Project cooperationUpdated on 26 January 2026
Partner Search - HORIZON-MISS-2027-01-CLIMA-02: Researching and applying the potential of Artificial Intelligence to foster climate resilience
Innovation Manager at Bondalti Water
Lisbon, Portugal
About
Bondalti Water offers an industrial sector anchor (water management and water-related infrastructure) and an AI/data integration capability to develop and validate AI tools that (i) improve actionable adaptation knowledge for regional/local decision-making, and/or (ii) strengthen sectoral climate resilience through AI-enabled optimisation and digital transformation.
We are well positioned to support Objective 2 (“AI for sectoral adaptation”) in the water management / wastewater management domain explicitly listed as a relevant sector.
What we can contribute (work packages / tasks)
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Objective 2 demonstrators (water sector): develop and test AI tools that support climate-resilient operation of water/wastewater assets (e.g., drought/low-flow operation, storm overflow risk, influent variability, energy and chemical efficiency under stress). Testing can be organised with at least 5 regional/local authorities, as required by the topic.
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Objective 1 support (“AI for more accessible data”): AI methods to improve data integrity, accessibility and usability for decision-makers (harmonising heterogeneous sensor/operational datasets; uncertainty-aware indicators; interpretable outputs), tested with at least 3 authorities.
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Operational integration: deployment-ready integration with local authority workflows (dashboards, alarms, scenario testing), embedding climate data into decision-making processes, aligned with the expected outcomes.
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Data pipelines, monitoring and risk assessment alignment: contribution to monitoring approaches compatible with Mission expectations (including links to the Mission Implementation Platform; use of recognised frameworks referenced by the call, where relevant).
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Responsible AI: practical measures to avoid bias, ensure representativeness, and manage limitations/misinformation risks when using generative AI, as explicitly requested.
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Training and dissemination packages: end-user training materials for regions and local authorities on adopting and operating the AI-powered improvements.
Assets
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Strong field experience in continuous monitoring and robust operations in harsh aqueous environments (fouling-prone, variable loads), and in turning operational data into decision support.
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In-house capabilities in data engineering, time-series analytics, hybrid/digital-twin modelling, and OT/IT integration relevant to local infrastructure operators.
Partners sought
We seek consortia including:
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Regional/local authorities (demonstration territories) to satisfy the minimum testing requirements (≥3 for Objective 1; ≥5 for Objective 2).
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AI/ML research teams (incl. deep learning, trustworthy/causal ML, uncertainty quantification), climate service and risk-modelling experts, and dissemination/SSH partners.
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Sector technology partners (utilities, infrastructure operators, solution providers) to ensure scalability and uptake, consistent with the topic’s expectations for Objective 2.
Keywords / tags
AI for climate adaptation; climate resilience; regional/local decision support; water management; wastewater management; extreme events; data integrity & accessibility; interpretable AI; uncertainty-aware indicators; digital transformation; trustworthy/generative AI safeguards; training & dissemination; Mission Implementation Platform links..
Organisation
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