ARTIFICIAL
INTELLIGENCE

At Vivent Biosignals, we apply artificial intelligence to one of the most underexplored data sources in agriculture: plant electrophysiological signals.

Plants continuously use biosignals to control growth and development, including reproduction, to respond to pests and diseases and to change in their environment, like temperature or light levels. Using advanced AI and machine learning techniques, we decode these signals to deliver diagnostic and predictive insights, helping make agriculture more resilient, more efficient, and more sustainable.

Our AI Pipeline

 

1. Signal Collection
We begin by capturing high-resolution electrophysiology signals from plants using biosensors. These biosignals serve as the raw data for our models.

2. Data Annotation
Each recording is enriched with metadata such as crop type, substrate, irrigation regime, life stage, and environmental conditions. This structured annotation ensures model accuracy and adaptability and speeds up our product development process.

3. Model Development
Using our proprietary dataset, the world’s largest and most diverse, and now exceeding 1.2 million plant-days—we train machine learning models to identify specific stress signatures and predict plant health outcomes. These models learn to distinguish between normal variation and early signs of stress, even under diverse growing conditions.

We compute up to 25 different crop health metrics from one electrophysiological signal so users receive insights that are specific and actionable.

4. Real-Time Processing
Once deployed, models run directly on sensors or in our cloud, delivering real-time alerts when stress is detected and feeding information to our intuitive, engaging dashboards. This allows growers and agronomists to act, often days before visible symptoms appear.

5. Intuitive, Engaging Data Visualisations
We provide clear crop health metrics designed for either farmers or for plant scientists on dashboards accessible on any connected device.

AI That Adapts to Every Crop, Every Condition

 

Thanks to the scale and diversity of our dataset, our models are highly generalizable. We can:

 

  • Calibrate thresholds for farmer interventions based on your crops and your growing conditions
  • Show how specific stress events impact crop yield
  • Improve performance over time as new data is continuously integrated

Only a few days of recording from small groups of plants are needed to calibrate our models, for your crop, making the models both highly adaptive and scalable

Pushing the Frontier of Responsible AI in Agriculture

Our focus is not just on innovation, but on using AI for good. By giving plants a voice, we unlock insights that enhance global food security and reduce the environmental impact of agriculture. We’re currently conducting trials, in both Controlled Environment and outdoor conditions, where plant biosignals directly control automated agronomic systems like irrigation. The preliminary results are fantastic with strong yield increases and less water used for irrigation.

If you’re a data scientist, researcher, or technologist interested in exploring one of the richest new frontiers in AI, plant intelligence, we invite you to collaborate!