PDF: Confidential Computing Solution

Confidential Computing and secure data collaboration solution

As data volumes grow, the need for privacy-preserving collaboration is becoming essential for regulated industries. This paper introduces Confidential Computing — a technology that protects data while it is being processed — and explains how Partisia combines it with Multi-Party Computation (MPC) to secure joint analytics across institutions.

The solution guide demonstrates how banks, insurers, and public authorities can compute insights on encrypted data to support compliance, fraud detection, and AI development. It includes practical deployment models, regulatory use cases, and technical architecture diagrams showing how secure enclaves and cryptographic computation interoperate.

Download the PDF to learn how Confidential Computing with Partisia enables secure data collaboration across borders, reduces privacy risk, and builds measurable trust with regulators and partners.

Reasons to integrate Condential Computing in to your business-model

Five key features to why you should implement Condential Computing as a pivotal part of your company’s decisions making strategy ...

Built on technology that ensures privacy, security and trust

With MPC, data is encrypted directly on the company’s servers, within its existing security procedures. This encrypted data is split into so-called secret shares. The shares are then distributed and processed across multiple secure nodes, ensuring that even if one node is compromised, the data still remains protected and cannot be reconstructed.

Blockchain Integration - Flexible Governance

All decisions made by data providers are logged on the blockchain, with results recorded in a secure, unalterable manner. This adds an additional layer of security and accountability, reinforcing the platform's integrity.

Industry Use Cases

Financial institutions, tax authorities, and central banks require detailed reporting and analysis of financial transactions.

Confidential Computing executed on the Partisia Platform assess market health or do Anti-Money laundering across multiple institution’s data without privacy breaches nor giving each other access to commercially confidential data.