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Engineers & Farmers - for Farmers

GEIA is an open, modular platform for smart farming at global scale.

About GEIA

GEIA is an open, modular platform for smart farming, designed to help growers automate, observe, and improve their growing environments under real-world conditions.

What began as a practical system for stabilizing and automating growing setups has evolved into shared infrastructure used by growers, builders, and partners across diverse agricultural contexts.

GEIA focuses primarily on controlled-environment agriculture (CEA),
including greenhouses and indoor systems, while remaining flexible enough for outdoor
monitoring, logging, and experimentation.

Why GEIA exists

Across many forms of agriculture, growers face similar challenges:

  • Manual work that doesn’t scale
  • Unstable growing conditions in sensitive systems
  • Limited visibility into what actually changes between cycles
  • Automation tools that are rigid, closed, or hard to adapt

Basic timers and isolated controllers can automate actions, but they don’t support learning.

GEIA exists to fill that gap.

The platform was shaped by working across different crops, methods, and environments,
turning real-world variability into a design requirement rather than an edge case.

Built across real growing systems

GEIA has been tested and applied across multiple growing methods, including:

  • Hydroponics
  • Aeroponics (including high-pressure systems)
  • Aquaponics
  • Soil-based cultivation

These systems differ widely in dynamics, failure modes, and constraints.
That diversity influenced how GEIA was built.

Rather than optimizing for one ideal setup, the platform supports:

  • Gradual adoption
  • Experimentation
  • Comparison across cycles
  • Adaptation to local realities

Indoor-first, not indoor-only

While automation delivers the highest value in controlled environments,
GEIA is not limited to indoor use.

Growers also use the platform for:

  • Outdoor monitoring
  • Environmental logging
  • Seasonal comparison
  • Research and experimentation

The same principles apply in all cases: observe, learn, adjust.

From system to platform

As GEIA matured, it became clear that no single configuration
could represent real farms.

Different growers needed different sensors, logic, and levels of control.

GEIA evolved into a platform:

  • Modular by design
  • Open by architecture
  • Deployable locally, in the cloud, or at the edge

This allows it to support many independent setups — not just one ideal model.

How GEIA is built

GEIA is structured around logical zones rather than fixed installations.

A single setup can start small and expand over time by adding
nodes, sensors, or integrations — without replacing the system.

This approach reflects how real farms grow and change.

The assumptions behind these design decisions are explained in the
How We Think section.

Ecosystem and collaboration

GEIA is no longer shaped by a single use case.

The platform connects:

  • Growers using it in real environments
  • Builders extending hardware and integrations
  • Partners offering services, tools, and expertise

The platform improves through use across diverse conditions,
not through centralized control.

This ecosystem approach allows GEIA to remain adaptable as agriculture itself changes.

Who is behind GEIA

GEIA was founded and architected by Junell Abdi, with a background in IT systems, embedded development, and hands-on farming automation.

Over time, the platform has been shaped with contributions from engineers, designers, farmers, researchers, and early testers across multiple countries.

Rather than being developed in isolation, GEIA evolved through real deployments,
practical constraints, and collaboration with people working close to the problem.

Junell A - Founder & Lead Architect of GEIA.AI

Junell Abdi

Founder & Lead Architect

How We think

The principles and assumptions behind how GEIA is built – from agriculture to infrastructure.

Looking forward

GEIA is built for the long term.

Not as a closed product, but as an open foundation that can support learning, automation, and collaboration across many different farming contexts.

It is not designed to optimize one perfect farm.

It is designed to support many real ones.

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