Product Update - Spring Release ´23

SGS DIGICOMPLY is the first Risk and Compliance platform using Generative AI

With our generative AI capabilities, we extract knowledge from expert-selected document sources and quickly validate it with citations, providing a significant improvement over our pioneering conversational AI capabilities.

You can now ask any question related to the most up-to-date data available in SGS DIGICOMPLY, just try this out, you'll be impressed, but watch out: always perform fact-checking before taking answers for granted! In its first version, the feature is available to all users but as we are constrained in capacity, we have set a limit of queries that you can perform based on your license profile.

Introducing the new restricted substances module - a completely redesigned module, with linkages to regulatory text and a faster-than-ever engine

We have significantly improved our search function and added some valuable features. The ability to easily find relevant restricted substances and put them into regulatory context will be very useful for our users.

The option to export the results as an Excel file and view a timeline of limit changes will improve the user experience and make it easier to collaborate with others. Live email notifications of relevant limit changes are also a great feature for users who need to stay up to date on regulatory changes.

Finally, user data integration will allow users to create customized views of use limits for specific substances, which will be very valuable for those who need to track specific substances closely. Overall, we have made some very important improvements to our search function and added some useful features that will be appreciated by our users.

Introducing the Food Safety Risks Predictive Dashboard

Want to stay up to date on the latest risks related to your products? With the Food Safety Risks Predictive Dashboard, it's more effortless than ever. The intuitively designed dashboard provides real-time insights into your product groups from numerous sources, complemented by AI-driven predictions. This makes it possible to track trends on current hazards, view predictions per commodity group and substance classes or individual substances, and understand when and where the problem first occurred.