The AI-driven SaaS product uses climate risk modeling to provide short- and long-term insights into weather and climate impact for food and beverage companies, helping businesses identify the actions needed today to adapt to climate change disruptions. For McCain, ClimateAi assessed risks for its crops in various geographic regions of focus and provided McCain with detailed recommendations on how it should adapt its practices to maintain yields and value at a microclimate level. That included potential financial impact as well. 

“We believe adaptation is of the utmost importance and urgency in the fight against climate change,” said Himanshu Gupta, cofounder and chief executive officer of ClimateAi. “We scan for a wide range of agriculture-specific risks, which is key for management decisions.”

Gupta explained that the product looks at risks including meteorological and climate information—air temperature, precipitation, soil temperature, relative humidity, evapotranspiration, solar radiation, and wind speed—as well as crop development stages including pest and disease pressures, location-specific attributes such as elevation and diurnal temperature shifts, and economic and financial data to break down how each impacts crop production and its resulting supply chain. The software forecasts extreme weather events from two weeks to 20 years out and uses machine learning to recommend actions. It’s all showcased in an easy-to-understand, filterable computer dashboard that’s customizable by region, timeline, and specific crop. 

For his clients, the access to this critical information has resulted in investments in heat-tolerant cranberries, development of climate-resistant seeds, and some serious ROI: Gupta calculates that clients see a 10- to 17-times return on every dollar they spend on his technology.

“Machine learning models are able to automate and speed up this process with the determination of the future regional climate conditions and which traits will be the most optimal,” Gupta said. “This enables farms to adapt quicker.”

ClimateAi holds five patents for its technology, which includes physics-driven AI, a machine learning hybrid technique used by self-driving cars. It’s essentially a neural network that understands climate physics to general forecasts. Clients can add proprietary data to create more accurate, hyperlocal forecasts at hourly, seasonal, yearly, and decadal time scales. To date, ClimateAi has pulled data from 35 countries for more than 40 different crops, servicing more than 20 major industry food brands, like McCain Foods, The Wonderful Company, and its subsidiary, Justin Vineyards and Winery. 

Gupta explained that ClimateAi’s machine learning technology is also integral to research and development teams at food companies to understand what risks are facing production and supply chains in the next decade. One is to identify new seed varieties that may fare better in changing environments. In the past, it would take seed companies years to undergo several rounds of trials to understand the seed traits needed to grow well in any one microclimate. Now, he said, AI technology can take on this task—and speed it up. He is seeing companies develop more climate-resistant seeds in a much shorter time and at a much lower cost. 

At Advanta Seeds, a developer of high-performance agricultural seeds, ClimateAi’s predictive modeling was influential on two recent occasions with very real financial losses at stake. First, the software informed Advanta’s operations team of wet conditions that would affect the harvest, allowing them to harvest early to prevent the loss of product, worth hundreds of thousands of dollars. Similarly, ClimateAi forecasted an “unexpected precipitation event two months out in a key location before other tools,” Gupta said. The Advanta team sent seeds to those regional farm customers early so they could plant ahead of the precipitation. Gupta said this decision alone resulted in a 10% increase in sales for Advanta, and, possibly more important, built customer loyalty. 

To further guard against changing weather patterns, Gupta said his software is helping clients understand possible investment opportunities by noting lower-risk locations for future planting. By evaluating the risk exposure, the product helps customers vet potential sites and choose the one with the most meaningful climate risk outlook. This has been particularly welcomed by wine and spirits companies, who are looking at new opportunities in U.K. farmland that was previously unsuitable for grape growing for wine and seeking insights on barley production for whiskey. As it did with seeds, ClimateAi can point out wine grape varieties that will fare better given the uncertainty of climate change, like Marselan that’s being grown in Uruguay.

Gupta said that he is currently working on launching a ClimateAi impact product that will partner with government agencies. A native of India, Gupta previously worked with the Indian government on the 12th Five-Year Plan, a renewable energy vision, and conducted emissions modeling work for India’s submission to the Paris climate accord. Growing up there, he said he witnessed the struggles of the farming community, and now wants to find ways to deploy ClimateAi to farms in countries that have been most impacted by climate change. That sentiment is echoed by his cofounder, Max Evans, who remembers watching his family of farmers in Ecuador react to changing weather patterns there. 

“We’re already feeling these impacts in our supply chains and food security today,” Gupta said. “Our goal is to build resilience to these impacts, improve rural livelihoods, and help the players better understand, manage, and communicate climate risk.”