options for streamlined compliance and customizability
- Transparent consent mechanisms that cryptographically bind data usage to regulatory requirements
- Support for digital asset wallets, institutional custody, and stablecoin payment workflows