Artificial Intelligence (AI) in PLM

AI in PLM Software

Examples of AI in PLM software include applications of predictive AI, which can forecast potential risks and errors, to identify problems before they begin in the product development process. AI in PLM can recommend the best ingredients or packaging components to improve products and reduce costs, enabling quicker decision-making, while also making it quicker and easier to search for information to meet consumer, market and regulatory requirements.  

At Trace One, we’ve been hearing from our customers that they’re already seeing the power of generative AI for marketing teams. Now, they’re excited about generative AI in PLM for R&D teams and quality managers. They’re looking forward to how AI can increase efficiency and maximize return on investment (ROI) when entering and extracting information for product development and management.

PLM software has reshaped new product development and introduction (NPDI). for the food & beverage, cosmetics & personal care, and specialty chemical industries. Trace One PLM solutions empower brands and suppliers across the entire supply chain to work together directly on shared product data. PLM software also helps businesses navigate global regulatory requirements, which have increased over the past 30 years. As market pressures require NPDI to be timely and cost-effective, continued enhancements in PLM help businesses launch new products with the confidence to know they’re viable, feasible, and proactively planned. 

Recent technological advancements in PLM include: 

• Transitioning from on-premise to the cloud providers, maintaining the security of an enterprise cloud solution, and the speed, flexibility, cost-efficiency, and easy integration of software as a service (SaaS). 

• The integration of regulatory compliance regulation data helped customers to make the right decisions for their products as they manage ongoing compliance checks, monitor changing laws, and ensure products remain compliant and competitive in every market. 

• Integration with legacy systems synchronizes repositories across products, suppliers, and brands for seamless product data sharing. 

• The evolution of process PLMs from discrete PLMs facilitates collaboration without spreadsheet clutter and sifting through email threads. Trace One has created a single platform that both suppliers and retailers use. 

• Over time, Trace One created solutions that go beyond PLM: e-sourcing, artwork management, etc. All linked to the same product and supplier information with Master Data and sharable across several solutions. 

As PLM software has evolved, different forms of data have become more inter-connected, and the amount of data has grown significantly, as has the focus on data quality. Large, high-quality data sources, and many process steps to optimize, means that there are many PLM AI use cases that can have big impacts on your NPDI development process. 

Current State: AI in Trace One PLM

We’ve partnered with Google Vertex AI and Microsoft Azure OpenAI to empower AI in PLM.

We selected these trusted partners to provide cutting-edge technology and consistent updates to ensure a top-tier customer experience. We know that your proprietary data and its safety are crucial to your business, and so we are working with cloud providers who are dedicated to safely and securely developing AI solutions for enterprise. 

AI technology is rolling out across Trace One’s PLM software suite, bringing instant advantages to many parts of the NPDI process. Here are some of the latest features: 

Extracting data during raw materials onboarding 

Manufacturers and brands spend tremendous amounts of time on raw materials onboarding, which often requires manual data entry of thousands of pages of information. In addition to being time-consuming, this process is also error-prone, as it’s almost impossible to avoid making mistakes with a large amount of data entry. But the AI-powered feature automatically extracts relevant information from supplier specification documents, resulting in cost savings through increased efficiency, accuracy, and productivity. It processes common document types and formats, and seamlessly maps the extracted data to existing system attributes, quickly making the data available in the PLM system.  

Natural language inquiries on product regulations  

Complying with global regulations is also time-consuming, as regulations are complex and vary across countries, requiring an encyclopedic and up-to-date knowledge of a large amount of information. With the AI-powered feature, regulatory affairs staff can ask questions in natural language, like “Give me a summary of the changes in Codex 2022 compared to Codex 2019” or “What substances am I not allowed to use in food supplements in France?” This improves the user experience and results in increased ROI due to increased efficiency, reduced training time for new users, and faster go-to-market time. 

Finished product certificates 

Certificates play a key role in managing production sites and products in master data. To enhance this process, we introduced an AI-based innovation that automates and simplifies certificate management, improving efficiency and data accuracy while offering an enhanced user experience.   

Currently, suppliers can enter certificates for their production sites in the master data view. Our recent updates to our offering extend the scope of possible actions for these suppliers by giving them access to product lists and enabling them to add certificates at the product level. 

Future State: AI in Trace One PLM