Confidential Computing
Confidential Computing
Partisia Confidential Computing lets enterprises process encrypted data securely, ensuring privacy, compliance, and full confidence without compromise.
Trusted by enterprises, governments, and research institutions
Secure collaboration across datasets and organizations
Partisia Confidential Computing performs computations on encrypted data without ever breaching the regulations or privacy of the information. The platform enables organizations to compute on protected data, so any enterprise can use all of its data with full confidence and without compromise.
Imagine doing computations on all the world's data while still protecting the privacy of the information. Data stays encrypted at rest, in transit, and — with confidential computing — even in use, to comply with the strictest regulations and to enable collaboration without compromise.
Confidential data collaboration without compromise
The Partisia Confidential Computing platform provides an easy programmable solution for computing on encrypted data. It facilitates large private and public data providers to collaborate around activating confidential data using a combination of MPC and federated or local computations.
The UI provides an easy way to connect to external data sources and Business Intelligence (BI) tools. Blockchain-based orchestration ensures transparent and trustworthy collaboration between data providers and other users of the system.
Characteristics
What sets Partisia Confidential Computing apart from traditional data platforms.
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Encrypted by default
All data can be computed on directly in encrypted form.
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Full auditability
Auditable trail of all use, making regulatory compliance seamless.
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Flexible programming model
Computations are defined using Rust, Java, or bespoke frontends.
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Data and BI integrations
Integrates with most data sources and Business Intelligence tools.
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Authentication and authorization
Plug into existing identity and access control systems.
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Deploy anywhere
Run on-premise or in any major cloud.
Case studies
How organizations use Partisia Confidential Computing in production.
Virtual Public Register
The VPR Platform facilitates confidential computing and collaboration across public registers — virtually combining and using public registers without exposing the underlying data. Matured for commercial use through R&D projects funded by the Danish Industry Foundation and Innovation Fund Denmark, the VPR is operated by the Danish Health Data Organization (SDS) and Statistics Denmark (DST). The OSCAR Project builds a commercial platform around the VPR with template healthcare analyses for third-party analysts. The potential is real-time analysis on highly sensitive data that is otherwise time-consuming and expensive to access.
Financial Fraud Detection
Financial fraud costs trillions of dollars globally and fuels organized crime. Most fraud passes through banks, but detection today happens within a single bank with too little information. Confidential Computing lets the Partisia Platform and MPC use confidential data across banks, regulators, and jurisdictions without violating competition rules or individuals' right to privacy. Recently, the FCA hosted an event where Partisia developed a PoC in close collaboration with Goldman Sachs, Deloitte, Sedicii, and Ex Ante Advisory.
Use cases
Where Partisia Confidential Computing unlocks data that was previously off-limits.
Health and Pharma
Valuable, well-structured data collected over decades by health authorities and national statistics agencies can now be shared without revealing it. Pharma companies and national drug procurement get insights on drug development, usage, and effects much faster and cheaper. Ongoing R&D in Denmark aims to turn the country into one big privacy-preserved phase 4 drug study.
Fraud Detection
Financial institutions can perform risk assessments and fraud detection on their confidential data, even sharing across multiple institutions without any party learning anything about another. Multiple data silos can be merged without ever breaching the confidentiality of the information.
Training AI
Combining MPC and federated machine learning enables faster privacy-preserving training of AI models. Heavy training happens distributed on the data providers' own data, and insights are combined with MPC. Together, these Privacy Enhancing Technologies activate better and more sensitive data for training AI models.
Confidential data collaboration among organizations holds tremendous potential. Enabling independent organizations to work privacy-preserving on joint data without regulatory or antitrust challenges is a game changer.
How to deploy
Three deployment scenarios for Partisia Confidential Computing — pick the one that maps to how your organization works with data.
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Deploy and operate as a single entity
The customer downloads the software and deploys, with a single click, a network controlled entirely by the customer.
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Join an operational network as a node operator
The customer is invited to an existing network and downloads the software, deployed with a single click.
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Join an operational network
A network of node operators already runs the Partisia Platform. Integration is reduced to wiring up APIs or building tailored services using the built-in smart contract language.
FAQ
Basic knowledge about confidential computing
How does Partisia ensure the privacy of data during computation?
Partisia employs Multi-Party Computation (MPC) protocols, allowing computations to be performed on encrypted data without exposing the underlying information. This ensures data remains confidential throughout the process.
Can Partisia's platform integrate with our existing security infrastructure?
Yes. The platform supports integration with various authentication and authorization systems, enabling organizations to manage access controls effectively within their existing security frameworks.
What measures are in place to prevent unauthorized data access?
The platform incorporates robust authentication and authorization mechanisms, ensuring that only authorized personnel can access and perform computations on sensitive data. Blockchain-based orchestration also provides a transparent and auditable trail of all data interactions.
How does the platform handle regulatory compliance?
The Partisia Platform is designed with compliance in mind, offering full auditability of data usage and integrating anonymization techniques like k-anonymity. This facilitates adherence to stringent data protection regulations and privacy laws.
Is it possible to deploy the platform on-premises?
Yes. The platform offers flexible deployment options, including on-premises installations and cloud-based solutions, so organizations can choose the setup that best aligns with their security policies and operational requirements.
Why work with Partisia?
Partisia was founded in 2008 by global pioneers in Multi-Party Computation and advanced cryptography. Our core mission is to integrate Privacy Enhancing Technologies that improve decision-making and product development.
We empower companies to operate and compute on encrypted data — a platform where data from individuals, governments and private companies stays encrypted and protected, and still fully usable. Choose Partisia and get a partner built on expertise, know-how, and trust.