soilnet.ai_project

 

 

 

Fund data driven farming in Guatemala

Revolutionizing Agriculture: Invest in a Smarter, Sustainable Future with soilnet.ai.

soilnet.ai, in partnership with Genesis, is looking to improve smallholder farmers’ yields with AI-generated insights from soil sensors.

Lush Guatemalan farmland
500
Farmers
+10,000 p.a 
Total Output (tons)
0
Carbon Captured (t)

About the Project 

We’re building a data platform that transforms soil readings into practical, timely advice for smallholders—what to plant, when to irrigate, how to fertilize—so they can protect yields, reduce input costs, and build climate resilience.

The Problem

75% of the world’s soil is degraded and could reach 90% by 2050. Over-farming and climate change accelerate degradation, driving down yields and threatening food security.

Our Solution

AI-generated insights from in-field soil sensors. soilnet.ai analyzes multi-parameter soil data to guide irrigation, nutrient management, and crop plans—improving yields while conserving resources.

Snapshot

Focus regionGuatemala
Primary usersSmallholder farmers
DeliveryAndroid app + SMS
Data sourcesIn-field hand sensors weather; agronomy

The Compelling Story

Why now

Food security and climate resilience demand practical tools that work at farm-gate level. soilnet.ai directly addresses yield volatility and input waste with trustworthy, field-ready data.

How it works

Our machine-learning engine ingests soil sensor data (moisture, temperature, conductivity and more) and produces simple, actionable recommendations—when to water, how much fertilizer, and what interventions to avoid.

Who’s behind it

Built by experienced operators in digital transformation, fintech, and ag-tech. Advisors and partners include agronomists, micro-finance leaders, and ecosystem builders across Latin America and the U.S.

Current State

  • Field hardware stack validated (LoRaWAN base station + cellular backhaul); sensor data ingested into time-series DB and visualized in dashboards.
  • Pilot program underway in Guatemala with local partner Genesis.
  • Next milestone: mobile app build focused on farmer UX, localized agronomy advice, and cohort analytics for cooperatives.

Transparent Impact Metrics

We favor measurable outcomes over hype. As we scale, we will publish verified metrics below—updated in real time—so investors can see progress at a glance.

Social Impact

  • Yield stability and gains for participating farmers
  • Reduced input costs via precise irrigation & nutrients
  • Farmer-friendly UX with local language support

Environmental Impact

  • Water conservation through targeted irrigation
  • Lower fertilizer usage and runoff
  • Foundations for carbon-capture verification

Financial Model

  • Hybrid B2B2C: cooperatives/NGOs sponsor cohorts; optional farmer subscription
  • Low-cost hardware footprint; software-led margins
  • Path to scale via bundles with finance & inputs

Join Us: Fund the soilnet.ai App

We are seeking to raise $25,000 to build and deploy the next phase of the Soilnet.ai mobile app for an initial cohort of 5,000 farmers in Guatemala.

Use of Funds

  • App development: farmer UX, offline-first workflows, Spanish localization
  • Data science: agronomy models, alert thresholds, QA & validation
  • Pilot operations in Guatemala: onboarding, training, support
  • Impact measurement: dashboards, third-party verification setup

What this unlocks (urgency)

  • App MVP launch and cohort-level analytics for local partners
  • Evidence package: early yield, input savings, and water outcomes
  • Readiness for expansion to additional territories

Supporting Materials

For deeper diligence, access detailed briefs below. Request additional documents under NDA.

 
Investor Brief (PDF)
Download
 
One-Pager: Guatemala Pilot (PDF)
Download
 
soilnet.ai Technical Overview (PDF)
Download

 

Prefer to speak first?

Email us for a confidential conversation about impact, milestones, and deployment plans. We respond within 1 business day.

We never share names without permission. NDA available on request.
Farmer using mobile app in a field
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Privacy-first | Guatemala pilot | Contact: [email protected]