Imagine a digital vault where different organizations can put their secret data to train an AI, but no one—not even the people running the vault—can actually see the raw information. It uses special hardware locks and a digital ledger to track exactly who did what, ensuring everything is legal and private. It's like a group of banks collaborating to find fraud without ever showing each other their customer lists.
Organizations cannot collaborate on sensitive data because of strict privacy laws and the risk of data leaks. Current cloud solutions often require trusting the provider with raw data, which is a legal and security deal-breaker for government and health sectors.
A Confidential Computing and Secure Multi-party Execution Platform. This is an open-source tool for collaborative AI that keeps data encrypted even during processing.
If you are a medical research organization dealing with strict patient privacy laws—this project developed a confidential computing platform that allows multi-party analysis of sensitive health data without exposing individual records.
If you are a government agency dealing with cross-border data sharing restrictions—this project developed a secure data sharing platform that ensures compliance with EU and national data protection laws.
If you are a cloud service provider dealing with clients who distrust shared infrastructure—this project developed zero-trust cloud topologies and remote attestation to prove the security of the computing environment.
Based on available project data, the platform is being developed as an open-source implementation, but specific pricing or commercial costs are not mentioned.
The project aims for community adoption through open-source artefacts and is being demonstrated in vertical cross-border scenarios for public administration and healthcare.
The project explicitly mentions an open-source implementation of the platform for collaborative AI, suggesting a permissive licensing model.
It includes a legal framework for compliance with national and EU data protection legislation for cloud-based processing in local and cross-border settings.
The solution is designed to be compatible with the EOSC Interoperability Framework across technical, semantic, organisational, and legal layers.
The consortium is heavily weighted toward commercial application, with a 50% industry ratio (8 industry partners out of 16). The presence of 5 SMEs suggests a focus on agile development and market entry, while the 10-country spread indicates a strong push for cross-border interoperability and EU-wide legal compliance.
Contact Universidad de Murcia regarding the TITAN project
Contact us to explore integrating TITAN's open-source confidential computing tools into your data pipeline.
