The trust engine, everywhere
UpTrust ranks people by who others have good reason to trust, not by who is loudest. That same math does not only work on posts. We ran it over open academic papers, over open-source code, and over Wikipedia to see who each field actually trusts. Each one is its own live site. Go look.
Three live graphs
Each graph uses public data only. Nobody buys their way up. Trust is earned from what the record shows.
The same scoring run over a large set of public scientific papers and their citations.
See who the research community actually leans on in a field, from the citations up.
Open the graphThe same scoring run over open-source projects, built from who stars whose work.
See who keeps the open-source world running, not just who has the most stars.
Open the graphThe same scoring run over Wikipedia edits, built from who the encyclopedia keeps and reverts.
See which editors the encyclopedia leans on to stay accurate.
Open the graphWhy this matters
Most platforms keep their ranking hidden and locked to one place. Ours is a method, and a method moves. Point it at any record of who relies on whom and it answers the same question: who do the people who know best actually trust? We run it on public data here so you can check the work. Point it at your own data and it answers that for your world.
That is the whole reason these three sites exist. They run on data we did not make and cannot bend. The same method holds up on papers, code, and an encyclopedia. Three unrelated worlds, one result.
For agents and developers
We are building a server that lets an AI agent ask the same trust questions you can. Who is trusted on this topic. Who bridges two sides that usually do not agree. An agent can ask on your behalf, with your permission, and act on what it learns. This part is early, and we are opening it up step by step.
Sign up and the trust math works for your conversations the way it works for science, code, and Wikipedia.
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