Sentinel-2 harvest composite, Iowa 2024
Harvest image with AI field boundary predictions overlaid
Harvest Predictions
Satellite Image Answers

Ask a place
what changed.

Upload satellite imagery and ask plain-language questions. Locamage turns pixels into answers people can use.

Question Which fields changed since last week? Ask in the same language a field team would use.
Evidence Compare imagery, dates, and overlays. Use visual context without forcing a GIS workflow.
Answer Return the areas worth inspecting. Surface the visible change and why it matters.
Action Send the next team to the right place. Turn the result into a map, note, or review queue.

Questions it can answer.

Ask a satellite image about damage, growth, risk, or change.

Every satellite image has a question inside it.
Ask it in plain language.

Why this is possible now.

Earth AI is getting useful because it no longer treats each image as a one-off snapshot. The strongest systems combine sources, compare time, and turn pixels into a clear next step.

More than one sensor.

Useful answers can draw from optical imagery, radar, elevation, climate context, maps, and other Earth data.

Time is part of the image.

The question is often what appeared, disappeared, expanded, dried out, flooded, or burned between dates.

The output should be usable.

Teams need to know where to look, what changed, and what to do next, not just receive another model layer.

Try a public demo.

Image-location demo

Upload a street-level image and Locamage estimates where it was taken. This demo is smaller than the satellite workflow, but it shows the same visual reasoning.

Try It →
Street-level imagery used for geolocation analysis

Request private beta access.

Tell us what imagery you work with and what questions you need answered. We will reply with the right setup for your use case.