Both PERSIST and GenoMed4ALL required cross-institutional data sharing infrastructure, with interoperability listed as a keyword in PERSIST.
ENTERPRISE SOLUTIONS CONSULTORIA Y APLICACIONES
Spanish IT consultancy providing federated learning, health data interoperability, and privacy-compliant infrastructure for EU biomedical research consortia.
Their core work
Enterprise Solutions Consultoria y Aplicaciones is a Spanish IT and data solutions company based in Zaragoza that specializes in health data systems for clinical research environments. Their work focuses on building interoperable, privacy-compliant data infrastructure for large-scale EU medical research projects — specifically platforms where sensitive patient or genomic data must flow between hospitals, research centers, and AI systems across multiple countries. They operate as technical service providers contracted directly by research consortia, supplying software tools, data pipelines, or integration components rather than leading the research themselves. Their projects sit at the intersection of health informatics, AI/ML (particularly federated learning), and regulatory compliance for biomedical data.
What they specialise in
PERSIST explicitly lists privacy, security and ethics as a keyword domain, reflecting work on GDPR-compliant clinical data handling.
GenoMed4ALL applies federated learning to genomic and haematological disease data, signaling a move into privacy-preserving ML architecture.
PERSIST (2020–2023) built Big Data and AI infrastructure for patient-centered survivorship care plans after cancer treatment.
GenoMed4ALL (2021–2025) targets genomics and personalized medicine for haematological diseases using multi-omics data integration.
How they've shifted over time
Their earliest H2020 engagement (PERSIST, 2020) was grounded in practical clinical data challenges: making cancer patient records interoperable across care settings, while navigating privacy and ethics constraints — a compliance-heavy, systems-integration focus. Their subsequent project (GenoMed4ALL, 2021) marks a clear technical deepening: the focus shifted to federated learning and multi-omics, placing them in more computationally advanced territory where distributed AI models are trained on genomic data without centralizing sensitive records. The trajectory is from "connecting health data systems" toward "enabling privacy-safe AI on genomic data" — a meaningful upskill in both the ML and regulatory complexity of their work.
They are moving from health data integration toward federated machine learning on genomic datasets — a high-demand niche as EU precision medicine initiatives scale up under GDPR constraints.
How they like to work
This organization participates exclusively as a third party in EU projects — meaning they are contracted by consortium members to deliver specific technical services rather than holding a formal partner seat. This model is typical of specialized IT vendors who provide platforms or tools to research consortia without taking on the administrative burden of full consortium membership. Working with them likely means engaging them as a service provider or subcontractor rather than co-applicant, which can simplify onboarding but limits their institutional commitment to project governance.
Despite only two projects and no direct EC funding, they have been exposed to a network of 41 unique consortium partners across 16 countries — a broad European footprint for an organization of their size. This suggests their technical services were valued enough to be included in geographically diverse, multi-partner consortia.
What sets them apart
Enterprise Solutions stands out as a pure technical enabler in health research consortia: a private company that plugs in as a third-party specialist rather than chasing coordinator roles or EC funding directly. This positions them as a pragmatic, low-friction partner for consortia that need specific IT capabilities — health data pipelines, federated learning infrastructure, GDPR compliance tooling — without the overhead of a full research partner. For any consortium building a precision medicine or genomic data project that needs proven health informatics support from a Spanish SME-adjacent company, they fill a specific and hard-to-replace niche.
Highlights from their portfolio
- GenoMed4ALLA 2021–2025 RIA applying federated learning to genomics and AI-driven personalized medicine for haematological diseases — one of the more technically ambitious precision medicine projects in the H2020 health portfolio.
- PERSISTA 2020–2023 RIA building Big Data and AI infrastructure for cancer survivorship care plans, directly addressing post-treatment patient follow-up — a significant real-world clinical application with strong health system relevance.