The Next Era of Private Market Data Intelligence

In the beginning, there were no standards—no 10-Ks, no quarterly reports, no analyst calls.

If you were an investor in the 1800s, your knowledge of companies depended entirely on the whispers of your personal network or the headlines in yesterday’s newspaper. But things were about to change.

In 1863, amid the frenzy of railroad expansion and rampant speculation, Henry Varnum Poor, a lawyer and journalist by training, saw the chaos firsthand—and knew investors deserved better.

Poor began meticulously gathering detailed information on railroad companies. It was painstaking work: writing letters by hand to hundreds of railroads, waiting weeks or months for replies, following up persistently, and carefully reviewing dense, often inconsistent reports. He copied data manually, cross-checked figures, and verified every detail with precision.

After five years of dedicated effort, Poor published the first edition of Poor’s Railroad Manual in 1868, providing investors with standardized, reliable data on railroad companies for the very first time. Poor created one of the world’s first standardized databases of company information, compiled directly from primary sources.

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Two hundred years have passed, and the public markets have evolved dramatically. With the SEC enforcing rigorous disclosure standards, financial reports are standardized, accessible, and abundant. But in private markets, things haven’t changed nearly as much. Even today, gathering comprehensive, accurate data on private companies can feel as slow and manual as it did in Poor’s time.

Granted, aggregating private-market data no longer takes five years, thanks to computers, Google, and databases like PitchBook and Capital IQ. But at the same time, the sheer scale of available information—and the sheer number of companies—has exploded. Today, there are tens of millions of private companies and tens of thousands of investors in the U.S. each associated with hundreds of thousands of data points scattered across many different sources.

We have reached an inflection point. The exponential growth in private market complexity and data volume has pushed traditional databases beyond their limits and present major challenges. Researchers seeking companies that match specific criteria still wrestle with outdated databases, rigid filters, and stale information. To bridge the gap, they spend hours—or even days—on painstaking, manual, and error-prone research, piecing together company profiles from multiple sources. The result? Slow decision-making, overlooked opportunities, and persistent inefficiencies. Just as Poor recognized centuries ago, navigating a new era of information demands a fundamentally new approach.

Enter Capix.

Capix leverages neural search to transform the tedious, manual process of gathering private-market intelligence into an experience that takes minutes—not days. By constantly aggregating up-to-date structured and unstructured data from numerous trusted sources, Capix allows users to define precise criteria like “find PE firms that focus on middle-market healthcare deals and have raised a new fund in the last two years” and instantly surfaces relevant firms along with their profiles.

We stand at the threshold of a new era and believe AI can unlock unprecedented depth, accuracy, and coverage for private markets. That’s why we’re building a private-market data intelligence platform from the ground up as an AI-native solution. Henry Varnum Poor believed investors deserved better, and we carry that torch forward with Capix. Capix is more than just another database; it’s a complete reimagining of how private-market intelligence is gathered, refined, and served. It’s time to think bigger, move faster, and embrace a solution built for the demands of modern private-market complexity.

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Written by Bruno Jacob, CEO at Capix