Our Story · Made in Texas
The screen we wish we'd had.
We’re a small team in Texas made up of people who have searched for, bought, sold, and advised on small businesses. We kept seeing the same pattern: you find a deal that looks solid, start building a model, ask the broker for more data… and then you either spend $15,000+ and weeks on a full QoE (often put together by a junior person) or try to make do with your CPA. Neither option gives you a clear, quick read on whether the earnings are real and what to ask next.
We’ve been through it. Full-scope QoEs were built for bigger deals and bigger budgets. On the smaller ones we care about, you need something faster and more useful before you commit real time or money.
We've lived this experience.
There aren't effective, fast, affordable ways to pressure-test the numbers before writing an LOI or before you burn another weekend. Full-scope QoEs were built for larger deals and larger budgets. The lighter alternatives were either too shallow or too slow to actually protect time and capital. Small deals need to move quickly without skipping diligence.
We built the tool we kept wishing existed.
LiteQoE is a focused financial screen designed for buyers with tight budgets and timelines. You upload what you already have: the CIM, tax returns, P&Ls, balance sheets, whatever the broker sent. We help you compile the right additional documents for diligence. We trace the numbers, pressure-test the add-backs, grade the health of the business, and give you a clear next-steps list, usually within hours, not weeks. It costs $199.
- Catch it early
- Spot the deals that don't hold up before you spend real time or money.
- Ask the right things
- Get a suggested list of what to request on the deals that do.
- Escalate wisely
- Save the full QoE for the deals that actually deserve it.
The goal was never to replace a full Quality of Earnings when one is warranted. The goal was to make the first serious look so inexpensive and so useful that you can run it on every live deal.
How we did it
AI is helpful, but when the numbers can affect whether someone moves forward on a deal, you can't just dump a pile of tax returns, P&Ls, and bank statements into a model and hope it comes back clean.
Unfortunately, that approach is common, and it's risky. A general model can sound confident while getting details wrong, produce different results if you run it twice, and leave you with almost no clear trail back to the original documents. When you're trying to screen a deal, that creates more problems than it solves.
We didn't want that. So we spent the time to build our own system, one designed specifically for this kind of diligence work. It's not a general chatbot with a financial prompt. It's a purpose-built process that treats reading and organizing the documents separately from calculating the results.
- Read and organize
- Each document is read and sorted on its own, separate from any math.
- Calculate in code
- The math is handled in a controlled, repeatable way. Same file, same answer.
- Check and cite
- Key figures are checked against the underlying data and tied back to the source documents.
We're proud of how it turned out and we're improving every day. It produces a screening report that's faster and more accessible than a traditional full Quality of Earnings, while still giving a clear, checkable view of the earnings and the main risks. The whole thing is built so the numbers can be examined and confirmed rather than just accepted.
On smaller deals, the real value of a screen is whether a buyer can actually trust it.
We went the longer route because of that. It's the standard we built to, and it's why the report feels different from most of what's out there.
LiteQoE vs. dropping your files into a chatbot
| General AI chatbot | LiteQoE | |
|---|---|---|
| The math | Done by the model, which can add wrong and still sound sure | Done in code. Every total is recomputed and must add up |
| Run it twice | Can give different numbers each time | Same file, same numbers |
| Add-backs | Often accepted as the seller listed them | Each one graded Supported, Partially Supported, Rejected, or Insufficient Evidence |
| Proof | Little or no trail back to your files | Key items cite the document and page they came from |
| Checking figures | Rarely checked against the source | Material figures re-checked against the documents; misses are listed |
| Bank statements | Read as text, if at all | Deposits matched month by month to booked revenue; gaps flagged |
| Missing documents | Fills gaps with guesses | Gaps are named and the report is marked incomplete |
| Wrong files | Uses whatever you upload | Each file is checked and labeled; wrong ones are set aside |
| Verdict and grades | Whatever the model decides to say | Health grades set in code from the facts; the verdict can only be lowered |
| Next steps | Generic diligence checklist | Up to ten steps tied to this deal's flags, ranked by importance |
| The output | A chat reply you have to organize yourself | A consistent report and PDF, with kill sheet, schedules, and owner questions |
| Your data | May sit in a general chat history | Kept private to your account, with encrypted uploads |
LiteQoE is a screening tool, not an audit, valuation, or lender-ready Quality of Earnings.
We built it because we needed it.
Now it's the tool we wish every searcher had in their bag.
— The LiteQoE team
Know before you buy.