From Data to Decisions: The Technologies Reshaping Pig Production
Data-driven pig production should be the new norm, reshaping how decisions are made across the operation, but the reality is that swine producers have been left behind compared to other sectors of agriculture, and even livestock. Sensors, artificial intelligence, software, and automation are driving this shift toward more connected and consistent use of information, resulting in a more connected system of integration, with more consistent use of information across the operations, but while much has been achieved there is much more to do.
Pig production has always been a business of precision. Breeding, feeding, health, and marketing decisions are tightly interconnected, and small changes in one part of the system can have significant consequences across the whole operation. What is changing today is not the complexity of pig production, but how that complexity is managed. A combination of technologies is now reshaping how decisions are made across the industry. This is not about replacing human expertise. It is about improving how information is captured, interpreted, and applied. The shift is from fragmented, periodic observation to continuous, connected management across the entire production system.
This change is also being driven by structural pressures. Labor constraints, rising input costs, and increasing expectations around efficiency and sustainability are forcing producers to operate with greater precision than ever before. The technologies themselves are not the story. What matters is how they begin to connect different parts of the system. Data collected at one stage can now inform decisions at another, creating a more integrated approach to managing performance, health, and efficiency across the entire production cycle.
Examples of the technologies that I believe will define what this shift looks like in practice, particularly where data, decisions, and execution start to connect, are separating themselves from the general innovation pack, by offering real improvements in profitability to pork producers. Xsights provide animal-level monitoring and traceability, with new innovations around medication tracking and advanced wearable tagging systems. SWARM has shown in larger integrated pork production how they can provide decision intelligence across supply chains to optimize profitability. EveryPig offers a more structured health and team communication for health care and hog management. Distynct real-time risk detection on farm. Munters (full production system integration), HEFT (humane end-of-life management) and DSM’s Verax to analyze blood metabolites illustrate how the industry is moving beyond data collection toward integrated, decision-driven systems. Together, these are not isolated technologies, but signals of a broader shift toward systems that connect data, decisions, and execution across the entire production cycle.
Analyzing that shift requires considering the different types of technologies that contribute to capturing data, structuring information, supporting decisions, and ultimately executing them in practice.
1. Sensors & IoT: Building the Continuous Data Layer
Alongside vision-based systems, a second layer of innovation is emerging through sensors and IoT technologies. These systems capture environmental, physiological, and operational data that were previously difficult to measure in real time. The focus is not just on collecting data, but on turning it into actionable information that supports better decisions, as digital tools convert real-time data into insights that improve management and productivity.
A key shift within this layer is how data is increasingly tied to actions and outcomes rather than observation alone. Xsights extends beyond monitoring by integrating medication logging directly into farm workflows, capturing treatments at the point of administration and linking them to individual animals. This closes a longstanding gap in traceability, allowing producers to evaluate not just health signals but how interventions influence outcomes over time. At the same time, Distynct focuses on real-time responsiveness, using connected sensors and mobile alerts to detect critical issues such as feed disruptions or environmental failures as they occur. Together, these approaches reflect a broader shift from simply collecting data to enabling faster, more consistent, and more actionable decision-making in daily operations.
Beyond these systems, a broader ecosystem of sensor technologies continues to expand the range of signals that can be captured. Companies such as Cynomys and dol-sensors monitor air quality, temperature, and humidity to maintain optimal barn conditions, while Allflex provides identification and traceability technologies that form the foundation of digital animal management.
Other approaches capture more specific signals. SoundTalks uses acoustic analysis to detect respiratory disease early. At a more integrated level, platforms such as Eco-Pork combine sensors, AI-enabled cameras, and cloud-based analytics into unified systems that connect data across the farm.
Together, these technologies are creating a continuous data layer that feeds into more advanced analytics and decision-making tools. The value of this layer is not just in the volume of data collected, but in how consistently it can support timely, informed action across the production system.
2. Software & Analytics: Turning Data into Decisions
Collecting data is only part of the process. The next step is structuring it in a way that supports consistent decision-making. This is where farm management software and analytics platforms play a central role. These systems organize, structure, and analyze information across the production cycle, enabling producers to understand performance, identify inefficiencies, and benchmark results. Across the industry, data analysis is increasingly focused on transforming production data into actionable insights that improve management and decision-making.
A key development within this layer is the move from data management to decision intelligence. SWARM Engineering operates at this level by using AI-driven models to structure and optimize decisions across production, logistics, and supply chains, helping producers align hog supply with processor demand and coordinate flows from farrowing to finishing. By accounting for variability in weights, health, and market conditions, it enables real-time trade-offs across the system rather than optimizing isolated tasks. At the production level, BarnTools (owned by MTech Systems) connects data across the entire lifecycle, from genetics and breeding through feeding, growth, and processing, enabling large-scale operations to monitor performance, benchmark outcomes, and anticipate risks across multiple sites. Complementing this, EveryPig focuses on structuring day-to-day operational and health data, digitizing workflows, communication, and recordkeeping to improve visibility, coordination, and early detection of issues across teams and farms. A similar shift is emerging in biological and nutritional decision-making, where tools such as DSM’s Verax™ use biomarkers and machine learning to detect nutrient imbalances and health risks before symptoms appear, enabling more proactive and preventive management.
Alongside these platforms, a broader set of software tools continues to provide the foundation for digital pig production. Systems such as PigCHAMP, Cloudfarms, and AgroVision offer comprehensive data management and reporting capabilities, while SwineTech digitizes workflows and task management. More specialized platforms such as FarmResult provide deeper analytics for performance and genetic tracking, and tools like Pig’UP support benchmarking and multi-site management.
