Bio-Logic
The Digital Pulse of Nature.
Our Life Science research bridges the gap between Botanical Phenotypes and Computational Logic.
By leveraging the same high-resolution vision models developed for neuro-imaging, we analyze cellular structures in plants to predict yield, detect disease, and optimize biological output without chemical over-reliance.
Core Research Focus
- Phenomics: Real-time mapping of plant growth cycles via hyperspectral imaging.
- Genomic RAG: Using LLMs to query vast botanical databases for trait optimization.
Field Intelligence
Precision Agriculture
Crop Health Monitoring
Utilizing UAV-mounted sensors and satellite data, our AI detects Nutrient Deficiencies and Water Stress before they are visible to the human eye. This allows for targeted intervention, reducing fertilizer waste by up to 40%.
Yield Prediction
"Analyzing 26 variables—from humidity to historical soil data—to predict harvest volume with 94% accuracy."
Threat Mitigation
Botanical Security
Global food security is threatened by invasive pathogens. Our Pathogen-Vision model identifies leaf-rust, fungal infections, and pest infestations at the spore level.
- Spore-Level Recognition
- Automated Quarantine Alerts
Protecting biodiversity through digital vigilance. Our system tracks over 4,000 botanical diseases in real-time.
Supply Chain Logic
Harvest & Quality
Automated Grading
Computer vision systems for real-time sorting of produce based on size, ripeness, and internal decay detection.
Perishability Prediction
LLMs forecasting shelf-life duration based on transport conditions and initial harvest data.