IUNU and Priva partner on yield forecasting for greenhouse growers

Integration of the Priva One Platform and IUNU’s LUNA AI System enables rolling one- to eight-week yield forecasts that update as greenhouse conditions evolve, the companies said.

Three smiling men pose in front of a blue screen in a greenhouse.
The Priva and IUNU teams working together at the PROOF Research & Development Centre at HortiTech.
Photo courtesy of IUNU

Greenhouse AI technology company IUNU and horticulture climate and process control company Priva have announced a partnership that combines climate execution data from the Priva One platform with continuous plant-level insights from IUNU’s LUNA AI system to deliver reliable yield forecasting and prognosis capabilities to commercial greenhouse growers.

The integration, available now to joint customers globally, addresses achieving reliable, week-over-week yield forecasts.

“What truly impacts profitability is not whether a forecast is off by a small percentage. Growers can manage small deviations,” said Adam Greenberg, CEO of IUNU. “What causes real damage are the big swings. Unexpected peaks or gaps in harvest volume arrive too late to adjust labor, logistics or commercial commitments. This partnership gives growers evidence-based forecasts that evolve as their crop responds to real conditions.”

IUNU Luna autonomous cameras and sensors.
Photo courtesy of IUNU

The Priva One platform provides visibility into climate execution and what happens inside the greenhouse, while IUNU’s LUNA AI system adds continuous plant-level insight at scale, capturing real variability across plants, zones and conditions, the company said.

Because this learning is automated and continuous, it scales across entire commercial operations without increasing labor or relying on manual crop registration, the company added, with the approach learning continuously from the specific facility, genetics and executed climate strategy.

“When climate execution data and plant-level learning are combined, prognosis shifts from experience-based to evidence-based,” said Meiny Prins, CEO of Priva. “The model adapts as the crop responds. If plant development accelerates or slows, if climate strategies shift or if labor actions alter plant balance, the system incorporates those effects before they turn into costly volume swings.”