
Pycno
The data is aggregated in our software platform. The system brings latest scientific knowledge to the farmer and provides recommendations based on real-time sensor and weather data..
- B2B
- B2C
- manufacturing
- subscription
- food
- energy
- agritech
- deep tech
- hardware
- recognition technology
- iot internetofthings
Date | Investors | Amount | Round |
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- | investor investor investor | €0.0 | round |
investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
investor | €0.0 | round | |
N/A | AUD80.0k | Grant | |
Total Funding | 000k |
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Pycno is a technology company specializing in advanced agricultural sensors and analytics platforms. The company provides professional, easy-to-use sensors that collect real-time and historical data to support decision-making in agriculture. By leveraging this data, Pycno helps farmers and agricultural businesses cut costs by optimizing the use of resources like water and fertilizer. The sensors are designed for full autonomy, featuring solar panels and internal batteries, and are capable of soil moisture capacitive sensing without degradation over time.
Pycno's platform aggregates data from multiple sensors and fields, allowing users to apply the latest phenological and disease models to monitor trends and assess risks. The platform also integrates local weather stations and satellite data to provide comprehensive insights. Users can access their data securely from anywhere, thanks to built-in SIMs that support over 160 countries.
The company's business model revolves around selling sensor kits and providing a subscription-based analytics platform. Pycno serves a diverse range of clients in the agricultural sector, including individual farmers, agricultural enterprises, and research institutions. The company operates in the global agricultural technology market, focusing on innovation and data-driven solutions to enhance agricultural productivity and sustainability.
Keywords: agricultural sensors, real-time data, analytics platform, resource optimization, soil moisture sensing, phenological models, disease prediction, solar-powered, global connectivity, agricultural technology.