An industrial computer vision company providing precision agriculture solutions to indoor growers, has raised USD$7 million in an oversubscribed Series A financing led by S2G Ventures and Ceres Partners.
iUNU stated it is transforming the way indoor growers do business by harnessing the power of computer vision through its product offering, LUNA. The LUNA platform delivers a system of mobile and fixed cameras with high definition imaging and environmental sensors that measure and record everything down to the real-time growth rate of each plant.
The software combines computer vision and machine learning technologies to continuously build detailed models of individual plants, unique among millions, throughout the day. LUNA detects even the most minute changes in health of individual plants, giving growers precise knowledge needed for proactive management. LUNA uses this insight to drive margin for growers through crop monitoring/forecasting, space utilization, and labour planning – while giving increased pricing leverage to the sales team.
According to iUNU, greenhouse production is experiencing significant growth. In North America, the greenhouse fruit and vegetable market is growing more than 20 percent annually. As greenhouses expand their square footage to meet demand, however, labour shortages and rising labour costs pose challenges for growers.
"Our communities are under-greenhoused,” said Adam Greenberg, CEO and founder of iUNU. “Rising consumer demand is accelerating the growth of the greenhouse industry, but the massive shortage of both growers and manual labour requires a scalable machine vision solution to further the supply."
The LUNA system surpassed one billion square feet of greenhouse analysis in 2019. As a result, achieving and desired outcomes for customers has become both more precise and faster. The company maintains the LUNA system has the most extensive knowledge from imaging on the market. While each grower using the LUNA platform owns their own imagery, the constant growth of the volume of imaging drives the machine learning and value the system provides.