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

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

Detects compound and chronic stress patterns across metrics and time.

Placement, exposure-hour and grow-light recommendations.

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

Airflow, humidity and heat management, including VPD.

Pest risk from environmental conditions, plus identification from symptoms.

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

Projects how the plant would fare under hypothetical conditions.

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

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.

Exports what a mature plant learned and grafts it onto a new one of the same species.

A conversation channel between plants, with 71 skills as the fast path for asking each other things.

Budgets a battery and a solar panel against what the plant needs.

Watches whether the pot is running out and guides the move to a bigger one.

Makes the plant aware of whether anybody is in the room, and behave accordingly.

Reads the canopy with a thermal camera: where it is transpiring and where it has stopped.

Bends care to the time of year, in the right hemisphere.