Objective
Paramorph is an advanced AI optimisation technology developed by Inephany to improve neural network training efficiency and efficacy. Training modern AI models is costly, time intensive, and energy demanding. Current practice relies on launching many separate runs with fixed hyperparameters to identify suitable configurations. This process consumes substantial GPU resources, increases financial and environmental costs and may yield suboptimal models.
Paramorph replaces this multirun trial approach with real time adaptive control within a single training run. Using a proprietary multi-agent reinforcement learning framework, it adjusts key hyperparameters at the level of individual model layers as training progresses. This enables fine-grained, continuous, learned optimisation during execution. No existing deployed solution provides real time, layer level, learned hyperparameter control within one training run.
The technology has demonstrated up to 3.5x faster convergence compared to widely used optimisers such as Adam under standard settings. Validation has been conducted on transformer models including GPT 2 and OLMo. Paramorph has reached TRL5 and is supported by an EU patent application, trade secrets, and a proprietary dataset covering more than 2,800 model configurations.
The target market includes AI research organisations, foundation model developers, quantitative finance firms, biotechnology companies, and enterprises operating compute intensive AI workloads. Paramorph reduces required experiments and shortens training time, lowering compute expenditure and energy consumption. Efficiency gains of up to 5x in large scale training could reduce carbon emissions by several thousand tonnes per cycle.
Support from the EIC will enable progression to TRL8 through large scale experimentation and structured enterprise pilots, de-risking the technology, unlocking private investment, and strengthening Europe’s position in sustainable, competitive AI infrastructure.
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.
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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HORIZON.3.1.2 - The Accelerator
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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-EIC-ACC - HORIZON EIC Accelerator
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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) HORIZON-EIC-2026-ACCELERATOR-02
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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.
WC2B 6NH London
United Kingdom
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.