Trust is the Scarce Resource – Why Sayari’s relationship intelligence is essential to global commerce

There has never been more information available about the global economy. Yet there has never been greater uncertainty about what is true.

Artificial intelligence has made information more abundant than ever. It can generate convincing answers in an instant. But AI cannot determine whether the underlying information is accurate. It cannot reliably distinguish between legitimate and fraudulent relationships, hidden ownership structures, or commercial networks purposely designed to conceal risk.

As AI makes information abundant, trust becomes the scarce resource.

The organizations that possess enduring value won’t be those with the most information. They’ll be the ones with the most trusted information.

That shift is fundamentally changing how governments investigate financial crime, how financial institutions manage risk, and how global enterprises understand the suppliers, customers, and counterparties that support their businesses. The question is no longer whether organizations have enough information – it is whether they can trust it.

By connecting corporate registries, beneficial ownership records, customs and trade data, shipping records, sanctions information, court filings, and hundreds of other authoritative public sources, Sayari reveals the commercial relationships that connect companies, suppliers, owners, subsidiaries, intermediaries, and global trade networks.

Today, its Knowledge Graph is the model of global commerce: 1.5 billion or more entities across 250+ jurisdictions, with lineage back to 2015, creating one of the world’s most comprehensive maps of commercial relationships.

When MissionOG invested in Sayari in 2020, we believed that understanding global commercial relationships would become dramatically more important. Static databases and point-in-time diligence efforts were not built for a world where risk moves through ownership chains, suppliers, subsidiaries, intermediaries, and cross border trade networks.

That belief has only strengthened.

Sayari illustrates the pattern we seek at MissionOG: an operational problem that grows more urgent over time, a differentiated data advantage, deep integration into critical customer workflows, and a platform that expands as customer needs become more complex. That pattern shaped our original investment in Sayari and continues to inform how we invest today.

Its founding insight remains simple: organizations cannot effectively manage risk if they don’t fully understand who they are doing business with.

That challenge has become significantly more urgent over the past several years. Global commerce increasingly sits at the intersection of geopolitics, regulation, national security, and financial crime. Following Russia’s invasion of Ukraine, sanctions expanded dramatically across jurisdictions. Export controls and tariffs have become key tools of industrial and national security policy. The Uyghur Forced Labor Prevention Act raised expectations around supply chain transparency. Organizations increasingly face pressure to understand not only their direct counterparties, but also the ownership structures and commercial relationships hidden layers beneath them.

Financial crime has become more sophisticated. Trade-based money laundering, shell companies, layered ownership structures, and complex cross-border commercial networks are often used to conceal illicit activity, evade sanctions, and disguise beneficial ownership. Financial regulators continue to warn that increasingly sophisticated criminal organizations exploit legitimate trade and corporate structures to obscure the movement of goods, capital, and commercial relationships.

The challenge is no longer collecting more information. It is connecting the right information and then proving it. This is precisely where Sayari has differentiated itself. Rather than creating another corporate database, Sayari has built a platform that connects corporate registries, beneficial ownership records, customs and trade data, shipping records, sanctions lists, court filings, and other authoritative public sources into a unified view of global commercial relationships. Instead of simply identifying companies, Sayari helps organizations understand who ultimately stands behind them.

The platform’s impact is increasingly evident across both the public and private sectors. Publicly disclosed customers and use cases include government agencies, global manufacturers, financial institutions, and logistics providers. Honeywell has described using Sayari to strengthen third-party risk management across its global supplier ecosystem. Financial institutions use the platform to improve sanctions investigations and beneficial ownership analysis. Government agencies rely on Sayari to support trade enforcement, export control investigations, supply chain risk analysis, and efforts to identify illicit financial networks designed to remain hidden. The Company’s work supporting U.S. Customs and Border Protection further demonstrates how relationship intelligence is becoming essential to enforcing increasingly complex supply chain regulations.

Whether serving government agencies, manufacturers, logistics providers, or global financial institutions, the underlying requirement is consistent: organizations cannot manage risks they cannot see.

We think of Sayari as providing the trusted relationships behind the data – the relationships that give information meaning. The distinction matters. Traditional databases answer questions about individual entities. Sayari answers questions about relationships.

Risk is rarely isolated to a single company. It exists across ownership chains, suppliers, subsidiaries, intermediaries, shipping networks, and beneficial owners. Understanding those relationships (not simply the entities themselves) is what enables governments and enterprises to identify risks that would otherwise remain invisible.

We believe Sayari’s advantage compounds because the platform becomes more valuable as it adds more jurisdictions, ownership records, trade documents, customer workflows, and relationship context. In markets like this, breadth matters. Source quality, traceability, depth of customer workflow – it all matters.

That combination is hard to replicate.

Importantly, Sayari has not simply benefited from these market shifts, it has executed alongside them. It has expanded its reach across government agencies, financial institutions, manufacturers, logistics providers, and many of the world’s largest enterprises. That ability to grow alongside customer needs is one of the defining characteristics we look for in enduring enterprise focused technology companies.

In high-consequence environments, answers cannot simply be plausible. They must be explainable, verifiable, and traceable back to authoritative sources. As AI lowers the cost of generating information (and increasingly, misinformation) the value of trusted underlying data only increases. We believe the next generation of enterprise software will increasingly be defined not by how much information it organizes, but by how effectively it establishes trust in that information.

Looking back, our conviction has grown not simply because Sayari has executed well. It has grown because the forces that shaped our original investment thesis have become even more pronounced. Global commerce has become more interconnected. Financial crime has become more sophisticated. Regulatory expectations have expanded. AI has accelerated the creation of information while increasing the value of trusted, verifiable data.

These are not temporary trends. They represent a fundamental shift in how organizations must make decisions. As AI makes information abundant, trust becomes the scarce resource. We believe the next generation of enterprise software won’t simply organize information; it will provide trust.

As such, we believe companies like Sayari will become increasingly important. The organizations that create enduring value will be those that help customers make better decisions when the cost of being wrong is extraordinarily high.