Key Takeaways
• Aimer Vision, an AI-powered tool, enhances pasture measurement accuracy using smartphone-based scanning
• The system may increase farm profits by USD $400 per hectare, equating to $60,000–$80,000 annually for average-sized dairy farms
• Developed using 15,000+ video scans across four grazing seasons, the tool is optimized for real-world conditions
• It addresses labor shortages by eliminating the need for specialist pasture measurement staff
• Global expansion is in progress, with data collection already underway in Ireland for European adaptation
AI Meets Agriculture: Aimer Vision Set to Reshape Dairy Farming in New Zealand
New Zealand, a global leader in dairy exports, is witnessing a transformative shift with the launch of Aimer Vision, an artificial intelligence (AI) tool developed by agri-tech startup Aimer Farming.
This innovation aims to digitize pasture management, boosting both profitability and sustainability at a time when the agricultural sector faces mounting pressure from labor constraints and environmental regulations.
How Aimer Vision Works: Technology in the Farmer’s Pocket
Aimer Vision uses machine vision algorithms integrated into a smartphone app, enabling farm workers to scan pasture in just five seconds through a 180-degree sweep.
The system estimates pasture cover with up to 90% accuracy, providing instant analysis and actionable recommendations during daily farm routines.
This model has been trained on more than 15,000 pasture video scans, collected across all four grazing seasons during its beta phase, which helped the AI learn diverse growth conditions and improve its accuracy.
— Jeremy Bryant, Founder and Chief Technology Officer, Aimer Farming
Economic Upside: From Efficiency to Earnings
Aimer Vision’s predictive and real-time measurement capabilities can translate into a profit increase of up to USD $400 per hectare. For an average New Zealand dairy farm, this could mean an additional $60,000 to $80,000 in annual revenue, achieved through optimized pasture management and reduced wastage.
— Jeremy Bryant, CTO, Aimer Farming
A Digital Twin for Every Paddock
A key feature of Aimer Vision is its creation of a digital twin for each paddock. The system continuously learns and maps individual pasture growth trends, enabling tailored grazing schedules and supplement recommendations.
It also offers 21-day predictive insights, helping farmers plan inputs and resources well in advance.
This contributes not only to operational efficiency but also to environmentally sustainable practices, such as minimizing nitrogen runoff and managing soil health.
— Jeremy Bryant, CTO, Aimer Farming
Addressing Labor Shortages and Skill Gaps
One of the significant challenges in the agricultural sector, particularly in remote or rural areas, is the shortage of skilled labor.
Aimer Vision allows farm workers—regardless of technical background—to perform precision pasture measurement without additional equipment or training.
The smartphone-based tool can be used during routine operations, eliminating the need to dedicate time or personnel specifically for this task.
This user-centric design aligns with broader trends in digital agriculture, focusing on:
• Automation
• Accessibility
• Efficiency
A Global Vision: Scaling Beyond New Zealand
Aimer Farming is also preparing for international deployment, beginning with a year-long data collection initiative in Ireland. The Irish pilot is expected to fine-tune Aimer Vision’s adaptability to European climates and grazing systems.
— Jeremy Bryant, CTO, Aimer Farming
Moreover, Aimer is building what it calls the world’s largest pasture productivity database. This dataset holds immense value for food supply chains, agricultural input providers, and sustainability auditors, offering insights into field-level efficiency and product performance.
— Phil Townend, Chief Commercial Officer, Aimer Farming
Aimer Vision delivers a forward-looking solution that blends the power of AI with the practical needs of dairy farming.
It helps address current industry challenges—such as rising input costs, labor shortages, and the pressure to demonstrate environmental stewardship—without adding operational burden.
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