Supply Chain Intelligence

1. Macro Intelligence: Global Supply Chain Restructuring

The geography of global trade is undergoing its most significant transformation in decades. Geopolitical tensions, from U.S.-China decoupling to sanctions regimes and regional trade bloc formation, are forcing multinational firms to reconsider supply chain architectures built on decades of globalization. Simultaneously, the rapid diffusion of AI technologies is reshaping where production concentrates, which logistics corridors gain strategic importance, and how firms make sourcing decisions at scale.

Our research takes a macro structural view of these shifts. We track how trade flows are being rerouted, how new supplier ecosystems are forming in emerging regions, and where critical dependencies and vulnerabilities are concentrating. By combining international trade statistics, policy analysis, and network modeling, we aim to produce a forward-looking picture of how global supply chains will be reconfigured over the coming decade.

2. Network & Credit Analytics: From Graph to Risk

Behind every global supply chain lies a complex web of interconnected dependencies. Yet, traditional risk frameworks often treat firms as isolated entities, ignoring the critical vulnerabilities hidden within their structural positions. Our research operates on the principle that network topology is, in itself, a fundamental risk signal.

We investigate how disruptive events and localized shocks propagate through global trade networks. Rather than viewing supply chains as static lists of buyers and sellers, we analyze them as dynamic systems susceptible to cascading failures. By mapping these structural characteristics, we aim to uncover hidden risks—from systemic bottlenecks and critical hubs at the macro level, to fragile, multi-tier dependencies at the firm level. Our event studies focus on understanding how these networks fracture and adapt under the pressures of geopolitical realignment, economic shifts, or unexpected disruptions.

Ultimately, these network-derived insights power a new paradigm for risk assessment. We translate complex topological data into structural credit evaluations and event-risk models. By assessing a firm's resilience, exposure, and centrality within its broader trade network, we provide a more accurate, predictive measure of counterparty risk and operational stability than traditional financial statements alone can offer.

3. Data Platform & Simulation: Intelligence in Action

Research insight is only valuable if it can be acted upon. To close the gap between analysis and decision-making, we have built two complementary operational tools.

The first is an interactive analytics dashboard powered by global customs and trade data. The platform aggregates cross-border shipment records across dozens of countries, enabling users to visualize trade flows, track supplier relationships, monitor market concentration, and detect anomalies in real time. Embedded within the dashboard is a domain-specialized AI agent that allows users to query complex supply chain questions in natural language, bridging the gap between raw data and actionable intelligence even for non-technical stakeholders.

The second is a supply chain simulation engine. Real supply chains are dynamic systems: a factory shutdown, a port disruption, or a sudden demand spike can trigger cascading effects that are difficult to anticipate. Our simulation framework models the propagation of supply and demand shocks through a network, allowing researchers and practitioners to run structured scenario analyses, stress-test sourcing strategies, evaluate policy interventions, and rehearse responses to disruption before they occur in the real world.