Data fragmentation, adversarial nation-states, and how Strider is building the system that enables organizations to navigate the next frontier of strategic intelligence

In a world defined by the abundance of data, the scarcest resource has become clarity.

More data has been created in the last three years than in all of prior history combined, driven largely by advances in technology like artificial intelligence. Yet, insights remain scattered across domains. Information stays siloed within systems. Critical decisions are still being made from incomplete pictures, even as the raw material to complete them sits in plain sight.

This is the central intelligence challenge of our time: connecting fragmented data and translating it into actionable information in real-time. The same technologies driving this explosion of data have also given us the tools to make sense of it. Now what’s needed is an intelligence model grounded in openness, networked collaboration, and machine-speed cognition.

The Intelligence Paradox: More Data, Less Clarity

The intelligence model that carried nations through the last century was built around a simple premise: information was scarce and the side that could find it first won. Back then, the biggest challenge was collection. Intelligence apparatuses relied on information gathered through human sources (HUMINT) and electronic signals and systems (SIGINT). The side with the best spies, deepest networks, and most classified insights held the advantage. Today, that problem has inverted.

Most of the world’s data is now being created in the public domain through the mass digitization of public records, social and news media, and AI. As a result, the challenge has shifted from collection to connection. With so much information already in the open, the advantage belongs to whoever can synthesize it fastest and act with precision.

The Public-Private Divide

Traditionally, governments and the private sector have held different halves of the same intelligence map. Governments see threats through classified intelligence about foreign actors, strategic intent, and geopolitical context. The private sector sees terrain: real-time data about supply chains, innovation networks, talent flows, and operational risks. The seam between them has become one of the most consequential vulnerabilities for democratic security in a digitally networked world.

This divide has real operational consequences. Consider how sanctions work. Governments regularly sanction foreign organizations, removing their ability to conduct commerce with domestic entities. But without visibility into how sanctioned entities and their affiliates adapt—shifting ownership structures, spinning up new front companies, rerouting capital—the action is rendered largely meaningless. It’s a real-life game of Whac-A-Mole: you think you address the threat, yet it reappears under a different identity. The same dynamic plays out across export controls, investment screening, and supply chain security.

The private sector faces an equally critical gap. The bulk of the talent, technology, intellectual property, and supply chains that power democratic economies exists outside government. This makes private sector entities prime targets for adversarial nation-states executing whole-of-society campaigns to capture these assets. Yet without the strategic context that governments hold, most are navigating those threats blind.

Democracies must adopt a new economic security model by fusing collaboration and intelligence sharing across public and private domains. The competitive advantage will not come from matching the secrecy of authoritarian regimes—it will come from mastering openness.

A New Intelligence Model

The world is entering the Intelligence Age, in which power is determined by who can see clearly, decide quickly, and act with precision.

Building an intelligence model equal to this moment requires a fundamentally new approach—one built not on secrecy and silos, but on collaboration and connection. One that fosters deep cooperation between the traditional intelligence community and private-sector innovators. One that leverages cutting-edge technology and intelligence capabilities to defend against threats and ensure continued leadership in science, technology, and global security.

Open-source intelligence (OSINT) should sit at the center of this new model.

But data alone does not create insight—structure does. When powered by agentic AI that can plan, collect, and synthesize information at scale, OSINT becomes a dynamic foundation for modern intelligence. Analytical methodologies, combined with AI-driven analysis and human judgment, transform disparate signals into strategic intelligence. These frameworks clarify how nation-state actors acquire technology, move capital, recruit talent, and exploit the seams of open societies, turning complexity into context and information into decision-ready insight.

This structured approach, however, cannot operate in isolation. No single institution can see the full picture alone. But a federated system—where each entity contributes to and benefits from a shared operating picture—can. This is the other essential component of any new model: an architecture that enables trusted data exchange and AI-driven synthesis between public and private networks, bridging national security insight with economic reality.

This should be the new intelligence philosophy: connection, not classification—gaining insight from integration rather than isolation.

The System Strider Built

Strider has built the system that enables organizations to navigate the next frontier of strategic intelligence.

