TraceGains has unveiled Intelligent Document Processing (IDP), an AI-powered Certificate of Analysis solution set to transform quality control in the food and beverage industry. Launching on March 25, 2025, this innovation addresses one of the sector’s most time-consuming tasks by automating COA processing for material compliance and lot-level ingredient quality control. Built on OpenAI’s foundation model and specifically trained with food industry data, IDP can review documents against specifications almost instantly, dramatically reducing the previous 12-minute-per-page processing time. This technology represents a significant advancement for manufacturers and suppliers focused on maintaining food safety standards while improving operational efficiency.
The Technology Behind TraceGains’ IDP Solution
The new Intelligent Document Processing solution from TraceGains represents a significant technological breakthrough for food manufacturers. By leveraging OpenAI’s foundation model, TraceGains has created a specialized tool that understands the unique requirements of Certificate of Analysis documents in the food and beverage industry. This AI system has been extensively trained and validated against global industry COAs, ensuring it can recognize and process documents from various suppliers and regions.
What makes IDP particularly valuable is its ability to learn and improve over time. As the system processes more documents, it gets smarter and more accurate, adapting to new formats and specifications. This continuous improvement cycle ensures that the solution remains effective even as document formats change or new suppliers are added to the supply chain.
IDP goes far beyond traditional Optical Character Recognition (OCR) technology that simply converts images to text. Instead, it intelligently extracts relevant information from non-standard documents and transforms this data into a structured, composable format that integrates with other systems. The result is a seamless flow of quality data throughout an organization’s supply chain management processes.
Early trials of the technology show promising results that match automation success stories in food production. The system has demonstrated the potential to match or exceed human accuracy while processing documents at much higher speeds. This combination of speed and accuracy addresses a critical pain point for food manufacturers who must process thousands of COAs annually.
Transforming Food Safety Management
Food safety remains a top priority for manufacturers and consumers alike. The manual processing of COAs has historically been a bottleneck in ensuring ingredient safety and compliance. With TraceGains’ IDP solution, food companies can now automatically review inbound COAs against required specifications and immediately flag potential issues for human oversight.
This automated approach dramatically reduces the risk of human error in reviewing critical safety data. When a COA arrives with parameters outside acceptable ranges, the system identifies these discrepancies instantly, allowing quality teams to address issues before ingredients enter production. This proactive approach to quality management helps prevent costly recalls and protects consumer health.
Greg Heartman, Vice President of Product Management at TraceGains, explains the value proposition: “By combining our rich contextual TraceGains data with the OpenAI model, we’ve created a vertical-specific AI solution for brands to manage the continual quality of their supply chain and ensure consumer food safety.” This specialized approach ensures the AI understands the context of food safety requirements, making it more effective than general-purpose document processing tools.
For food companies already exploring AI applications in their operations, IDP offers an immediately practical application with clear ROI. The system integrates with existing TraceGains solutions, creating a comprehensive quality management ecosystem that supports food safety from ingredient sourcing through final product release.
Economic Impact on Food Manufacturing
The economic benefits of implementing TraceGains’ IDP solution extend throughout the food manufacturing process. By eliminating manual COA processing, companies can reassign valuable personnel from tedious data entry tasks to more strategic quality management activities. This reallocation of human resources alone creates significant value for organizations struggling with staffing challenges.
The reduction in processing time from 12 minutes per page to near-instant represents an enormous efficiency gain. For large manufacturers receiving hundreds or thousands of COAs weekly, this time savings translates directly to reduced operational costs and faster ingredient approvals. Faster approvals mean less warehouse space dedicated to quarantined materials awaiting quality verification.
Additionally, improved accuracy in COA processing helps prevent costly mistakes that could lead to product recalls or wasted ingredients. In an industry where rising costs continue to pressure profit margins, these efficiency improvements offer welcome relief. The technology allows companies to maintain or improve quality standards without increasing quality control staffing.
Paul Bradley, Senior Director of Product Marketing at TraceGains, notes: “We designed IDP to deliver superior accuracy and reliability by continuously learning and improving with every use. Our AI-driven solution eliminates the inefficiencies of manual data verification, empowering brands to proactively manage supply chain quality and compliance.” This focus on continuous improvement ensures the investment in IDP technology continues to deliver value long-term.
Industry Reach and Implementation
TraceGains’ extensive industry presence positions them well for wide adoption of their IDP solution. With over 1,500 global clients, including more than half of the top 100 food and beverage manufacturers, the company has built a substantial network within the industry. This network encompasses 90,000 supplier locations and tracks over 600,000 ingredients and products.
The broad reach of the TraceGains network creates a powerful data ecosystem that benefits all participants. As more companies implement the IDP solution and process COAs through the system, the AI becomes more intelligent and accurate for everyone. This network effect has the potential to transform quality management across the entire food industry.
Implementation of the IDP solution appears straightforward for existing TraceGains customers, as it integrates seamlessly with their current systems. For organizations facing food manufacturing challenges related to quality control and compliance, this solution offers a relatively low-friction entry point into AI-powered quality management. The system’s ability to adapt to various document formats minimizes onboarding challenges for new suppliers.
The URL for more information about the solution (https://www.tracegains.com/idp-solution) provides interested companies with access to detailed implementation guides and case studies. This comprehensive support helps ensure successful deployment across organizations of various sizes and technical capabilities.
Future Innovations in Food Quality Management
TraceGains’ launch of the IDP solution represents just the beginning of their AI strategy for the food and beverage industry. The company has outlined plans to expand AI capabilities beyond COA processing in the coming year. This roadmap includes the development of sophisticated AI and agentic systems focused on quality/compliance and formulation tasks.
These upcoming innovations could potentially transform how food companies develop new products and maintain compliance with ever-changing regulations. By applying AI to formulation challenges, TraceGains may help companies quickly adapt recipes to address allergen concerns, supply chain disruptions, or emerging consumer preferences without compromising quality or safety.
The food industry has historically been cautious about adopting cutting-edge technologies, often waiting for proven results before implementation. TraceGains’ approach of starting with a specific, high-value use case like COA processing creates an entry point that demonstrates clear benefits while building trust in AI applications. This strategy may accelerate the adoption curve for more advanced applications in the future.
As these AI systems mature, they have the potential to create entirely new approaches to quality management in food manufacturing. Rather than simply automating existing processes, these tools may enable predictive quality management that identifies potential issues before they occur. This shift from reactive to proactive quality control represents a significant advancement for an industry where consumer safety is paramount.