With AI, Himanshu Gupta is giving the climate forecast for supplychains a makeover
Himanshu Gupta knows full well the heavy toll climate change is taking on agriculture. Growing up in India and eventually working in public policy, he saw how the unpredictably late monsoon season was damaging crops and worsening farmers’ lives.
“I always knew there was a big problem,” he said of the climate change-fueled dangers to agricultural commodities like cotton and the resulting impact on livelihoods.
“The question was, ‘Do we have the technology to solve this?’”
That eventually led him to co-found ClimateAi, a Bay Area-based startup that aims to help farms and other businesses prepare for a hotter, more disruptive climate using the power of artificial intelligence. By harnessing machine learning models, the company says its customers can anticipate and prepare for climate risks to their supply chains and operations over periods ranging from weeks to seasons.
That timeframe, Gupta said, is traditionally a modeling blindspot for climate forecasters without access to AI-powered tools.
Forecasting extreme weather events like hurricanes and heat waves for hyper-specific geographies weeks to seasons ahead is difficult to do accurately. But having sufficient time to prepare for a natural disaster can be the difference between averting catastrophe and not.
If you tell a company’s supply chain manager a heat wave is approaching that may impact their cotton supply chain a week before it arrives, Gupta said, that isn’t enough time to move inventory or prepare in other ways. “But if you were to tell them that there's a higher risk of a heat wave in the next season in this area where we think that cotton yield might be down, this becomes very actionable for them,” he added.
ClimateAi created deep learning models,