Strider OS is an agentic AI-native system designed to continuously ingest, process, and synthesize unstructured global data into structured outputs. In other words, an agentic data refinery. We take the fragmented, multilingual, and constantly shifting data that defines the modern risk environment and turn it into something organizations can leverage to make faster, more confident decisions. The system resolves identities across sources, maps relationships across jurisdictions, and surfaces what is relevant based on the context of the decision at hand.

Analysis that used to require weeks of skilled human effort can now be maintained as a live picture that reflects the world at the moment a decision needs to be made. The goal is clarity at the moment of decision: what matters, why it matters, and what to do next.

What This Means for Democratic Societies

The global competition for data dominance is one of the defining battles of the 21st century. The ability to collect, process, and control vast amounts of data is now critical to economic and geopolitical power. This dynamic changes everything—how organizations investigate risk, how governments analyze and share intelligence, and how societies understand the forces shaping security, innovation, and influence.

Meeting this moment demands an all-of-society approach to intelligence. That means governments, industry, and academic institutions must operate not as separate actors, but as nodes in a shared intelligence network.  They must come together to protect the talent being recruited, the technology being acquired, the intellectual property being stolen, and the supply chains being compromised.

The intelligence model for this moment must be built on data, accelerated by AI, and strengthened through collaboration across public and private domains. It will require governments and industry to master openness and finally operate from a shared picture—contributing to and benefiting from a common understanding of the landscape.

By aligning the vastness of OSINT, the speed of AI, the creativity of the private sector, and the authority of government, we can outthink and outpace closed regimes.

That is the frontier of strategic intelligence.

This piece, written by Greg Levesque, Strider CEO and Co-Founder, and Calder Walton, historian at the Harvard Kennedy School, was published in Foreign Policy on October 8, 2025.

The world is at an inflection point for intelligence and national security. The explosion of openly available data, paired with artificial intelligence (AI) capable of processing it at scale, is not just augmenting intelligence work—it’s redefining it. Intelligence is no longer only about secrets. It’s about using data to see clearly, decide quickly, and move first in a global technology race with profound geopolitical implications.

Today is unlike the world of 1947, the year of the CIA’s founding, when members of the intelligence community had to be hunters to find hidden secrets. Instead, data now permeates our daily existence, and intelligence can be collected globally and at scale within a digital environment. The game has changed beneath our feet. We are in the middle of renewed great-power rivalry, focused on winning the race for technologies of the future—AI, quantum computing, and synthetic biology. Mastery of these technologies will shape the geopolitical order of the next century.

History shows that paradigm shifts in technology and geopolitics demand a comparative paradigm shift in the U.S. intelligence community’s approach: from a closed, classified model to one grounded in openness, velocity, and cognition. At the center of this shift is open-source intelligence (OSINT). Powered by AI, OSINT isn’t a supplement to traditional intelligence. It is becoming the foundation.

First, OSINT must be framed as a national asset, particularly as data becomes a factor of production alongside land, labor, and capital in the AI era. Its applications cut across industry, academia, and government. Because its strength lies in accessibility and transparency, OSINT must be developed outside classified environments. That’s why it’s called “open.”

Yet many within the U.S. intelligence community still treat OSINT as secondary. That’s outdated thinking. With the vast majority of the world’s data now generated in open digital environments, OSINT must be the starting point for analysis. The question is no longer “What secrets can we uncover?” but “What does the open domain already reveal?”

Some have proposed the creation of a dedicated open-source U.S. intelligence agency. But this overlooks a key fact: The most valuable open-source work is being done outside the government. To fully realize OSINT’s potential, the United States must treat it as a national asset—not just a bureaucratic capability. That means building bridges between public and private, not more walls within the state. Instead, the private sector, where true innovation in emerging technologies such as AI lies, is far better placed to lead the United States’ future in developing scaled tools to advance the country’s intelligence and counterintelligence capabilities and doing so as colleagues operating a national asset.

Moreover, the ability of private sector intelligence providers to offer accurate, timely, and relevant insights is no longer in doubt. More than a decade ago, in 2013, the cybersecurity firm Mandiant was the first to discover the Chinese espionage group APT1. In 2016, CrowdStrike first identified Fancy Bear, the Russian hacking group. One recently retired former senior U.S. intelligence official who spoke on condition of anonymity estimated that about 95 percent of his previous work could have been obtained through OSINT.

