Scouly is a deal-sourcing tool for people buying small businesses. It scores 173,769 companies that are not for sale, using only records the government already publishes, and ranks them against whatever acquisition thesis you give it.
It is not a marketplace. Nothing on this site is listed, there are no brokers, and there is no inventory. If a business shows up in Scouly it is because its public filings suggest the owner may be approaching a transition, not because anyone asked to sell.
The businesses worth buying usually change hands before a listing exists. Someone already close to the company hears the owner is tired and makes an offer. By the time a business reaches BizBuySell the buyer is competing with thirty or forty other people and the price reflects that.
But the signal that an owner is getting close to a decision is often sitting in a federal file years ahead of time. The SBA publishes every 7(a) and 504 loan it approves, including the term. Add the term to the approval date and you get a maturity year, which is a dated moment when the owner has to refinance or sell. State registries publish formation dates, so operating age is documented rather than guessed. OpenStreetMap is good enough to measure whether a local market is fragmented or already consolidated.
None of that is secret. It is just tedious to assemble, which is the whole product.
| Source | Publisher | What it establishes |
|---|---|---|
| 7(a) and 504 loan disclosure | US Small Business Administration | Loan amount, approval date, disclosed term, and therefore scheduled maturity |
| PPP loan data | US Small Business Administration | Payroll scale at the time of application |
| Form 5500 | US Department of Labor | Employee headcount for plan filers |
| State business registries | Individual US states | Registry-verified formation date |
| Companies House | UK Government | Incorporation dates for UK coverage |
| OpenStreetMap | OpenStreetMap contributors | Establishment density, used to measure local fragmentation |
Coverage today is 137,849 US companies and 35,920 UK companies across seven industries: HVAC and plumbing, dental, niche manufacturing, landscaping, auto repair, funeral homes, and veterinary. 66,307 SBA loans have a computable maturity year, and 7,892 of those come due between 2026 and 2028. Counts were last regenerated on 2 July 2026.
Scouly does not estimate revenue or EBITDA. Public records cannot support that number honestly, and a made-up one is worse than none. What the SBA file gives you is a loan a lender actually underwrote, which is a documented floor on the size of deal the business can carry, and that is how the figures on this site should be read.
Scouly does not contact owners. It drafts outreach and you send it, from your own address, under your own name.
The target score is deterministic. It runs from 0 to 100, comes from three weighted signals, and is itemised on every profile with a link to the record behind each component. No model writes it. AI is used only to draft the screening brief, and the brief never invents a number the records do not contain.
The loan term is missing from a meaningful share of SBA records, so every maturity count here undercounts. Maturity is derived from approval date plus disclosed term, which means it ignores refinancing, early payoff and default: a loan listed as maturing in 2027 may already be settled. SBA borrowers are not a random sample of US small businesses, so the series describes SBA-financed ownership specifically rather than the whole market. UK companies carry no SBA or payroll signal at all; their scores rest on Companies House registry longevity and fragmentation, and their profiles say so.
A high score is a reason to look. It is not a reason to buy, and it is not diligence.
The SBA maturity wall is published under CC0 with no signup and no attribution requirement: the national series, all 51 states, seven industries and the 40 largest metros. Aggregate SBA totals exist elsewhere. This particular cut, by industry and metro and maturity year, is not published anywhere else that I have found.
Journalists, students and researchers are welcome to use it. If you want a regional cut that is not published, email me and I will make one.
Search funds have run on the same sourcing model for forty years. You raise a bit of capital, you spend eighteen to twenty-four months building a list by hand, you cold call, and the quality of your deal flow comes down to how many hours you can put into a spreadsheet and how good your intern is. Everyone in the industry knows the good deals are proprietary. Almost nobody can systematically find them, so in practice most searchers end up in a broker's inbox competing with everyone else who ended up there.
The reason is not that the information is hidden. It is that it was never assembled. The federal government has published every SBA 7(a) and 504 approval, with terms, since 1990. Fifty states publish formation dates. The Department of Labor publishes headcount. All of it is free, all of it is downloadable, and none of it was ever joined together and pointed at the question a buyer actually has, which is not "what is for sale" but "whose loan comes due in eighteen months."
That join is the whole thing. Once you compute a maturity year for 66,307 loans, an eighteen-month search stops being a list-building exercise and becomes a timing exercise. You are no longer hoping to find a seller. You are looking at a calendar of owners who will each face a refinance-or-sell decision on a known date, and choosing which ones to write to first.
I think that flips who gets to run a search. The advantage today goes to whoever can afford the most research hours. If the sourcing layer is public data and costs $35 a month, the advantage goes to whoever writes the best letter and shows up first. That is a much better filter for who should own a business, and it opens the model to people who were never going to raise a traditional search fund in the first place.
I could be wrong about the size of it. I am not wrong that the data exists and that nobody was using it this way.
Scouly is built by Nishkal Dachepelly. The analysis on this site, the ingestion pipeline, the scoring and the writing are all mine. If a number here looks wrong, it probably is worth telling me about, and every figure links to the record it came from so you can check it without asking.
Email: nishkal.dachepelly@gmail.com. Code and datasets: github.com/Nishkal2010.
No. Scouly holds no listings, represents no sellers, takes no commission and is not licensed as a broker. It is a research tool that ranks companies by public signals. Every conversation with an owner happens directly between you and them, initiated by you.
Entirely from published records: the SBA's quarterly FOIA release of 7(a) and 504 loans, PPP loan data, Department of Labor Form 5500 filings, state business registries, the UK Companies House register, and OpenStreetMap. Nothing is scraped from private sources and nothing is bought from a data broker.
The Explorer tier is free and includes ten full company profiles with the source records behind each score, with no card required. Operator is $35 per month for unlimited unlocks, unlimited screening briefs and pipeline tracking.
You can check it, which is better. The score is deterministic, built from three weighted public signals, and itemised on every profile with a link to the underlying record for each component. If you disagree with a weighting you can change it in your thesis and the ranking updates.
Yes. It is released under CC0, so there is no attribution requirement and no signup. A link back is appreciated but not required. The methodology and its limits are documented in full so you can decide whether it fits your question.