A bridge between AI and plants: pluggable sensors, persistent plant memory, multi-provider AI and a first-person plant voice.

Placement, exposure-hour and grow-light recommendations.

Pest risk from environmental conditions, plus identification from symptoms.

Detects compound and chronic stress patterns across metrics and time.

Projects how the plant would fare under hypothetical conditions.

Predicts watering needs from soil moisture, trends and care history.

Species-aware alerting: turns raw threshold breaches into prioritized, actionable alerts.

Trend, cycle and slow-decline analysis over stored sensor history.

Airflow, humidity and heat management, including VPD.

The plant writes its own dated journal, grounded in real readings and care events.

Feeding schedule and nutrient guidance from conductivity and care history.

Probes the plant with specific wavelengths and reads the electrical response of each photoreceptor pathway.