Research Security Realities and How to Overcome Them

Every year, our adversaries inflict hundreds of billions of dollars of economic damage to U.S. institutions and corporations. They do it by unlawfully accessing academic and corporate research to steal American innovation, disrupt supply chains, commit economic espionage, execute malign foreign talent recruitment programs, infiltrate networks and infect our investment capital across all industries – especially in the areas of critical infrastructure and emerging technologies.  

The current set of tools available to research security professionals is fragmented. There are multiple players in multiple capability spaces and very few offering a comprehensive suite of capabilities that truly serve to secure the innovation enterprise. The problem is simply too big, and the stakes are too high to get one piece of the puzzle right.

Today’s research security professionals would be wise to consider the broad set of capabilities they need and to examine the vendors who can reliably and comprehensibly provide them and who can continually evolve their offerings as both the threat landscape and the technology landscape evolve. As we see it, the current operating reality for research security officers (RSOs) looks like this:

Fragmentation is the core operational problem. In this environment, RSOs are forced to “tool-chain” their workflow. In practice, this means research security teams must jump across disconnected products and manual steps to assemble identity, affiliation, collaboration, funding, and risk context. This drives inconsistent decision making, creates longer cycle times, and persists preventable and avoidable blind spots.

The market is shifting from point tools to workflow platforms that unify data provenance. What RSOs increasingly need is not another single-purpose dataset, but a platform that consolidates and preserves provenance across various data sources.  This allows them to make defensible and risk-based decisions and determinations so that every assessment is traceable, reproducible, and audit-ready.

Platforms must be built around the RSO workflow and fuse the right categories of end-to-end data. In recognition of this need, our work at Finch AI does not rely on a singular data source. Instead, we integrate the domains that RSOs actually depend on, including corporate data (ownership, subsidiaries, control), academic and research data (affiliations, publications, collaborations), threat-country-specific data (state-linked entities, priority sectors, and other contextual signals). Then, we bring them together into one operational environment.

AI is an accelerator enabling faster quantitative and qualitative risk evaluation. With consolidated data and provenance as the foundation, Finch AI applies AI to expedite both quantitative analysis (entity resolution, network relationships, change detection) and qualitative synthesis (contextual narratives, evidence-based summaries) to support consistent, defensible decisions at scale.

With this important context in mind, RSOs must have mission partners who not only understand the current research security landscape, but who can help them navigate challenges and thrive. In our work as part of the National Science Foundation’s SECURE Analytics partnership, we do precisely that. Together, we are building a next-generation research security platform that meets the moment with fit-for-purpose capabilities that secure the innovation enterprise and protect American national and economic security.

To learn more about what we’re doing and how we might partner to apply these same principles to your mission, please get in touch at info@finchai.com.

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