More recently, relatively small and highly skilled teams such as those in Dow Chemical were able, for example, to harness openly and commercially available data to accurately predict Russia’s full-scale invasion of Ukraine in February 2022—ahead of many nation-states that were directly involved. Their capabilities, access to intelligence, and teams have only improved in the years since as corporate leaders deepen investment in and adoption of these tools given rapid shifts in geopolitics.

Less appreciated is a parallel revolution taking place in counterintelligence. That process, which is being equally driven by AI, has only just begun. As with intelligence more generally, the private sector, not governments, will drive forward a counterintelligence industry fit for purpose in the information era.

The U.S. intelligence community was built to counter the Soviet Union—a world of secrets, not sensors. It has evolved, but its structures and culture remain rooted in another era. Traditionally, intelligence meant collecting secret information, which was then analyzed and disseminated to decision-makers. In the past century, and even the early years of this century, intelligence required the resources of governments to pull off—to uncover the secrets that adversaries did not want discovered. And because intelligence concerned secrets, it required—almost as a matter of definition—secretive means of collection.

Today’s new digital environment offers vast amounts of information that, in the hands of the right data scientists, can be skillfully analyzed to uncover nonobvious insights. This is what the investigative reporting outfit Bellingcat has so skillfully publicly demonstrated, revealing the malign clandestine activities of the Russian government that would have previously, in the pre-digital world, been onerous tasks for Western intelligence services.

Instead of intelligence being concerned with secrets, today, it must be considered in a broader national framework: It’s about delivering advantages to decision-makers. Intelligence now is about data: who holds it; who controls it; and who can most efficiently process it, using machine learning and AI, to glean insights that enable precision in action. Whoever can achieve the latter will be the masters of this century.

If our understanding of intelligence is changing before our eyes, so too is counterintelligence. The latter can most usefully be understood as actions intended to defend against foreign intelligence offensives. One part of counterintelligence is counterespionage—catching spies, in popular parlance—but it is far broader, including activities meant to counter disinformation and even involving counterterrorism and counter-sabotage activities. Counterintelligence is one of the broadest areas of intelligence work, touching all parts of a target threat surface, whether government or private sector, for the simple reason that any part of that surface can fall prey to a hostile foreign actor.

Again, in the past century, counterintelligence was the domain of governments—it was concerned with government versus government action, nation-state versus nation-state. This is not how espionage is being waged today. Corporations stand on the front lines alongside governments in today’s tech-enabled espionage game.

To grasp the previous essence of counterintelligence, think of the nonglamorous but essential work of British intelligence officers described in the novels of John le Carré. It involved meticulous paperwork, cross-checking files, and often descended to mind-numbing activities such as scouring a foreign telephone directory in reverse to find a desired name attached to a telephone number. Within Britain’s intelligence services, there were real life officers similar to le Carré’s character Connie Sachs, who had an encyclopedic knowledge of Soviet espionage.

In the digital intelligence world unfolding before us today, Sachs would be an AI co-pilot processing real-time data flows across intelligence verticals. While the community works to incorporate AI and open-source capabilities, progress is constrained by classification, bureaucracy, and cultural resistance. Secrecy remains the coin of the realm.

To understand the precarious counterintelligence challenge facing the United States, it is necessary to appreciate how the People’s Republic of China, the principal strategic threat to the United States, understands intelligence.

China uses a whole-of-society approach to collecting intelligence, using all available means, people, and resources to steal Western military, commercial, and industrial data. It does so in fulfillment of a grand strategy, expressly enunciated by Chinese Communist Party (CCP) General Secretary Xi Jinping, intended to leapfrog ahead of the United States and become the world’s leading military and economic power.

To achieve Xi’s aim of “national rejuvenation,” the CCP blends military and civilian power and correspondingly draws little distinction between military and civilian targets in the West. Using increasingly authoritarian legislation passed under Xi, the CCP has expressly authorized its intelligence services to steal intellectual property from Western targets that cannot be developed by Chinese homegrown talent. Emerging technologies that will shape humanity this century, such as AI, quantum computing, and bioengineering, thus lie squarely within Beijing’s sights.

