It’s not uncommon for you and your neighbours to get the same forecast but widely different actual measurements. Ordinary weather models make forecasts for large grids that cannot account for the hyperlocal nature of the weather.
These models cannot be trusted with certainty to plan your farming activities ahead. Luckily, we have developed a disruptive technology that will change farming practices forever.
We help farmers optimize their field work and improve profitability and sustainability by eliminating the guesswork of weather prediction.
“Interesting, the rainfall predictions seem quite accurate. Over the summer, a few times other apps have predicted no rain, and Cordulus predicted 7 mm which we got. Last night, other apps said 2 mm while Cordulus said 17 mm. We got 20 mm!”
Cordulus already stands at the forefront of local weather forecasting, but we still aim to improve. Even though this technology is new, it has already proven itself to be a better alternative for farmers than traditional forecasting methods.
Here at Cordulus, half of our entire team is dedicated to product development and applied meteorology. Focusing on consistently improving the precision and accuracy of our weather forecasts, we strive to master disciplines within data science, machine learning, and meteorological forecasting.
As our network grows, so too does our ability to provide precise and error-corrected measurements and forecasts that all of our users can benefit from.
"If I’ve got the agronomist on the farm, we can look back and see if there’s been growth issues; whether we had enough rain or not, whether it’s been in a period of drought that could have impacted the establishment of the reseed."
"Easy to install, great quality weather station product. Records wind speeds over time to assist with spray recording and general day-to-day operations."
"It should almost be a law to have Cordulus Farm. It's absolutely critical for drilling and spraying properly. Most people have a feeling about the weather and its importance, but it's too vague. The data in the app makes it systematic."