A pioneering agricultural innovation project has highlighted how artificial intelligence (AI) can be successfully deployed to unlock the full value of pig health data and support smarter decision‑making across the Scottish pig sector.
The Pig Insights project, funded through the Scottish Government’s Knowledge Transfer and Innovation Fund (KTIF), was designed to address one of the most persistent challenges facing pig producers. While large quantities of health and welfare data are routinely collected, they are often fragmented, complex and under‑used – as a result, early warning signals of disease and emerging health risks can easily be missed.
Led by Scottish Pigs Ltd – a farmer‑owned cooperative representing all major commercial pig producers in Scotland – the six‑month project brought together key industry, academic and regulatory partners including SRUC, Quality Meat Scotland, Food Standards Scotland, United Pig Cooperative and ScotEID.
At the heart of Pig Insights is the development of a new digital platform called ViewQVRs, which transforms Quarterly Veterinary Reports (QVRs) from static compliance documents into live, interactive intelligence. This means that, for the first time, farmers, vets and industry organisations can visualise, benchmark and track pig health and welfare data at farm and national level.
A major innovation within the project was the application of AI, particularly Large Language Models (LLMs), to summarise and interpret both structured data and free‑text veterinary notes. Importantly, all AI tools were run locally rather than through third‑party providers, ensuring sensitive farm data remained secure and under industry control.
The system integrates multiple data streams, including on‑farm veterinary assessments and abattoir carcase inspection outcomes, opening the door to earlier detection of disease trends and a better understanding of how farm‑level health issues influence slaughterhouse results. A proof‑of‑concept linkage also demonstrated how meat inspection feedback required under Food Chain Information regulations could be returned more effectively to producers.
Pig Insights has immediate relevance for national initiatives such as Scotland’s PRRS Control and Elimination Scheme, providing a unified evidence base to support more targeted, data‑led decision‑making. Although delivered within a short timeframe, the project has established strong technical foundations and a clear roadmap for wider rollout, according to Andy McGowan, director of Scottish Pigs Ltd.
He said: “Pig Insights has shown what’s possible when the industry works together to make better use of the data we already collect. For too long, valuable veterinary and inspection information has been buried away in PDF reports.
“This project demonstrates how modern analytics and AI can turn that information into practical intelligence that directly supports farmers, vets and disease control programmes.”
Researchers at SRUC led the technical development of the ViewQVRs platform. Sandy Carmichael, who led the AI work on SRUC’s behalf, said:
“This project demonstrates that AI can be used responsibly in agriculture to support, rather than replace, expert judgement. By combining robust statistical methods with carefully governed language models, we’ve shown how complex veterinary data can be turned into clear insights without compromising accuracy, transparency or data security.”
Beyond pigs, the approach offers a scalable model for AI‑enabled disease surveillance for other livestock sectors, positioning Scotland as a leader in agricultural data innovation and resilient food systems.