The CCP does not necessarily only steal secrets—it collects data of all kinds, some secret, some hiding in plain sight. This is where AI will prove to be so useful for the party—it is only through AI that the Chinese state will be able to glean insights from the vast quantity of data that it has already captured and continues to steal, storing these troves in mass data centers constructed across the country to hold domestic and foreign collected data. We can attest that the U.S.-China trade war, relaunched in April, has only intensified Chinese theft of U.S. intellectual property as the CCP tries to evade imposed trade barriers.

The Western bifurcation of public and private sectors, from an intelligence perspective, is a seam that U.S. adversaries such as China are systematically exploiting. On its own, the U.S. government cannot counter the scale of China’s intelligence offense, given its all-of-society model, which leverages gray-zone activities such as recruiting scientists or engineers inside U.S. companies to steal intellectual property. As of 2022, the FBI was opening a new China-related investigation every 12 hours. Before retiring as FBI director in January, Christopher Wray warned that China had stolen more U.S. personal and corporate data than every other country combined.

In response, a private sector counterintelligence industry is already forming as companies elevate their insider threat and security operations to tackle nation-state threats. In January, Meta CEO Mark Zuckerberg appeared on Joe Rogan’s podcast and, among other subjects, discussed the work of counterintelligence teams at Meta. Zuckerberg described their work as including identifying when platforms such as Facebook are being used by malicious actors.

It is not just Meta pursuing counterintelligence work. As of this writing, numerous job openings can be identified at leading tech companies that are, in essence, concerned with counterintelligence—at Apple, OpenAI, Meta, Amazon, Microsoft, Accenture, Crowdstrike, and Twitter/X. Every Big Tech company is adopting this model.

Unsurprisingly, the U.S. government is moving much more slowly. While the CIA, established in 1947, has undergone periodic bureaucratic updates over the years, its fundamental DNA remains broadly the same as it was nearly eight decades ago. If you were to conceive of an intelligence community fit for purpose in the 21st century, it would share many of the same objectives, but its shape would be entirely different.

In the meantime, given the pace of change and the geopolitical stakes confronting the United States, Washington should already be bolstering the tech industry’s ability to police and respond to nation state espionage.

The intelligence race is already underway—and the winners won’t be those who hoard secrets. They’ll be those who harness data, use AI, and collaborate. This is not just a transformation of tradecraft. It’s a redesign of intelligence itself. The United States should lead it.

Competing Governments and Global Economic Risks 

Today, many governments are using their international economic relationships to achieve their own strategic goals. Sometimes, this comes at the expense of their global partners. Countries like the PRC, Russia, and Iran often put this strategy to use to further their own technological interests, making it harder for businesses and academic institutions worldwide to protect themselves from these risks. 

That’s why Strider created Organizations Search, our third-party due diligence tool for security, compliance, and reputational insights. 

Huge Organizations Search Data Expansion 

This month, we’re excited to announce some major improvements to Organizations Search. These new milestones significantly contribute to our vision of Organizations Search being a comprehensive risk screening solution for strategic state-sponsored intervention in the global economy.  

Most notably, Organizations Search now includes government registration records for 200 million legal entities located in the United States, Canada, Europe, and Japan. Integration of this data into Organizations Search reflects the rapid maturation of Strider’s ability to illuminate risky economic connections around the world, not just within regions of special concern. 

In the coming year, we’ll be adding even more data sources related to cross-border trade, ownership, and other economic relationships. With these updates, our clients will gain an even deeper understanding of which organizations might pose a risk due to their economic connections. After all, state-sponsored actors don’t limit themselves to their home countries—they own, trade with, and collaborate with millions of organizations around the world. Our clients know this and are looking for scalable solutions to manage these risks. 

New Data from Russia and Iran 

We’re also excited to announce two new data additions specifically focused on Russia and Iran.  

