AI reads supplier documents such as safety data sheets (SDS) and specifications, pulls out the key data and places it in the right fields of your system. Instead of retyping hazard classifications and ingredient lists by hand, regulatory, EHS and R&D teams review what the AI extracted and approve it. The result is faster onboarding, fewer typing errors and more consistent data.
Every raw material comes with paperwork: safety data sheets, specifications, certificates of analysis and technical data sheets. Most arrive as PDFs, often in different languages. Teams manage large numbers of them, and each document can be updated several times over the life of a material. The data they hold is critical: it drives hazard classification, labels and safety data sheets.
Getting that information into a system usually means a specialist reads each document and retypes the data. This creates three problems:
A supplier SDS follows a standard structure. Section 2 covers hazard identification, including the GHS classification. Section 3 covers composition and ingredients. These two sections hold the data regulatory teams need most, and they take the longest to retype.
In Trace One SDS, the process works like this:
In Trace One SDS, AI extracts hazard classification and composition data from Sections 2 and 3 of supplier SDS PDFs. The regulatory expert reviews, edits and approves the result.
The same approach applies to product development. During raw material onboarding in Trace One PLM, AI extracts the relevant information from supplier specification documents and maps it to the right fields. R&D and quality teams get usable raw material data in the system faster, without retyping it from the PDF. For cosmetics and chemical manufacturers, the Supply Chain Assistant add-on in Trace One Devex PLM also extracts Section 2 (hazard identification) and Section 3 (composition) from supplier SDS files into fields that stay editable until someone validates them.
AI extraction is fast, but it is not the final word. Supplier documents can be incomplete, outdated or unclear, and AI output can be wrong. Experts stay in charge of three things:
AI that authors a complete SDS or updates it on its own, without review, is not what regulated teams need. The value is in removing the retyping so experts spend their time checking and deciding.
AI removes the typing, not the judgment. Every extraction is reviewed by an expert before it drives a classification, label or safety data sheet.
Supplier data feeds everything that comes after it: hazard classification of your own mixtures, labels, your own safety data sheets and regulatory reports. When supplier data is entered the same way every time, those downstream results are more consistent and easier to trust.
In Trace One SDS, extracted supplier formulation data connects to the material record, so it flows into classification and labeling work without being entered twice.
How AI speeds up product development beyond documents: How does AI speed up time to market in product development?
What AI can do in Trace One PLM today and how it protects your data: AI in PLM with Trace One
Trace One is a global provider of AI-native Product Lifecycle Management (PLM) and regulatory compliance software for the food & beverage, cosmetics & personal care, and specialty chemical industries. With more than 30 years of industry expertise, the company helps over 9,000 brands worldwide develop, launch, and manage remarkable products faster. Purpose-built for formula-based product development, its platform connects the entire product lifecycle from ideation to launch, with integrated regulatory intelligence spanning 170+ countries. Learn more at traceone.com.