Merqato

Merqato

Web & Mobile Local Product Search.

HQ location
Amsterdam, Netherlands
Launch date
Employees
Enterprise value
$2—2m
Company register number
55982727
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DateInvestorsAmountRound
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€350k

Seed
Total Funding000k
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More about Merqato
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Merqato, an Amsterdam-based company founded in 2023, provides an AI-powered predictive analytics platform specifically designed for the fresh fruit and vegetable industry. The company was established by Claire Bénard, Jan-Willem Snoeker, and Thomas Beelaerts, who united with the common objective of reducing food waste through technology. Snoeker brought commercial experience from roles at Philips and a prior fintech startup, while Beelaerts had a background in agricultural innovation. Bénard, a data scientist with a history of applying machine learning to solve impactful problems, provided the necessary data expertise after the company pivoted from its initial idea of a surplus marketplace to a data-driven forecasting tool.

The firm targets wholesalers, distributors, cooperatives, and buyers in the fresh produce sector, aiming to improve their operational planning and reduce waste. Merqato's business model is centered on its software-as-a-service (SaaS) platform, which helps clients navigate the challenges of thin margins, unpredictable supply, and intense competition. By generating more reliable, long-term forecasts for both supply volume and price, the platform enables users to make better data-driven decisions, align their supply chain more effectively, and reduce value loss from produce being sold at lower prices.

Merqato's platform integrates a company's historical operational and order data with a variety of external data sources, including weather patterns, energy prices, trade volumes, and market trends. Using AI and machine learning algorithms developed in collaboration with agronomists, the system analyzes these diverse datasets to deliver forecasts up to six weeks in advance, which it claims can improve accuracy by at least 25%. Key features include harvest forecasting, demand planning, and smart alerts for significant volume changes or price shifts. Initially focusing on perishable products like strawberries, tomatoes, grapes, and green beans, the company has built models trained on large datasets from partners across Europe and South America.

Keywords: fresh produce forecasting, agricultural technology, supply chain optimization, AI-powered analytics, food waste reduction, predictive algorithms, demand planning, harvest forecasting, price prediction, agtech, fruit and vegetable market, data-driven agriculture, supply and demand matching, operational planning, food supply chain, wholesalers, cooperatives, distributors, SaaS, machine learning

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