SGS launches global food risk intelligence platform

Food manufacturers and suppliers are under pressure to manage fragmented regulatory requirements and rising product safety risks across international sourcing networks. In this context, testing and certification company SGS introduced the SGS Nexus platform to support predictive food safety and compliance management.

Combining regulatory monitoring with food risk analytics
The SGS Nexus platform combines the existing SGS Digicomply regulatory intelligence system with Agroknow’s food safety analytics tools. The integration brings together regulatory tracking, risk modelling and compliance documentation within a single digital supply chain intelligence environment.

The system integrates three main capability areas: SGS’s inspection and quality assurance data, regulatory monitoring from SGS Digicomply, and AI-supported food risk analytics developed by Agroknow. The objective is to enable earlier identification of regulatory changes and potential safety incidents affecting food manufacturers, ingredient suppliers and retailers.

Application areas include food processing, ingredient sourcing, private label manufacturing and international food distribution, where companies must continuously monitor supplier compliance and changing national food regulations.

Monitoring regulatory changes and emerging safety risks
The platform is designed to track global regulatory developments, food safety alerts and compliance requirements, linking them directly to product formulations and ingredient lists. This allows technical and regulatory teams to identify potential compliance gaps earlier in the product lifecycle.

Predictive risk detection functions analyse datasets such as product recalls, import refusals, border rejections and food safety monitoring programmes. Machine learning models are used to identify statistical patterns that may indicate emerging risks before they result in compliance failures or supply disruptions.

The system also supports audit preparation by converting external regulatory and safety data into structured documentation aligned with standards such as the Global Food Safety Initiative (GFSI) and the US Food Safety Modernization Act (FSMA).

Supplier risk benchmarking and audit preparation
Additional functionality focuses on supplier risk evaluation and audit planning. The platform enables benchmarking of suppliers and raw materials using external risk indicators and historical incident data to support sourcing decisions and annual audit scheduling.

Laboratory testing programmes can also be prioritised based on identified risk levels, allowing quality teams to allocate testing resources based on measurable exposure rather than fixed testing schedules.

AI-supported search tools allow users to query regulatory or safety datasets using natural language, enabling faster access to compliance information relevant to specific products, ingredients or markets.

Integration into enterprise software environments
In addition to the software-as-a-service (SaaS) platform, SGS Nexus will also be available through Data-as-a-Service (DaaS) interfaces. These allow integration of regulatory and food safety intelligence into enterprise software environments such as product lifecycle management (PLM) systems, enterprise resource planning (ERP) platforms and internal risk modelling tools.

This type of integration supports automated compliance checks and risk analysis within existing digital quality management workflows.

Supporting predictive food safety management
The development of SGS Nexus reflects a broader shift toward data-driven food safety management, where companies increasingly rely on integrated regulatory datasets and analytics tools rather than manual compliance tracking.

By combining regulatory intelligence, supplier risk analysis and predictive modelling in one platform, the system is intended to support a transition from reactive compliance processes toward predictive risk management approaches in global food production networks.

Edited by industrial journalist, Aishwarya Mambet, with AI-assistance.

www.sgs.com