“Rooted in Science … Designed for Agriculture”
At Orugen, we engineer solutions that are rooted in science and designed for agriculture. Our team of experts come from diverse backgrounds such as math, engineering, agriculture, and beyond to provide our clients with robust solutions for hard to solve problems.
Ai for the real world…
We are an independent research and design lab that pairs creativity with scientific rigor to bring new solutions to agriculture. We pride ourselves on our R&D capabilities, and our team of experts is constantly pushing the boundaries of what's possible.
We have a long history of successful bespoke projects, and many of our most advanced ideas have been developed internally by our own group. We are always looking for ways to improve our products and services, and we are constantly innovating to bring new solutions to the market.
Our Services
Deep Learning
Deep learning is driving the future of artificial intelligence. Recent advances in AI have been made possible by deep learning, which is a way of teaching computers to learn by example. Deep learning algorithms are inspired by the structure of the human brain and are known as neural networks. These neural networks are built from interconnected network switches that learn to recognize patterns in the same way that the human brain does.
Computer Vision
Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Visual information in collaboration with deep learning models allow machines to understand and then react to what they “see.” As the technology continues to develop, the potential uses for computer vision are only limited by our imagination. Computer vision will become an increasingly important part of our lives, changing the way we interact with the agricultural world around us.
Hardware - Edge Processing
Edge computing is a term used to describe the process of taking action on data at the edge of the network, as close to the source as possible. By doing this, it is possible to reduce latency and bandwidth use. Edge computing is particularly important for applications that require real-time data processing, such as Computer Vision or other hardware-intensive tasks. By processing data at the edge, these applications can avoid the need to send data back and forth to a central location, which can help to improve response times and save on bandwidth usage. In addition, edge processing can help to improve security by keeping sensitive data within the confines of the edge device.
