What would Earth do?
AI-enabled hardware, an agentic management layer, and a structured data feed. Together, they make the full output of measured land visible, verifiable, and financially useful.
You can't manage
what you can't measure.
Everyone responsible for land now has to prove what's happening on it, not only for their own operations, but for their investors, their regulators, and the public.
Conservation groups, governments, and industry all face the same question. It has to be answered with evidence that is continuous, independent, and from the ground.
Almost nobody
measures the ground.
Manual surveys cost too much to repeat. Legacy cameras don't connect to anything. Satellites can't see under the canopy.
So decisions that shape entire landscapes get made from a distance, on data that is already a year old. We build the instruments that close that gap.
From sensor to cell phone — in 30 seconds.
Sensors, gateway, satellite, AI: the full path from a node in the field to a decision on a phone. Hover a marker to see the instrument that stands there — or tap it, on a phone.
An AI optical sensor that classifies on the device and sends the conclusion first, the photograph only when it is worth the bandwidth. Small, concealable; solar and ultra-low-power: it runs unattended for a year.
A multi-species optical sensor for the park boundary. It recognises 8–10 classes in a single detector and carries a second radio, so one unit at the village edge gives people advance warning without being retasked as the season changes.
Transmits from anywhere — LTE · LoRa · Starlink. Nodes relay over LoRa; the gateway uplinks via Starlink. Many sensors share one link — pooling the satellite cost.
Ingests any sensor into one automated pipeline: stored, analyzed, and delivered as maps, dashboards, reports, real-time alerts. Edge classifiers refine results on-device, down to identifying individual animals.
Initial deployments across four continents.
From the California redwoods to the Bangladesh Sundarbans.
A loop that deepens with every measurement.
Each sensor deployed expands the measurement footprint. Each measurement deepens what is known about the land. As density grows, every signal becomes a more honest representation of ecological reality, and a more useful one for the institutions that need to act on it.