Boardroom Insiders: A Solo-Founded Executive Database Hits $5M ARR, Sells for $25M — Winning With “Human-Curated Data”

The Big Picture

The Contrarian Bet on “Human-Powered Data”

Boardroom Insiders’ product is a collection of detailed profiles of individual Fortune 500 executives (career history, public statements, priorities, even personality) all compiled by hand. B2B salespeople and consultants use it to prepare for executive meetings. It started from a gap Gillenwater saw firsthand while consulting for a major tech company: in her own words, “salespeople didn’t know how to pitch the C-suite, or what to even talk about.” She turned that prep material into a product. Including the upper-tier BI Pro offering (relationship maps and alerts), the profile count passed 29,000 by 2022.

Because each entry is researched and written by hand, one at a time, scaling is slow, but that very slowness became the barrier to entry. Data that can be crawled mechanically can be replicated by any competitor. Data that a human has read through and editorially contextualized is expensive to copy, and since the executive roster keeps turning over, only an organization that keeps updating it (in this case, a 25-person research team in India) can sustain it. It stands as the “human-curated data” counterpart to BuiltWith, whose machine-collected data reached $14M ARR with one person.

Only $200K Raised, 85% of Equity Retained

Capital strategy is another core piece of this story. Initial funding came from Gillenwater’s own consulting income (five figures a month). Later came $125K from a friend’s company-sale windfall, and about $75K more from family and friends, total outside funding capped at $200K, with equity given up held to roughly 15%. Having grown the company to $5M ARR over 14 years without VC money, Gillenwater, the largest shareholder, personally received a gross $13M (about ¥1.95B) at the $25M sale. Against $200K of outside capital, the total distribution to all shareholders was $22.5M. A design of low dilution and a long time horizon left nearly all of the exit’s upside with the founder.

Why It Commanded a 5x Revenue Valuation

The aggressive $25M valuation against $5M ARR comes down to the nature of data businesses. Gross margins are high (once created, the same data can be sold to any number of companies), and churn is low (annual licenses of $50K-$300K, once embedded in a sales organization’s workflow, become hard to remove). For an information giant like Euromoney, on top of that, the math is simple: plug the product into its existing customer network and revenue grows. For SaaS businesses that sell data, the ultimate buyer is an information giant that sells other data to the same customers. Major financial and corporate-information companies are always hunting for data assets, and even niche data commands high multiples if it is “data that exists nowhere else.”

The process timeline is also on the record. The decision to sell was made in spring 2021, the advisor-led process started that September, and the deal closed on January 20, 2022, about nine months from decision to closing.

Anatomy of the $25M — a Take-Home of About $9M

The sale price didn’t land straight in the founder’s bank account. This is a rare case where the cost breakdown itself is public.

The M&A advisor alone took 4% of the sale price. After fees and taxes, the gross $13M shrinks to about $9M. And even so, $800K was distributed as phantom equity to 13 employees who held no stock. Few cases disclose, down to this level of detail, how the money actually flows inside a headline “sold for $25M.”

What to Discount — This Wasn’t a “Solo SaaS”

“Started solo” is accurate. “Did it all solo” isn’t. At the time of sale the team was 28 full-time staff plus 27 more in research and development, over 50 people total, since a human-curated database is, in essence, an editorial organization as the product. Compared to the BuiltWith model (one person plus automated collection), this structure lags in margin and agility. Speed tells the same story: 14 years from founding to $5M ARR, human curation grows on this kind of timeline, and it doesn’t mesh well with a design aimed at a fast exit. There’s also an open question about how much staying power “researched and written by a human” retains now that generative AI has made information gathering and summarization cheap. This sale closed in January 2022, right before that inflection point.

Conditions for Reproducing This, and the Limits

Two things here would work the same way anywhere: “editing information someone will pay dearly for into a buyable form” can be started solo, with no technical background required, and the capital strategy of low dilution over a long time horizon is available to anyone patient enough. Gillenwater wasn’t an engineer. The core of this business was editorial, not software. On the other hand, a $50K-$300K annual price point presupposes Fortune 500 sales budgets, and doesn’t work in a market with a thin layer of high-paying enterprise customers. Anyone considering this in Japan should look, before replicating executive-profile data specifically, for niche information that’s costly to keep updated and cuts directly into a buyer’s workflow. Read alongside Microgrid Knowledge’s sale of a niche information asset, this is worth reading as a pattern for carrying “information editing” all the way to an exit.

Related Reading

• BuiltWith — the solo “machine-collected data” SaaS at the opposite pole
• Microgrid Knowledge — a comparable sale of a niche information asset