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ClimateAi Unveils Breakthrough 1km Resolution Climate Risk Forecasting using Physics-Informed Machine LearningCovered by AP News

Researcher analyzing agricultural grains and legumes in the laboratory. Research and Development Team.

Make cost-effective, data-driven decisions in R&D projects that account for a changing climate

Understand the changing needs of your customers and ensure you’re investing in climate-resilient solutions.

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Common R&D Challenges

  • A lack of reliable insights into future climate conditions for location-based R&D projects incurs more expenses and lower ROI
  • Innovation efforts are stymied without aggregated data across teams to drive investment decisions for projects that occur decades before go-to-market
  • Without incorporating climate risk, R&D teams miss out on taking advantage of new funding opportunities

ClimateAi’s tools help R&D teams across industries better understand how climate conditions and key climate risks will evolve over the coming years so they can focus on innovating and adapting for the climate-changing future.

Make Cost-Effective Decisions in R&D with Climate Insights

wheat iconAgribusiness: Make cost-effective decisions around what traits and seeds to breed with insights into future climate conditions in end markets, and identify new markets for seeds based on emerging climate conditions.

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food and beverage icon Food & Beverage: Identify emerging markets and manage increasing inventory volatility in your supply chain

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Other Industries: Develop the products of the future with confidence by understanding the changing needs of your customers

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Assessing Current and Future Climate Risks–at a Fraction of the Time and Cost

A large multinational corporation with 11 divisions, including agricultural solutions, was noticing an increase in climate volatility, creating challenges for strategic planning for R&D. The company was looking for better tools for a more uncertain world and a partnership that would jointly inform decision-making.

In a trial engagement, ClimateAi was tasked with identifying suitable production locations for newly developed seed varieties in India — which would enable the company to more quickly, cost-effectively, and reliably launch new crops.

Learn how ClimateAi’s platform accomplished in a few hours what the company had worked on for several years, at 10% of the cost.

Read The Full Case Study

crop field with sustainable agriculture