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Consortium Studio

Focus Areas

Four thematic clusters where MediSea is happy to coordinate or join. We pick consortia that fit at least one of these clusters; we politely decline the rest.

Why only four

Credible consortia need a coordinator who has lived in the domain. We hold the scope narrow on purpose so we can carry the governance story, the technical orchestration, and the MRVMRVMeasurement, Reporting, and Verification: the evidence pipeline that turns impact claims into auditable numbers; core to climate, biodiversity and impact-investing due diligence. evidence layer without subcontracting any of them. If your idea lands outside these four clusters, we will say so on the first scoping call instead of selling you a fixed-price engagement that should not happen.

Cluster 01

Trustworthy and governed AI in regulated environmentsGovernance-aware AIAI that knows about the rules it operates under: policies, approval boundaries, risk thresholds, logging requirements, and who is accountable for each decision. Governance is built into the system rather than added after the fact.

Explainable assistant systems for operators in maritime, energy, and public-sector settings. Tool-contract schemas and least-privilege policy engines acting as a safety kernel for autonomous operations.

What we bring

  • Governance-aware orchestration layer between AI services, hardware, and human oversight.
  • Auditable decision flows that survive a regulator walking in.
  • Edge-first inference patterns where latency and data sovereignty matter.

Partners we want

  • Domain experts in regulated maritime, offshore energy, or public-safety operations.
  • Research groups working on explainability, policy engines, or formal verification.
  • Operators willing to host pilots and contribute use-case telemetry.

Calls that fit

  • Horizon CL5 D5-10 (ZEWT, two-stage).
  • MSCA Doctoral Networks on AI governance and embedded AI.
  • Cascade-funded cybersecurity assessment opportunities.

Cluster 02

Multi-agent systems and knowledge integrationMulti-agent systemsSoftware architectures where several cooperating AI agents each handle a specialised task and hand off work between themselves under coordination rules, producing richer behaviour than any single agent could deliver alone.

Bio-inspired knowledge integration and large-scale multi-agent simulations as the backbone for coordinated robotics across sectors. Tools that let teams of agents and humans share context without bespoke glue per deployment.

What we bring

  • Composable multi-agent stacks: orchestration, message contracts, and conflict-resolution patterns we have refined across pilots.
  • Simulation-to-deployment harnesses so the agents you test are the agents you ship.
  • Knowledge-graph layers for cross-source evidence (sensor, regulatory, operator).

Partners we want

  • Robotics groups with strong perception or planning stacks but limited orchestration capacity.
  • Knowledge-graph and ontology specialists, especially in the marine and earth-observation domains.
  • Industrial partners with multi-asset estates where coordination beats per-asset point solutions.

Calls that fit

  • Horizon Mission Ocean OCEAN-04 (testing-site network).
  • Horizon CL6 ZEROPOLLUTION-01 (multi-agent monitoring).
  • Digital Europe Programme through EDIH access for capacity building.

Cluster 03

Blue economy and zero-pollution applicationsBlue EconomyOcean-based economic activities managed sustainably (for example offshore energy, shipping, aquaculture); often a test bed for governance and technical solutions that can extend to other sectors.

Concrete robotics applications for the blue economy: AI-assisted inspection for offshore oil and gas, renewable-energy monitoring for offshore wind, and data-driven mooring reliability for aquaculture. Always with environmental constraints and regulator-grade record keeping.

What we bring

  • FPSO mooring chain inspection workflows with earlier anomaly detection and lower diver exposure.
  • Offshore wind-farm monitoring designs that combine fixed sensors and mobile robots.
  • Aquaculture mooring reliability and zero-pollution evidence pipelines.

Partners we want

  • FPSO operators, offshore-wind asset owners, and large-scale aquaculture sites.
  • MRV specialists, environmental consultancies, and marine survey companies.
  • Civil-society partners on coastal communities and marine biodiversity.

Calls that fit

  • Horizon Mission Ocean OCEAN-01 (habitat mapping).
  • Horizon CL6 ZEROPOLLUTION-01 (source-to-sea).
  • Clean Industrial Deal CID-01 / 02 for decarbonisation-aligned demos.

Cluster 04

Explainable AI for operator training and MRVExplainable AI (XAI)AI systems designed so humans can understand why a decision or output was produced: visible reasoning steps, evidence citations, and behaviour traces that support review and trust.

The human-and-evidence layer that every robotics rollout eventually needs. Training simulators that explain themselves, monitoring-reporting-verification pipelines that hold up to audit, and assistant systems that respect the operator's mental model.

What we bring

  • Explainable assistant UI patterns that surface model uncertainty without overwhelming the operator.
  • Training simulators with auditable decision flows for offshore, port, and aquaculture crews.
  • MRV evidence pipelines: sensor capture, lineage, retention, and regulator-grade export.

Partners we want

  • Training providers, vocational schools, and maritime academies.
  • MRV consultancies, certification bodies, and standards organisations.
  • Behavioural-science researchers focused on human-AI teaming in safety-critical settings.

Calls that fit

  • MSCA Doctoral Networks on AI governance and embedded AI.
  • Digital Europe Programme operator-upskilling and EDIH capacity calls.
  • Erasmus+ Sector Skills Alliances for maritime workforce transitions.

See also

  • Programme Pathways for the calls each cluster maps onto.
  • Projects and publications for the underlying work that gives each cluster its evidence base.
  • Whitepaper for the technical framing of the orchestration layer and explainable AIExplainable AI (XAI)AI systems designed so humans can understand why a decision or output was produced: visible reasoning steps, evidence citations, and behaviour traces that support review and trust. story.

Have a project that fits one of these?

Tell us the cluster, the call, and what you bring. We reply within three working days, or earlier if a deadline is tight.

Start or join a consortium