FAME Kickoff meting in Rome (16-17 March, 2023)
FAME is a joint effort of world-class experts in data management, data technologies, the data economy and digital finance to develop, deploy and launch to the global market a unique, open, publicly accessible, trustworthy, energy efficient, and secure federated data marketplace for EmFi, which will offer novel decentralized programmable pricing and trading of data assets.
The FAME data marketplace will alleviate the proclaimed limitations of centralized cloud marketplaces towards demonstrating the full potential of the data economy.
Our role
Evidenleads the FAME analytics toolbox, focused on cataloguing AI/ML techniques for EmFi use cases and deploying configurations for energy-efficient and sustainable cloud/edge computing applications.
Related News
Eviden hosts FAME's 9th GA in Madrid
The meeting brought together 35 partner organisations, both in person and remotely, to report on the project's progress.
Unlocking customer behavioral insights
A case study by our Trustworthy AI team in the FAME blog
FAME: New article and video
Unlocking efficiency with Marketplace Assets: a case study on FAME Marketplace is the title of an article published on the FAME project blog - written by Raquel Lazcano, Trustworth
Related Publications
A case study on FAME Marketplace for unlocking customer behavioral insights
FAME project - blog
This blogpost explains how the FAME Marketplace offers pre-built analytical tools for effective customer segmentation, and explore two use cases: improving financial recommendations and developing loyalty programs for parking in Athens.
Unlocking efficiency with Marketplace Assets: a case study on FAME Marketplace
FAME project - blog
In today’s ever-changing technological landscape, companies are constantly looking for innovative ways to increase efficiency and minimize costs, and even more nowadays with the advent of artificial intelligence and large language models.
C4 Model: A Research Guide for Designing Software Architectures
8th International Conference on Software and System Engineering (ICoSSE 2025), Nice, France
Given nowadays increasing complexity of software systems, their architectural design prior to their actual implementation becomes quite complicated.
Preserving data privacy in Machine Learning pipelines with Federated Learning
FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.
Flexible robots for intelligent automation of precision agriculture operations
CORDIS - EU Research Results
Artificial intelligence helps coordinate precision agriculture tasks
Leveraging Large Language Models for Financial Predictions
FAME project blog
In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.