Objective
The rapid adoption of Large Language Models (LLMs) for text generation has created a critical tension between functionality and privacy: while users increasingly rely on services like ChatGPT for personal and business communications, such cloud-based systems require surrendering control of sensitive data to third-party companies, often outside EU jurisdiction. The PersonalAI project addresses this fundamental challenge by enabling fully private, on-device personalization of open-source LLMs, leveraging breakthrough compression and fine-tuning techniques developed in the PI's ERC Starting Grant ScaleML project. Our preliminary PanzaMail study showed that models fine-tuned on as few as 50-100 user emails can generate text closely following genuine user writing, while our novel RoSA method enables this personalization on commodity hardware—reducing computational requirements by over 90% compared to standard approaches.
The technical innovation of the PersonalAI proof-of-concept lies in a four-component system that triages queries by complexity, executes simple tasks locally with efficiently-trained personalized models, sanitizes sensitive information from complex queries before cloud processing, and re-personalizes external outputs to match user style. As such, PersonalAI targets the rapidly-expanding EU AI market, where data sovereignty and GDPR compliance are paramount, for both companies and individual users. It offers the first solution that combines the personalization quality of proprietary services with complete data privacy. The project assembles a world-class team including the PI, lead developer Eugenia Iofinova (architect of PanzaMail), and two MIT advisors with deep entrepreneurial expertise. By transforming academic breakthroughs into a commercially viable product, PersonalAI will establish a new paradigm where users maintain complete ownership of their data and AI models while accessing state-of-the-art text generation and model editing capabilities.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2025-POC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3400 Klosterneuburg
Austria
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.