
Sensors, code & data
Raspberry Pi, Pico, ESP32, cameras, environmental sensors, data logging, and lightweight interfaces for field research.
View Nature AI sensor case ↗Research prototyping · Vancouver
Three focused product lines for environmental sensing, research prototyping, and physical model production.


One studio, three practical ways to move a research or design idea into the physical world.
Choose the closest starting point. Each line can remain focused or connect with the others when a project needs a complete system.

Raspberry Pi, Pico, ESP32, cameras, environmental sensors, data logging, and lightweight interfaces for field research.
View Nature AI sensor case ↗
CAD, field-ready housings, mounts, fixtures, 3D printing, and small-batch parts for testing and deployment.

Landscape, architecture, urban-design, and experimental models for researchers and North American design students.
A compact workflow keeps the work tied to the research question, timeline, and real deployment conditions.
Clarify the purpose, environment, inputs, output, timeline, and budget.
Develop the electronics, code, enclosure, printed part, or physical model.
Check the result, complete one focused revision, and document delivery.
03 · Selected study
Terrain studies, material tests, and water simulations help teams explore and communicate spatial ideas before full-scale implementation.
model making · casting · environmental simulation
All planning prices and final invoices are in US dollars. Final quotes reflect parts, complexity, testing, finish, field conditions, and delivery requirements.
For clean STL/3MF files and straightforward model components.
For a focused proof of concept using an existing development board and sensor.
For teams moving toward a demonstrable or field-testable system.
Nature AI Fab Studio
Send a short brief with the purpose, environment, timeline, available data or drawings, and what success should look like. We will recommend a practical path from prototype to test.