WeedEye

WeedEye

Real-time, AI-powered selective agricultural spraying technology.

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DateInvestorsAmountRound
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€313k

Seed
Total Funding000k

Financials

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Revenues, earnings & profits over time
HUF202220232024
Revenues000000000000
EBITDA000000000000
Profit000000000000
EV000000000000
EV / revenue00.0x00.0x00.0x
EV / EBITDA00.0x00.0x00.0x
R&D budget000000000000

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More about WeedEye
Made with AI
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WeedEye is a Hungarian agricultural technology startup founded in 2022 by Sándor Balla, Krisztián Kránitz, Balázs Vinkovics, and Vilmos Németh. The company develops a smart spot-spraying system that utilizes artificial intelligence, advanced cameras, and processing units to provide real-time weed detection and targeted spraying. This technology allows for precise, millimeter-level application of herbicides only where weeds are present, which can reduce chemical usage by up to 90% without impacting crop yields.

The system is designed to be easily retrofitted onto almost any existing agricultural sprayer, making it accessible to a wide range of clients from small family farms to large agricultural operations. It is ISOBUS compatible and works with various crops, including corn, sunflower, and rapeseed. By focusing on reducing input costs and environmental impact, the technology addresses major challenges in modern agriculture, aligning with sustainability goals like the European Union's Green Deal, which aims to halve pesticide use by 2030.

The business operates in three main areas: agricultural operations on approximately 2,500 hectares, machinery manufacturing with in-house development, and the development of their Smart Sprayer based on their own practical experience. In July 2025, WeedEye secured a significant investment of over 124 million HUF (€312,500) from Óbuda Uni Venture Capital (ÓUVC) to facilitate its domestic market launch and subsequent expansion into European markets.

Keywords: precision agriculture, agritech, selective spraying, AI weed detection, spot spraying, herbicide reduction, smart farming, sustainable agriculture, farm machinery, computer vision

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