Techion automates livestock parasite detection and improves farm productivity
Techion, a New Zealand-based agriculture technology firm, partnered with AI specialist Aware Group to address the pervasive challenge of parasite infections that affect livestock health and farm productivity. Traditionally, manual parasite detection was labor-intensive, slow, and expensive, leading to widespread preventative drenching of animals. This practice contributed to rising costs, inefficiency, and drench resistance, costing New Zealand farmers tens of millions of dollars annually. Techion developed the FECPAKG2 platform, which integrates portable digital microscopes (Micro-I) with cloud solutions and AI. The new system leverages Azure Machine Learning to analyze images of faecal egg count samples and provide rapid, automated, scalable diagnostics for parasites across various livestock. The platform's AI features, running on Microsoft Azure, allow farmers and veterinarians to receive accurate FEC results within seconds, enabling targeted and timely animal treatment instead of blanket medication. This not only boosts productivity and animal welfare but also mitigates the risk of overmedication and environmental harm. By scaling their diagnostic services globally and automating much of the manual analysis, Techion dramatically reduced the need for skilled human technicians and improved service delivery speed. The solution is now deployed for cattle, equine, pigs, and birds across regions including Australia, the UK, and more. Their approach exemplifies how cloud AI and local partnerships can create transferable digital diagnostics, with applications reaching beyond agriculture to broader animal, environmental, and human health issues. Future plans include building a global database of diagnostic images and forging additional partnerships to tackle complex health problems.
- Organization
- Techion
- Industry
- Agriculture
- Location
- New Zealand
- Published
- October 2023
Reported outcomes
−50%
quantified impactOther quantified impact
Strategic outcomes
Primary read
Use case focus
Showing 3 of 3
- 1Automated Parasite Detection for Livestock via AI and Cloud Diagnostics
- 2Real-Time Faecal Egg Count Image Analysis for Veterinary Parasite Management
- 3Scalable Cloud-Based Diagnostic Platform for Animal Health Monitoring
- Parasite infections significantly reduced animal health and production efficiency on farms.
- Manual parasite detection processes were slow, costly, and limited in scalability.
- Widespread preventative drenching resulted in increased costs and resistance development.
- Undetected drench resistance was estimated to cost NZ farmers $98 million per year.
- Growing volumes of image samples made it difficult to scale analysis with available technicians.
- Developed FECPAKG2 platform integrating portable digital microscopes with AI analytics.
- Deployed Azure Machine Learning to automatically analyze faecal egg count samples for parasite detection.
- Used Microsoft Azure cloud to securely store and process diagnostic images and results in real-time.
- Partnered with Aware Group for AI model development, training, and validation.
- Enabled automated, scalable, and rapid diagnostic services accessible to farmers globally.
- Reduced drench use by 30-50% according to independent studies.
- Saved millions in costs for farmers by targeting treatments and preventing resistance.
- Improved animal health, welfare, and production yields through timely interventions.
- Delivered rapid FEC diagnostics globally, supporting sustainable and informed farming practices.
- Reduced the environmental impact of overmedication and improved compliance with local regulations.
Architecture
The FECPAKG2 platform combines Techion’s portable digital microscopes (Micro-I) in the field with the RATA software platform, securely storing all diagnostic image data in Microsoft Azure. AI models trained and deployed in Azure Machine Learning Workspace analyze sample images uploaded from the field. Results are rapidly returned to farmers and advisors through Azure-based applications, allowing for real-time, targeted animal treatment decisions. The platform also features Azure Scalable Compute to flexibly deploy AI models and ensure global scalability.
Implementation partners1
Sources & evidence2
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