AI Supply-Chain Traceability and Investigation

Project experienceLarge multinational apparel manufacturer

Turning supplier disclosures into connected supply-chain intelligence.

An AI-powered traceability and investigation platform for a large multinational apparel manufacturer, connecting supplier documentation, upstream relationships and sourcing evidence in a knowledge graph.

Knowledge graphsDocument intelligenceSupplier investigation
Explore AI-powered supply-chain intelligence
EvidenceOutstandingManufacturerFinal productSupplier AEvidence attachedSupplier BRequest outstandingFacility BUpstream materialSupplier CMissing evidence
Conceptual architecture
01

The challenge

A manufacturer may understand its direct suppliers while having much less visibility into the organisations supplying those suppliers. Materials pass through multiple businesses before reaching the final product, and the supporting records arrive in different formats, from different contacts and at different levels of completeness.

The client wanted to investigate sourcing beyond its immediate supplier relationships and build the evidence needed for compliance and supply-chain certification processes. Collecting documents was only the first step. The information had to be interpreted, connected to the correct entities and made useful for tracing relationships across multiple tiers.

That required a workflow capable of expanding with the supply chain itself, rather than relying on a static list of first-tier suppliers.

02

The solution

The platform combined supplier participation with AI-powered document processing and a connected knowledge graph. Suppliers submitted sourcing documentation and identified the businesses supplying their input materials. Those upstream organisations could then be notified to provide their own records and supplier information, extending the investigation through successive tiers.

AI processed the incoming material into information that could be mapped and linked across the supplier network. The knowledge graph provided the relationship structure: organisations, materials, sourcing declarations and supporting documents could be explored as connected evidence rather than isolated uploads.

The result was an investigation environment where teams could follow upstream relationships, examine the supporting material and identify where additional information was still required. The collection workflow and the graph informed one another: newly disclosed suppliers expanded the network and created the next set of evidence requests.

03

Technical architecture

01

Collection workflow

supplier submissions, contact capture, upstream invitations and submission tracking.

02

AI processing

document interpretation and structured information extraction for graph mapping.

03

Relationship layer

graph-backed links between suppliers, disclosed sourcing relationships and documentary evidence.

04

Platform foundation

Neo4j, Kafka-based data flows, TypeScript services and GraphQL/REST interfaces, drawing on the underlying supply-chain platform experience.

05

Investigation interface

connected views for exploring sourcing paths and reviewing available evidence.

DiscloseInviteSubmitAI processingKnowledge graphInvestigation
Conceptual architecture
04

An important engineering boundary

A supplier declaration, an AI-inferred relationship and a verified sourcing fact are different things. A traceability system must preserve that distinction. Missing declarations, inconsistent documents and incomplete upstream participation cannot become verified facts merely because they appear in the graph.

Similarly, an investigation can stop at an established source or a documented boundary, but a non-responsive supplier does not prove the chain is complete. Coverage and outstanding requests are part of the evidence picture.

05

What the work enabled

The platform connected the participation workflow with a usable representation of the supplier network. It supported the client's effort to investigate sourcing, gather supporting documentation and prepare evidence for compliance and certification activities. The software supported assurance work; certification remained an external decision based on the relevant evidence and requirements.

Explore AI-powered supply-chain intelligence

An AI-powered traceability and investigation platform for a large multinational apparel manufacturer, connecting supplier documentation, upstream relationships and sourcing evidence in a knowledge graph.

Explore AI-powered supply-chain intelligence