Pillars
Data Space Innovation is Driven by Digital Technologies.
We develop advanced digital technologies that facilitate interoperability, security, and efficient data management. These solutions enable companies and organizations to connect, exchange and process large volumes of data, and extract valuable insights to improve their operations and boost competitiveness.
Trust and Traceability through Blockchain and DLT Technology
The combination of these technologies enables the secure recording of data transactions, ensuring traceability, transparency, and fostering a trusted environment among participants in the AIR Zamora ecosystem.
DID, Decentralized Identifier
A unique identifier that gives individuals or organizations full control over their identity, acting as a “digital passport” within the space.
Smart Contracts
Programmes that run automatically when certain predefined conditions are met. In this case, Solidity, your ‘digital fingerprint’ (hash) is anchored in the Blockchain, making the terms unalterable and verifiable.
Clearing House
This role uses DLT technology to record agreements immutably, ensure policy compliance, and act as a neutral arbitrator, providing transparency and trust in validation and dispute resolution.
Collaborative AI and Federated Learning
Collaborative AI and Federated learning enable the training of AI models on data distributed across multiple entities, without the need to centralize it. This approach protects privacy and intellectual property, fosters cooperation between organizations, and improves model quality by leveraging diverse information without compromising data security.
Federated Learning
An advanced AI technique that enables models to be trained in a distributed and secure manner. Instead of sharing the original data, only the model parameters or “learnings” are transmitted, protecting data privacy and ensuring compliance with regulations such as GDPR. This approach is ideal for organizations seeking AI collaboration without compromising data security.
FL-Orchestrator
Innovates in Federated Learning by using Smart Contracts to coordinate the entire training lifecycle in a decentralized manner. It securely registers participants, manages training rounds, and automatically aggregates results, ensuring transparency, traceability, and efficiency at every stage.
Generative AI
An advanced technique that enhances the quality and accuracy of AI models by integrating Large Language Models (LLMs) with vector databases. This combination allows the development of question-answering systems capable of querying distributed information within the data space and providing contextual, accurate, real-time responses.
Flexibility (BYOA)
Our Application Protocol allows users to implement their own Bring Your Own Algorithm (BYOA) approach, running algorithms in secure containers without modifying the original connector. This model ensures flexibility, interoperability, and security in using custom algorithms within the ecosystem.
Secure Value Exchange Protocols
A set of rules and standardized APIs that facilitate how participants and organizations interact, discover and share resources, and generate economic value efficiently and securely within the digital ecosystem.
Metadata Broker Protocol
A standardized protocol that allows connectors to register with a Broker and publish their data catalogs, making them easily visible and accessible to other ecosystem participants.
Application Protocol
Defines a standard API that allows connectors to process external logic, such as Federated Learning (FL) algorithms or advanced analytics processes, efficiently managing tasks and data flows within the ecosystem.
Payment Protocol
An integrated mechanism within data usage policies (Open Digital Rights Language — ODRL) that enables monetization of data assets and analytical services, incorporating automated payment flows that ensure secure, transparent, and efficient transactions among ecosystem participants.