The plant speaks.
Sensors attached to leaf, stem, and soil read 55+ simultaneous channels of what is happening inside the plant — water movement, stress signals, growth rate, nutritional state — continuously, in real time.
We gave a tomato plant control of its own environment. What it did, we did not expect.
Syntheflora reads 55+ channels of live plant physiology and turns that data into growing decisions — powered by Gemini AI.
See what we foundGemini listens.
Google Gemini AI processes every channel simultaneously and surfaces what matters — delivered in plain language, without a data scientist in the room.
You decide.
Irrigation timing, nutrient delivery, and light management informed by what the plant is actually doing — not by schedules built on averages and assumptions.
This is not a smarter irrigation scheduler.
Most precision agriculture technology connects one or two environmental sensors to AI. A moisture sensor. A weather station. A satellite image. These tools measure conditions around the plant and optimise the inputs you deliver based on what they read. The AI, however sophisticated, can only work with the data it receives. And a soil moisture reading tells you very little about what the plant is actually doing.
Syntheflora measures the plant itself. Water movement through phloem and xylem. Tissue impedance changes that signal stress before the leaves show it. Sap flow rates. Photosynthetic efficiency. Biopotentials. Biomass growth rate. Fifty-five channels of internal physiological state, measured continuously, in the plant — not inferred from the environment around it.
The difference is not one of precision. It is one of category. Environmental sensors tell you what the conditions are. Syntheflora tells you what the plant is doing in response to those conditions. One of these is a proxy. The other is the thing itself.
From the laboratory
When given control of its own light cycle, the plant changed it.
When Syntheflora's biofeedback loop was used to let plants regulate their own lighting — turning it on and off in response to their own physiological signals — they did not follow the 18:8 or 12:12 light-to-dark schedules that controlled-environment agriculture assumes.
Microgreen production cycles shortened from 7 days to 4–5 days. Wheatgrass from 10 days to 7–8 days. Pea biomass increased by 30%.
Source: Kernbach, S. "Biofeedback-Based Closed-Loop Phytoactuation in Vertical Farming and Controlled-Environment Agriculture." Biomimetics 2024, 9, 640.
Read the full research →
I want to know what my plants are actually doing.
The Discoveries section documents what the system has found — including results that contradicted established agricultural assumptions.
Explore the discoveries 02I want measurable improvements in yield, quality, or water use.
Water reductions of 25–50%. Quality gains in Brix, phenolics, and total soluble solids. Results from real deployments, stated as ranges.
See the results 03I need structured data and ESG documentation from my operation.
Syntheflora generates full batch-level physiological and environmental records, structured for ESG reporting and GMP audit requirements.
See the data outputs Scientific foundation CYBRES GmbH, Research Center of Advanced Robotics and Environmental Science, Stuttgart, Germany.
Peer-reviewed publication "Human-AI Collaborative Evaluation of Plant Physiology with Multisensor Data" — Kernbach & Gemini AI Platform, CYBRES GmbH, 2024.
Partner Developed in partnership with Vertical Green.
Headquarters Madrid, Spain. EU-based, GDPR-compliant data infrastructure.
Distribution Global distribution partners.
Ready to hear what your plants are saying?
Talk to a Syntheflora agronomist about your operation. Or find a distribution partner in your region.