Together, these systems form the foundation of digital pig production. Without structured, reliable data and the ability to translate it into decisions, more advanced technologies cannot deliver value. Industry experience continues to show that strong data management and decision systems remain central to improving health, productivity, and operational efficiency.
3. Specialized Digital Tools: Solving High-Impact Problems
Alongside system-wide technologies, a range of specialized tools are addressing specific bottlenecks in pig production, often in areas where operational constraints, welfare considerations, and risk management intersect.
HEFT focuses on one of the most critical and often overlooked stages of production: the end of life. Its nitrogen-based high expansion foam technology creates a controlled anoxic environment (below 2% oxygen), enabling humane stunning and euthanasia without the stress responses associated with conventional hypoxic methods such as carbon dioxide. Designed for consistency, operator safety, and biosecurity, this approach brings greater control and transparency to a stage of production that has historically been difficult to standardize.
Beyond this, other specialized tools focus on well-defined operational challenges where incremental improvements can deliver immediate value. Solutions such as Ro-Main automate pig counting with high accuracy, reducing labor and financial losses, while Asimetrix provides continuous weight tracking and growth analysis. In processing environments, CLK GmbH applies computer vision to carcass evaluation, improving consistency and efficiency. Platforms such as Farm Health Guardian digitize biosecurity and movement tracking, helping prevent disease spread, while emerging tools like Verility bring data-driven analysis into reproductive decision-making.
These technologies are often easier to adopt and provide a clear entry point into digitalization. While more focused in scope, their impact can be significant, particularly when integrated into broader systems where small improvements at critical points translate into measurable gains across the production cycle.
4. AI & Computer Vision: From Observation to Continuous Monitoring
One of the most important changes in pig production is the shift from human observation to automated, real-time monitoring. Computer vision and artificial intelligence are enabling producers to measure what was previously difficult, time-consuming, or subjective. Instead of relying on periodic checks, these systems generate continuous data on animal behavior, growth, and welfare, allowing earlier detection of issues and more consistent performance tracking over time.
A range of technologies are contributing to this shift. Companies such as Agri-Food AI are developing camera-based systems for real-time weight estimation, counting, and sorting, while FarmSee uses AI-driven machine vision to track individual animals, generate continuous weight and performance insights, and detect early signs of disease or underperformance, supported by SCR within the Allflex Livestock Intelligence ecosystem. Similar solutions are also being developed by companies such as Dilepix, which focuses on real-time monitoring of activity, weight, and reproductive indicators.
Other approaches focus on behavior and risk detection, with Serket analyzing behavioral patterns and Beyond Technology Global combining visual data with broader farm indicators to identify risks in real time. Monitoring is also extending beyond the farm, where platforms such as Argus.CV, Visionplatform.ai, Deloitte, and Genba Solutions apply similar technologies in processing environments. At a more integrated level, Dekon Group combines computer vision, IoT sensors, and analytics to manage pigs across their entire life cycle.
The value of these technologies does not come from individual models alone, but from how visual data is combined with other data streams to support more timely and consistent decision-making across the system.
5. Automation & Smart Barn Systems: From Insight to Action
The next step is converting insights into action. Automation systems are increasingly connecting feeding, climate control, and barn management into integrated platforms that enable real-time adjustments based on data. Modern swine facilities rely on automated systems to continuously regulate ventilation, feeding, and environmental conditions in response to sensor inputs.
Companies such as Fancom and SKIOLD provide integrated solutions for feeding, ventilation, and environmental control, while Big Dutchman combines automation with digital tools such as camera-based monitoring. Hotraco Agri focuses on centralized control of climate, feeding, and water systems. Other technologies extend this approach through more targeted applications. FREEDA Solutions and RedVan Solutions use data-driven feeding systems to optimize nutrition and performance, while PigTek provides integrated barn management solutions.
These systems represent the operational layer of digital transformation, where data is translated into direct changes in how the farm operates. As production systems scale, automation becomes essential for maintaining consistency, improving efficiency, and controlling costs.
6. Robotics: Automating physical work
In parallel, robotics is beginning to address one of the most persistent challenges in pig production: labor availability. Tasks such as cleaning, sanitation, and handling are time-consuming and repetitive, making them well suited for automation. Robotic systems are increasingly used to improve consistency, reduce manual workload, and strengthen biosecurity. Companies such as Envirologic and Washpower focus on automated cleaning solutions, while Swine Robotics is developing systems for both cleaning and reproductive management. While less data-driven than other technologies, these solutions play a critical role in improving labor efficiency, worker safety, and operational consistency.
What this means for the industry
Digital technologies do not remove uncertainty in pig production. Weather, biology, disease, and markets will continue to introduce variability. What changes is the ability to detect signals earlier, interpret them more consistently, and respond with greater precision.
Across agriculture and other industries, experience consistently shows that the value of digital technologies is not created by individual tools, but by how they are integrated into workflows and decision-making processes. The same applies in pig production. Isolated adoption will deliver incremental improvements. System-level integration will change how operations are managed.
The industry is not simply adopting new tools. It is moving toward a more connected production model, where data flows across stages, decisions are supported in real time, and execution becomes more consistent.
The difference going forward will not be which technologies are adopted, but how effectively they are integrated into day-to-day operations. In that sense, the shift is not technological. It is operational.
