CORRELATE AS

Their core work

CORRELATE AS is a Norwegian technology SME that applies data analytics and machine learning to complex, data-rich problems where conventional methods struggle to find patterns. In food systems, they work on digitising and making sense of city-region supply chains — traceability, sustainability metrics, and ecosystem service valuation. In health, they build advanced predictive models for diagnosing multifactorial diseases such as endometriosis, where symptoms are diffuse and diagnosis is typically delayed by years. The thread connecting these domains is their ability to extract actionable insight from messy, multi-source data and translate it into tools that support real decisions.

What they specialise in

How they've shifted over time

CORRELATE AS entered H2020 through the food and environment domain, contributing to city-region food system design with blockchain traceability and nature-based solutions thinking — a sustainability-and-resilience framing. By their second project, starting in 2021, the focus had shifted sharply to digital health: machine learning applied to endometriosis, complex multifactorial disease, and clinical decision support. Whether this reflects a strategic pivot toward health AI or simply reflects opportunistic project pursuit is unclear from the data alone, but the trajectory points firmly away from food systems and toward data-driven medical applications.

CORRELATE AS is moving toward digital health and predictive clinical modelling — their most recent project targets one of the most underdiagnosed conditions in women's health using machine learning, which is a high-growth and high-impact area.

How they like to work

CORRELATE AS has only ever joined projects as a participant, never leading as coordinator — this is consistent with a specialist contributor that brings targeted technical capability rather than consortium management experience. Both of their projects sit within large, geographically diverse consortia (57 unique partners across 23 countries from just two projects), meaning they are comfortable operating as one node among many. Prospective partners should expect a technically focused collaborator that integrates well into large consortia but is unlikely to drive project governance or dissemination.

Through just two projects, CORRELATE AS has been exposed to 57 distinct consortium partners spanning 23 countries — an unusually broad network for such a small project portfolio, reflecting participation in large pan-European collaborative actions. Their reach is solidly European with the geographic spread typical of H2020 RIA and IA consortia.

What sets them apart

CORRELATE AS occupies a genuinely unusual position as a small Norwegian SME with demonstrated H2020 credibility in both agri-food digital innovation and medical machine learning — domains that rarely overlap in a single organisation's portfolio. For consortium builders in digital health who need a partner that also understands food system complexity (relevant, for example, in nutrition-disease research), this cross-domain profile is hard to find. As a Norwegian EEA-based company they also broaden the geographic footprint of consortia without consuming Horizon budget reserved for EU Member States.

Highlights from their portfolio

• FEMaLe
  Applies machine learning to endometriosis — a condition affecting roughly 10% of women globally but averaging 7-10 years to diagnose — making this one of the higher-impact clinical AI applications in H2020 health research.
• CITIES2030
  Their largest project by funding (EUR 308,350) and the broadest in scope, combining blockchain traceability, nature-based solutions, and food security modelling across European city-regions within a single integrated framework.