First, we’ve added over 5 million supplier relationships from Russian government procurement records. This data shows which commercial firms in Russia have contracts with military, defense, and government end users. Understanding these connections can help our users identify companies with economic incentives to align with Russian government priorities. 

Second, we’ve added 2 million legal entities from Iran’s business registration system. This will help our users gain more insights into businesses operating in that often opaque region. 

Looking Ahead 

In today’s unpredictable globalized business environment, this type of comprehensive due diligence is more critical than ever before. 

These updates are just the beginning. We have many more exciting data expansions and features planned for Organizations Search in the coming months. These enhancements will further empower our users to screen broadly and deeply for state-sponsored risks within their global economic footprints.  

Learn more about Organizations Search here.

Request a demo to see what insights Organizations Search can unlock for your organization.

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A personal note from CEO and co-founder Greg Levesque

Since our inception, Strider has been committed to redefining the landscape of intelligence. We’ve championed the cause of open-source intelligence, offering strategic insights that empower organizations to navigate the complexities of a new geopolitical environment – defined by strategic competition. Our mission has always been marked by continual innovation, and we continue to harness the power of advancements in AI and machine learning to provide cutting-edge solutions. 

Generative AI has emerged as a transformative force, opening doors to imagine new capabilities and use cases. I’m excited to announce a pivotal moment in our evolution as we take the first steps to integrate this technology into our product portfolio. 

Today we’re introducing Spark AI, a generative AI-powered data search capability integrated into our Organizations Search product. Implemented as an in-product chat function, Spark AI will transform the way you interact with Strider data—currently over 10 billion documents from over 40,000 sources globally. 

Spark AI represents a significant milestone in our pursuit to make high-value, curated data accessible to our clients. This blend allows for unparalleled insights and provides faster access to crucial information, including the source documents that underpin our intelligence.  

At Strider, we’re always looking for the best ways to place a wealth of actionable data at the fingertips of our clients, and Spark AI is a giant leap towards that objective. The first dataset enabled in Spark AI will allow users to access unrivaled foreign procurement information cross-referenced with corporate data and commercial networks. In the coming weeks and months, additional datasets will become available to enhance our offerings and create new use cases and capabilities. Client feedback will be crucial as we chart this exciting path forward, and this is just scratching the surface of what’s possible. 

I want to emphasize the impact Spark AI will have on our community. For our enterprise clients, it represents a game-changing capability to facilitate rapid insights from traditionally difficult-to-access sources. This is the beginning of corporations being able to establish nation-state level intelligence capabilities in-house, leveraging both external and internal data and combining it with generative AI. This will help to reduce costs while enhancing security operations, strategic planning, M&A decisions, and more. 

For government agencies, the combination of open-source intelligence and generative AI marks the launch of a profound transformation. For example, it enables us to reimagine economic security tools, notably contested supply chains, export controls, sanctions, and foreign investment screening. Data has become a new factor of production, and generative AI is key to unleashing its full potential. 

Spark AI is an exciting component of our mission to empower organizations with the insights they need to thrive in an increasingly complex world. We’ll continue to expand, refine, and enhance our offerings, working together with our partners to drive progress and unlock intelligence to its highest capacity. 

Thank you for being part of this journey. 

With Respect, 

Greg Levesque  

CEO & Co-Founder 

The Power of Procurement Data 

Procurement data plays a pivotal role in organizations today. When properly utilized, it serves as the informational backbone for strategic decision-making and operational efficiency.  

By capturing essential details about supplier relationships, purchasing activities, costs, and performance metrics, procurement data empowers organizations to optimize their supply chains, ensure compliance, and enhance transparency. This data not only aids in informed procurement decisions but also helps mitigate risks, streamline processes, and foster accountability. 

And now with the integration of Spark AI in our Organizations Search product, clients can get critical access to procurement data by simply asking a question. 

Utilizing Spark AI 

Spark AI is Strider’s latest capability harnessing generative AI technology. Implemented as a chat function in Organizations Search, Spark AI revolutionizes the way you access, analyze, and utilize Strider’s procurement data. Simply type in a question relating to procurement history and get immediate answers about organizations, goods, and services that have transactional history with nation-state governments, defense, and military organizations. Source documents are always included for rapid verification.  

