Sensie translates plant measurements into real-time crop advice

Sensie is expanding its platform with Sensie Intelligence. The software combines sensor data with AI to provide real-time crop advice for greenhouse growers. The Sensie Omni sensor measures plant signals alongside root-zone conditions and the local greenhouse climate. The software translates these measurements into morning reports, updated analyses and answers to growers’ questions through chat. The first customers have been using Sensie Intelligence since early July 2026. More than fifteen organisations, including growers and research centres, now actively use the system to support irrigation and screening decisions, track plant recovery and compare treatments. “A grower wondering whether to give another irrigation cycle wants to know what their crop needs at that moment,” says Olivier Begerem, co-founder of Sensie. “That means interpreting the plant’s response in the context of the growing conditions and the grower’s strategy. Sensie Intelligence helps make that assessment.”

Starting with the plant
Sensie Omni measures changes in stem diameter alongside substrate water content, EC and temperature, and the local greenhouse climate. Together, these measurements help assess water supply in the root zone, demand driven by the climate and the plant’s response. The platform uses patterns in growth, shrinkage and recovery to calculate indicators for strain, recovery, strength and plant balance. Sensie Intelligence builds on these indicators, using AI to translate them into advice suited to the crop’s growing conditions and strategy.

The growing strategy sets the context
The system takes account of the crop and variety, greenhouse equipment, growing strategy, current weather and forecast. It also draws on previous measurements and actions and observations recorded in the logbook. A grower aiming for more generative growth, for example, has a different question from one seeking to improve recovery. The system therefore assesses rising plant strain alongside the growing objective and recovery over recent nights. This gives the measurement meaning within that grower’s strategy. Sensie Intelligence brings together agronomic expertise and technical development. Begerem and Maxime Dedecker, Sensie’s Crop Intelligence Advisor, contribute 15 years of practical experience in interpreting plant measurements and supporting growers. Co-founder and CTO Christophe Sysmans develops the hardware and software. The aim is to make well-grounded crop advice available at scale, tailored to each grower’s conditions and strategy.

From the morning report to the next question Each morning, a report summarises the previous day’s plant behaviour, overnight recovery and points that deserve attention. As conditions change during the day, growers can request a fresh analysis based on the latest measurements. The chat lets growers follow up on a report, request graphs and tables, or compare varieties, compartments and growing strategies. They can investigate a specific question without first building the analysis themselves. On a bright afternoon, for example, the system may suggest partial screening if plant strain is rising after a night with limited recovery. On an overcast day, it may instead recommend stimulating plant activity, depending on the measured plant response and the growing objective. The grower decides whether to act on the advice and can record the adjustment in the logbook. They can then ask the chat how the crop responded, with plant measurements shown alongside the climate trend. The following morning’s report shows how the plants recovered overnight. Actions and observations are retained as context for subsequent analyses.

Applications in research and growing technology
Advisers can review measurements, reports and the logbook remotely to support growers. Research centres and breeders can compare varieties and treatments, while technology suppliers can investigate how crops respond to their solutions. Sensie also sees opportunities to use real-time plant feedback as an input for autonomous growing models.

For more information:
Sensie
[email protected]
www.sensie.net