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This AI startup from The Hague knows exactly how much rain causes a disaster

15 February 2026·3 min read

The Pivot That Saved the Mission

Simmaco had founded GreenAnt in 2020 with the mission of making sustainable land management economically viable. The ant project was meant to be the means. But in Thailand, in conversations with farmers who explained why they could not abandon pesticides, even if they wanted to, the mission stayed the same. The means changed.

The pivot came from an unexpected direction. To monitor whether the ants were actually working, GreenAnt had used satellite data to track the health of trees. That data turned out to be far more valuable than the insects themselves.

"We realised that satellite data is an incredibly powerful tool for climate resilience," says Simmaco. "So we built an accessible, affordable interface that translates it into actionable insights." [2]

What emerged is Desidera, a platform that uses radar satellites rather than optical ones. The distinction matters. In Southeast Asia, clouds block the sky for more than 300 days a year. Conventional satellites see nothing. Radar cuts straight through.

Under the hood, Desidera runs on a digital twin of the earth that processes real-time satellite data and projects weather conditions three to five days ahead. The AI uses Graph Neural Networks, a technique particularly well suited to processing millions of interconnected geographic points simultaneously. This allows GreenAnt to model flood risk faster than existing weather systems. [7]

The system detects the exact millimetre of precipitation that will cause a flood at a specific location, scans weather forecasts for those threshold values, and sends warnings before the water arrives. [2]

Answers, Not Datasets

Studies and practical experience suggest that improved forecasts and decision support can increase productivity by up to 20%. But the real insight is not the number. It is about who can actually use it.

Most climate analyses require specialists to interpret the data. A smallholder farmer in Myanmar or Vietnam has no access to those experts. Desidera is built so that they do not need them. Users draw their plot on a map and ask questions via a chatbot. The AI provides answers, not datasets. [6]

"This approach addresses a critical knowledge gap," Simmaco explains. "It helps strengthen overall resilience." [2]

GreenAnt has run pilots in Myanmar and Thailand, including work with an international humanitarian NGO to protect flood-prone communities. In September 2024, Typhoon Yagi caused severe flooding that affected more than 1.1 million people across 70 townships and destroyed more than 2.3 million hectares of agricultural land. [5] The same technology that monitors mangoes in Thailand now tracks disaster risk in one of the world's most vulnerable regions. [2]

A €9 Billion Market

Farmers are not the only ones who need early warnings. The European insurtech market is expected to reach €9.2 billion by 2027, driven largely by climate-related challenges in insurance. [8] Natural disaster losses in Europe exceeded €50 billion in 2023, forcing insurance executives to reconsider decades-old risk models. [9] GreenAnt's bet is that the sector is willing to pay for foresight.

The team has grown to ten specialists in meteorology, machine learning and insurance. Building credible models for insurers requires fluency in both climate science and actuarial risk. Established players such as Aon and Munich Re already have sophisticated catastrophe models, but they lack the hyper-local precision that GreenAnt offers. That granularity is where the opportunity lies.

The company was recently selected for FoodSeed, the agritech accelerator backed by CDP Venture Capital and Eatable Adventures, which offers up to €500,000 in follow-on funding. [3] GreenAnt has also received support from Plug and Play, InnoQube Switzerland and the Cassini Accelerator Program. The next step: pilots in Vietnam, Thailand, the Philippines and Italy. [4]

The Queue That Tells the Story

The morning after the team had floated the idea of giving farmers access to capital through satellite-verified data, fifty farmers were standing outside their building in Thailand. They understood the value immediately. [1]

That queue tells the story better than any pitch deck. Climate technology does not fail because the science is wrong. It fails when it solves problems people do not actually have. GreenAnt started with a compelling idea about ants and ended up with infrastructure that farmers queue up for.

The complexity is not in the algorithm. It lies in understanding what people truly need.

On our platform

GreenAntGreenAntStartupSatellietdata en AI voor klimaatrisico en oogstvoorspellingen

On our platform

GreenAntGreenAntStartupSatellietdata en AI voor klimaatrisico en oogstvoorspellingen
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