AI insights
for precision farming

We believe that the growth of IoT sensors and data in Agriculture is an opportunity for AI enabled precision farming, to optimize farm operations and increase yields.

- Trevor Bloch, VROC CEO

Digital transformation of Agriculture

Improve yield by 15 to 20 percent

It has been estimated, that farmers may be able to improve yield between 15 and 20 percent using IoT technologies. As the volume of data being produced by farms continues to increase, AI can be applied to this data, to help farmers make critical decisions, confirm assumptions, and predict future conditions for more accurate planning, such as planting dates, crop selection, accurate distribution of fertilizers and treatments for disease and pests.

VROC's no-code AI Platform, OPUS can be used by the agricultural industry, to optimize faming practices.  

Discover OPUS
Precision Farming Use Cases

AI Benefits for the agriculture industry

Optimize farming practices and operations using IoT data. Benefit from real time monitoring across the whole network, along with advanced analytics predictions for improved decision making.

  • Insights for optimal harvest and planting dates
  • Detect variances between farm blocks and key influencing factors
  • Early detection and monitoring of disease, pests, and weeds with analytics for more accurate treatments and reduced wastage
  • Correlate relationships between soil, irrigation, productivity, and other variables
  • Monitor the condition of stored goods with insights to improve shelf life
  • Monitor livestock behaviour and predict welfare issues and mortality

A changing climate and global food security concerns make the long-term sustainability of the agricultural industry a high priority. Using data to monitor real-time conditions and predict future conditions and their impact, such as the weather, and being agile to adapt operating practices to ensure optimal harvests, is critical to building a resilient and sustainable industry.

Use real time and historic farm and industry data to assist with compensation modelling and forecasting to help provide a decision support tool for farm operators

Collect real time and historic data from critical machinery and predict future equipment conditions for predictive maintenance. These essential insights can help farm operators order spares to remote locations, so they arrive in-time, reducing downtime and high freight costs. Ai predictions can also determine accurate root causes of failure so that maintenance is carried out correctly first time.

OPUS Product Features

Why our customers choose OPUS

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Rapid AI Modelling

Produce AI models in minutes without coding or programming

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Accurate Predictions

With model confidence and accuracy averaging 99%, users have confidence to make decisions

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Interoperability icon


Built to integrated with legacy systems and equipment agnostic so you can obtain insights from your data

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Anytime, Anywhere

Optimize your team with anywhere, anytime access to real time monitoring and predictions

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AI Implementation

Time to value realisation

Client Setup

Client supply of historical data and set-up of real-time streaming

Week 1

VROC Data ingestion and real-time data streaming connection

Week 2 & 3

Client training and model generation

Week 4

Models in Production. Client starts delivering business value


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