Both times I had asked the best AI in the world. Both times I stood at the counter and found out, in front of people, that it was wrong.
I am not a casual user. I check things. And I still have hundreds of sessions where a confident, well-written, completely wrong answer sent me the wrong way.
Nobody is embarrassed because AI was uncertain. They are embarrassed because it was certain.
1 / 10
The problem
Ask 3 AIs the same question and they disagree.
You cannot tell which one is right. They all sound equally sure. So you either guess, or you go and find out the hard way.
The expensive part is not the wrong answer. It is that it arrives sounding exactly like the right one.
2 / 10
What we built
We only ask the AIs that are good at your topic.
No AI is best at everything, and the leader changes constantly. We keep score of who is good at what, send your question to the right few, then run our own math across their answers to settle the argument: one answer, with a certainty number attached.
Live today, in a real product, with paying tiers already priced. Not a prototype.
3 / 10
Why we ask several at once
One question, three answers, four things we keep.
Asking several AIs at once is not just an accuracy trick. Three of the four things it produces are assets nobody can buy, and we get them as a byproduct of running the product.
That last one is not theoretical. In one month we watched the model we had benchmarked against get retired 6 days later, a second one discontinued the same week, and a third cut its price by about 80% overnight. Model line-ups and prices change constantly. Our customers never have to think about it, because we are already re-scoring who is good at what.
Three of these four cost our competitors money. They cost us nothing, because the product produces them while it runs.
4 / 10
The proof, measured July 2026
Within 2 points of Claude Opus 5. 1/40th of the cost.
97% Accuracy
Claude Opus 5 got it right $338 per 100,000 answers
95% Accuracy
We got it right $8.50 per 100,000 answers
2,089
AI calls, every one billed and measured at that day's live prices. Nothing estimated.
Tested on questions the system had never seen, with none of our tuning switched on. We measured ourselves on reasoning problems, which is where today's AI is already strongest, so it is the hardest possible place for us to win. On the ground where AI is weakest, anything that moved after its training cut-off, we expect the gap to run the other way and embarrass the smartest models in the world. That test is next, and we will publish it either way. Full workings on request.
That 2-point gap, against a 40× cost gap, is the entire business.
5 / 10
Why it compounds
When the AIs disagree, real people settle it and get paid.
Every settled disagreement becomes a corrected, human-attested answer that we own. That library is the thing AI labs are already buying, in volume, from other people.
$1B/yr
what one supplier, Surge, sells this data for
$614M
what another, Mercor, did in 6 months
They buy corrections by the hour. Ours are a byproduct of people enjoying themselves, so our cost of producing the same asset is close to zero. None of this revenue is in our forecast.
Everyone else pays for this data. We are paid to generate it, then own it.
6 / 10
The business
We can afford to give it away.
Because the answer costs us a fraction of a cent, the free tier is not a loss leader we have to defend. It is simply cheap. Nobody paying full price for a frontier model can match that and stay solvent.
~80-92%
gross margin, what we keep of every dollar after the AI & card fees
6
plans, priced: Free · $5/mo · $9/mo · $19/mo · Company · $??/mo Paid plans open at launch
$0
up-front cost for the human experts. They are paid from what their work earns, not a wage.
The labor line that normally sinks a margin like this is a revenue share here, not a payroll.
7 / 10
Why this is low risk for you
Built, funded, filed. The only missing piece is growth.
You are not being asked to bet on whether it works. It works. You are being asked whether you can grow it.
8 / 10
The ask
A growth partner, paid before we are.
Take 100% of quick ramp-up revenues until you have recouped 3× your time and costs, plus equity, with ongoing profit sharing, or propose a term sheet that works better for your situation & resources. We are open to branding and business-model changes, or pointing the core engines at something else entirely.
100%
of early revenue to you, until you are 3× whole on time and cost
+ equity
and ongoing profit sharing after that
Bob Haya, founder, retired venture capitalist.
Everything is built. Tell us what you would change, and take the upside first.
9 / 10
That was the short version
The full deck, with the details, is next.
Another 15 pages: which AI is best at which subject, the 9 ways the product grows itself, & the money, line by line.
ReallySolved · the short version