Spark AI makes procurement information more easily accessible and can reveal gaps and opportunities that organizations might not be privy to otherwise. Here are a few ways Spark AI can be a crucial addition to the procurement process: 

Spark AI Can Reveal Supplier Relationships 

Spark AI Can Help Mitigate Risk  

Spark AI Can Help with Regulatory Compliance 

Spark AI in Action 

Here’s just one example of how Organizations Search and Spark AI can work in tandem. An institution using Organizations Search discovers that one of their suppliers has a Risk Signal of “Military Ties.” Organizations Search data reveals that this supplier appears on a list of registered defense industry suppliers maintained by the People’s Liberation Army. The user can then turn to Spark AI’s chat feature and ask what that specific company supplied to the People’s Liberation Army in a specified timeframe. Spark AI will offer an answer in simple text along with source documents of that procurement data. That organization can then search for other potential suppliers that have a more compliant track record if necessary.  

Conclusion 

Spark AI is your key to unlocking unparalleled access to our proprietary data assets. Better ensure security and compliance, strengthen your supply chain relationships, and leverage Strider’s growing procurement data. Request a demo today to see Spark AI in action.  

Open-source intelligence is the backbone of Strider Technologies, and a growing critical asset in today’s global economy for economic development and strengthening national security. Greg Levesque, Strider’s CEO and co-founder, talked on the subject in a recent SCSP NatSecTech podcast hosted by Jean Meserve, which you can listen to here. Greg was joined by Varun Vira, COO of C4ADS, a nonprofit utilizing open-source data to target transnational illicit networks. Below we’ll highlight five key takeaways from their conversation. 

We’re in a golden age of open-source data 

Data made publicly available on the internet has been expanding rapidly over the past decade. The Covid-19 pandemic only accelerated the push of data and information online. Nefarious governments are increasingly using this publicly available information to target private industry and academia. Companies are on the frontlines of this new geopolitical battle. 

Open-source data reliability is found in its scale 

Some have wondered if open-source data is reliable, particularly when it comes to incorporating it into security and critical business processes. But when large amounts of data are integrated, they can reinforce each other boosting confidence in its veracity. This reinforcement of disparate data points validating the same story offers a high degree of confidence in the accuracy of the information. But it’s important to validate the data and be careful not to jump to conclusions before investigating biases and data gaps that may be present. 

Governments aren’t efficiently leveraging open-source data—except one 

The U.S. government—and most other governments—is behind the curve in leveraging open-source data. There are efforts to ramp up the use of open-source data and begin to look at it as a key ingredient in various U.S. government mission sets. 

On the other hand, the People’s Republic of China (PRC) is doing an exceptional job of utilizing open-source data, particularly when it comes to mapping scientific talent around the world. They create scores for experts in technologies they’re interested in, and in some cases, even include an estimated cost to recruit that person. This type of data collection is not limited to academia but looks at talent in companies as well. This data is then used to fill domestic gaps within their own industries or technology fields. “The shocking thing for me,” Greg notes, “is the scope and scale of the activity. It’s happening in companies. It’s happening in universities. It’s not just a government-to-government issue.” 

The government’s adoption bottlenecks: processing and leveraging data 

The challenge for companies and governments alike is not acquiring data, it’s processing it in a way to derive value. A faster approach is required to increase efficiency, and governments must leverage private sector innovations to rapidly scale their capabilities. And while establishing a dedicated open-source agency is an option for the U.S. government, a cultural shift is also needed to accelerate the adoption and application of open-source data.  

Government and industry should collaborate  

To advance national interests and security, it’s critical for governments and industry to collaborate to maximize the value derived from utilizing open-source data. By joining forces, we can develop new capabilities that enhance government’s ability to advance its mission—whether that’s grant making, ensuring compliance with export controls, or supply chain resiliency. There’s a strategic opportunity for government to reposition and synchronize its efforts with the private sector.  

At Strider, we transform open-source data to provide meaningful insights for companies and governments alike to secure their technology and find new ways to compete. Learn more about our products and solutions or book a demo to see our intelligence in action.