SOFT-Farm Intelligence AI

Project Overview

An AgTech startup needed a way to transform large volumes of agricultural spatial data into actionable insights for farm managers. GIS-Point developed Farm Intelligence AI, an AI-powered geospatial analytics platform that allows users to analyze farm data through natural language queries and visualize results instantly on an interactive map.

Title: Farm Intelligence AI Assistant
Client: AgTech Startup
Sector: Precision Agriculture
Location: On-premise deployment

Challenge & Solution

Challenge:

Agricultural companies increasingly rely on spatial data from satellites, drones, field sensors, and farm management systems. However, transforming this data into practical operational insights remains challenging.

Most analytical tools require GIS expertise, complex dashboards, and manual data processing. As a result, farm managers often struggle to quickly answer operational questions such as identifying early crop stress, evaluating fertilizer efficiency, assessing environmental risks, or comparing seasonal yields.

In addition, agricultural businesses must ensure secure handling of sensitive operational and land ownership data. The client required a platform capable of integrating multiple agricultural datasets, performing advanced spatial analytics, and making insights accessible to users without GIS expertise.

Solution:

GIS-Point partnered with the client to design and develop Farm Intelligence AI, an AI-powered geospatial analytics platform for precision agriculture.

The platform allows farmers and agricultural companies to interact with complex datasets through a natural language interface. Instead of navigating traditional GIS tools, users can ask operational questions and instantly receive spatial insights visualized on an interactive map.

For example, users can query the system to identify fields with low NDVI values, compare yield performance across seasons, detect areas exposed to flooding risks, or analyze fertilizer application efficiency.

Platform Capabilities

The platform provides advanced spatial analytics for agricultural operations, including:

Automated crop health and vegetation stress analysis using NDVI indicators
Detection of environmental risks such as drought and flooding
Yield performance comparisons across seasons and parcels
Natural language interaction with spatial datasets
Interactive map visualization of agricultural insights

Key Services:

AI-Powered Spatial Analytics: Automated analysis of crop health, yield performance, and environmental risks using spatial data.
Conversational GIS Interface: Natural language interaction that allows farm managers to explore spatial data without GIS expertise.
Multi-Source Data Integration: Integration of satellite imagery, field boundaries, weather data, machinery telemetry, and farm management systems.
Secure On-Premise Deployment: Local platform deployment ensuring full control over sensitive agricultural data.
Embedded Spatial Intelligence: Integration of the AI spatial analytics engine into existing AgTech platforms.

Technology Stack:

Database & GIS: PostgreSQL + PostGIS
AI & Data Processing: Python
Frontend: React
Deployment: Docker
Infrastructure: AWS / GCP

People:

The project was delivered by a multidisciplinary team including GIS specialists, AI engineers, geospatial data engineers, and AgTech platform developers.

GIS-Point’s team designed the geospatial architecture, implemented spatial data pipelines, and developed AI-driven analytics for agricultural datasets.

Implementation Process

Data Integration: Aggregation and harmonization of satellite imagery, field boundaries, telemetry streams, weather data, and farm management datasets.
AI Model Development: Training NLP models capable of interpreting natural language farm queries and linking them with spatial analytics.
Spatial Data Processing: Development of geospatial pipelines for NDVI analysis, yield comparisons, and environmental risk detection.
User Interface Design: Creation of a conversational map interface enabling non-technical users to explore spatial insights.
Platform Integration: Embedding the AI spatial analytics engine into the client’s existing AgTech platform.

Results

The Farm Intelligence AI platform significantly improved how agricultural data is used in daily farm operations.

Key outcomes include:

Time-to-insight reduced from hours or days to seconds
Early detection of vegetation stress through satellite NDVI analysis
Improved efficiency of fertilizer and resource allocation
Faster identification of environmental risks such as drought and flooding
Wider adoption of spatial analytics by farm managers without GIS expertise

For the client, the platform also became a key differentiator for their AgTech product, enabling advanced geospatial analytics capabilities for their customers.

Our Team

Ievgen Lavrishko

CEO & Owner

Khrystyna Bochko

HR Generalist

Alevtyna Kostianchuk

Senior Project Manager

Andriiana Pavlyshyn

Head of Business Development

Roman Nahaiovskyi

Project Manager

Maria Kizim

Lead Generation Specialist

Ivanna Soltys

Tender Manager

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