ClimateAi brings AI-driven Growing Degree Days into daily farm and food operations

ClimateAi, a California-based agtech startup specializing in climate intelligence, is targeting one of agriculture’s most persistent operational challenges with the launch of a new Growing Degree Days (GDD) tool that integrates visualization, forecasting, and artificial intelligence directly into customer workflows. The product, unveiled in January 2026, aims to replace manual spreadsheets with actionable insights that help growers, processors, and food companies better plan harvest windows, manage disease risk, and coordinate labor and logistics, according to information published by AgFunderNews.

Growing Degree Days are a core metric in agriculture, widely used to estimate when crops will germinate, flower, and reach harvest, as well as to anticipate pest emergence. Despite their importance, many agricultural operations still rely on Excel spreadsheets and fragmented weather data to translate GDD information into decisions. ClimateAi’s new tool was developed in response to direct customer feedback highlighting this gap between data availability and practical usability.

“Over the past year it has been clear how important it is to be able to roll out AI tools very quickly to our customers,” Will Kletter, chief operating officer of ClimateAi, told AgFunderNews. He said that conversations with customers revealed GDD as a clear pain point, recalling that one grower told the company, “If you can get me off my Excel spreadsheet, I’ll be a customer for life.”

The new tool allows users to visualize GDD accumulation through graphs and field-level maps that track specific crop varieties and locations with daily updates. Beyond monitoring, ClimateAi has incorporated agentic AI capabilities designed to move the platform from passive reporting to active decision support. The system not only forecasts crop development stages with confidence levels but can also suggest actions or automate responses within operational planning.

GDD metrics are traditionally calculated by tracking the number of days when temperatures exceed a defined baseline, with accumulated heat serving as a proxy for plant development. While historical GDD data has long been used to estimate harvest timing, climate change has made historical averages less reliable. ClimateAi’s platform addresses this challenge by combining real-time data, long-range forecasts, and climate risk modeling to provide more adaptive projections.

More accurate harvest predictions have implications far beyond the farm gate. Kletter explained to AgFunderNews that processors and supply chain managers rely heavily on timing accuracy to manage capacity and logistics. In the case of a frozen vegetables customer, for example, the company needs to know how many trucks of peas will arrive at a processing facility on a given day and whether it has the capacity to freeze them at peak freshness and nutritional value.

One of ClimateAi’s food processing clients manages contracts with growers across multiple regions, tracking field locations, crop types, and planted acreage. Previously, this data was exported into spreadsheets, where staff manually added GDD calculations and attempted to model outcomes. With ClimateAi’s platform, all calculations are centralized, enabling the company to predict when crops will reach specific stages and aggregate data across fields to estimate daily volumes arriving at processing plants.

The tool also allows users to overlay crop-specific risk alerts, such as those related to extreme rainfall or temperature anomalies, providing additional context for planning. According to Kletter, this integrated view helps customers anticipate disruptions and adjust operations earlier, reducing both waste and cost.

ClimateAi is best known for its long-range weather forecasting capabilities and initially focused on large seed and agrochemical companies. However, the company has recently gained stronger traction among organizations that source agricultural commodities from large numbers of fields, including food processors and consumer packaged goods companies. These firms often face complex coordination challenges across procurement, production, and sustainability teams.

Kletter described an ongoing organizational shift within the food industry, where procurement and sustainability functions are increasingly converging. He said this reflects a broader recognition that climate is no longer a peripheral concern but a core business variable influencing both operational and strategic decisions. As a result, customers are seeking tools that embed climate intelligence directly into their day-to-day workflows rather than treating it as a separate analytical layer.

“Originally, we were trying to start a conversation about how extreme weather and climate is becoming a core business variable,” Kletter said in comments reported by AgFunderNews. “The key question now is how this becomes deeply integrated into our customers’ daily workflows.”

The rapid deployment of AI tools has been central to this strategy. While ClimateAi has expanded its technical team, the company has also leveraged AI-assisted coding tools to enable subject matter experts to build new features more quickly. According to Kletter, this has blurred traditional role boundaries, allowing data scientists to function as software engineers and accelerating product development.

A key component of the new offering is the introduction of AI agronomy agents. These agents can be trained by customers to reflect their specific crops, regions, and management practices. When the platform identifies a potential risk—such as heavy rainfall during planting—the AI agent does more than issue an alert. It can provide recommendations on how to respond, turning predictive insights into practical guidance.

While some customers value ClimateAi’s detailed, graph-heavy reports, Kletter noted that many also prefer information delivered in clear, accessible language. The platform therefore includes natural language summaries that highlight key insights and recommended actions, making the data easier to interpret for a broader range of users, from growers to sourcing managers.

The company began offering free trials of the new GDD tool following a recent webinar and received more than 20 immediate sign-ups, spanning row crops, potatoes, specialty vegetables, and wine production. This early interest has provided ClimateAi with rapid feedback from diverse agricultural segments, helping refine the product ahead of broader rollout.

ClimateAi has also started generating commercial revenue from yield prediction services, which rely on analyzing crop development indicators such as cluster size and counts in vineyards or flower numbers in strawberries. These capabilities further extend the platform’s value beyond weather forecasting, positioning it as a comprehensive planning tool for agricultural and food supply chains.

When asked about profitability, Kletter acknowledged that the company is prioritizing investment in its technical team to remain competitive in AI. “Investing in our technical team to stay competitive on AI has become more important than being immediately profitable,” he told AgFunderNews, adding that the company remains focused on maintaining favorable unit economics.

As climate volatility intensifies and agricultural operations become more complex, ClimateAi is betting that embedding AI-driven climate intelligence into everyday decision-making will become essential. By transforming a foundational but often cumbersome metric like Growing Degree Days into an actionable, automated workflow, the company aims to reduce friction across the agricultural value chain and help customers adapt more effectively to a changing climate.