ewpire - Full-cycle AI platform for founders and teams
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ewpire helps founders, teams, and companies test and build product ideas with more confidence. Instead of asking one AI, ewpire runs several leading AI models against your idea at once – each answers independently, then challenges the others – so you see where they agree and where they don't. From there, ewpire builds a working version of the product, and helps teams check how AI assistants describe their brand online, and fix it if wrong. One account, one credit balance, no code.
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I launched ewpire in April as a marketplace of nine AI agents. Nobody wanted nine agents. They wanted one answer they could trust, and I had built the opposite of that.
Three pivots later, one conviction was still standing. Ask a single model whether your idea is any good and it tells you yes – it is trained to be agreeable, and agreeableness is indistinguishable from insight when you are the one being agreed with. Ask several strong models independently, make them critique each other, and the disagreement is the useful part. That is the thing worth testing first.
ewpire is that idea taken all the way through:
Ideation – frontier models stress-test the idea on demand, saturation and competitors. You get one verdict, a confidence score, and a dissent map showing exactly where they split.
Validation – turn the idea that survived into a working MVP, with the same consensus reviewing the build. The code is yours to export and use.
Traffic – generate an AI-readable presence and measure how AI engines actually describe your project. We increase the probability of being cited correctly. Nobody can honestly promise more than that.
One account, one balance of credits, one folder of projects. The output of each step is the input to the next.
Two things I would genuinely like to be argued with about:
Does the dissent map change what you would build, or is it just a nicer-looking confidence score? And where does consensus fail – I am fairly sure there are question types where three models agreeing is worse than one model hedging, and I have not found them all yet.
Before publishing anything I ran our own Traffic product on ourselves. It reported that the index still quotes a price we retired in July, and that a single cached page was speaking for the whole company. I published that baseline this morning instead of fixing it quietly – the numbers and the method are in the write-up on our site.
First consensus report is free – 20 credits, no card.