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Home / Horizon Europe / HORIZON-CL5-2026-11-D3-23

Data sharing to support the training and development of AI foundation models in the energy sector

Open now · HORIZON Innovation Actions · HORIZON-CL5-2026-11-D3-23

Next cut-off
01 Dec '26
in 86 days
Per grant
€10M
the call's own average
Grants expected
3
projects that will be funded
Funding rate
70%
the rest is your own money

In context of Horizon Europe

This grant€10M
The track runs to the largest grant in Horizon Europe (€171M). The median across the 482 calls we publish is €5.3M, this one is above it.

What this call funds

Expected Outcome:

Projects are expected to contribute to all the following expected outcomes:

  • Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security.
  • Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency.
  • Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange.
  • Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution.

Scope:

The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus areas of the energy sector. Projects are expected to:

  • Building on the results of previously funded projects on the Common European energy data space[1] as well as the ongoing work within the Data 4 Energy expert group, projects are expected to demonstrate innovative methods and data governance strategies for sharing data among various energy actors. Projects are expected to demonstrate that they have access to large relevant datasets at the time of submitting the proposal.

Trimmed here, the full scope, expected outcomes and award criteria are on the official topic page ↗.

What applying costs you

ItemEstimateNote
Drafting effort6–8 weekssingle submission
Partner search4–8 weeksruns in parallel, and it is the part that slips
Your own money€4.3M30% of project cost, over the project's life
Time to first payment6–9 monthscut-off → evaluation → grant agreement

These are Bemzu's estimates from the call's structure (the number of stages and whether a consortium is required) not figures published by the Commission. Only the co-financing share is read from the call itself.

Where these conditions come from

Two kinds of row. Most are the sentence we read the condition from, quoted out of the call itself. Some say plainly that they are not a quotation but the programme's own rule for this type of action, the EU portal publishes a table of contents where the conditions should be, so for a Research and Innovation Action the rate comes from the rulebook rather than from the fiche.

ConditionQuoted from the call, or the rule behind it
Consortium sizeNot quoted from this call — Innovation Actions under the Horizon Europe rules are at least three independent legal entities from three different Member States or Associated Countries, at least one established in a Member State.
Funding rateNot quoted from this call — Innovation Actions under the Horizon Europe rules are funded at 70% of eligible costs for profit-making organisations, and 100% for non-profit legal entities — the rate shown here is the one that applies to a company.
MaturityTechnology Readiness Level - Technology readiness level expected from completed projects Activities are expected to achieve TRL 7-8 by the end of the project – see General Annex B.

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