Aequitas AI

The AI that abstains instead of bluffing

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Artificial Intelligence

Hi Product Hunt. I am Ruthvik, and I built Aequitas on my own. The inspiration was an uncomfortable observation: every AI system today is a language model checking a language model. You can stack as many critics and review passes as you like, but if every part of the stack is a language model, then nothing in it is incapable of hallucinating agreement. There is no point where something the AI cannot fake checks the reasoning. The other half of the problem is that every AI product always answers. Always. Even when it is far out of its depth. That is not something you fix with a better prompt. It is structural. Now think about who needs AI the most. A lawyer. A risk team. A regulator. A board. These people do not need an answer. They need an answer they can defend to somebody who is allowed to say no. For them, a fluent and confident wrong answer is worse than no answer at all, because they will act on it and then have to explain themselves. So Aequitas is built around the opposite instinct. It takes a hard question, debates it from multiple perspectives, then puts the reasoning through a formal proof engine, a mathematical solver rather than another AI grading the first. An independent adversarial audit tries to break the result. It also maps the cases where two goals in a decision genuinely cannot both hold, instead of papering over a real trade off with a fake consensus. Then a final deterministic gate, with no AI in it at all, decides whether the verdict earned the right to be called certified. When the reasoning cannot be shown to be grounded, Aequitas says so rather than quietly stamping it certified. Here is how the approach evolved, and it is the part I did not see coming. I set out to build the most rigorous answer machine I could. Then I found something in my own system that changed the project. A key internal model could quietly fall back to a weaker version, and the final report would still say "certified." Nothing was structurally stopping it. The output looked identical either way. That reframed everything. A system that cannot check its own machinery has no business certifying anything, because certifying a degraded run is a lie you do not even know you are telling. So I built a gate whose entire job is to block my own system. Aequitas now checks the health of every load bearing component on each run, and refuses to certify if any of them ran weakened. The same instinct spread. My reliability score used to look like a calibrated probability when it was really just a formula output, so I made it label itself uncalibrated instead of faking precision I had not earned. My fast screening tier is now code blocked from ever claiming certification, so a shallow pass can never dress itself up as a deep one. Where it actually stands today, precisely, because that precision is the product. Live on every certified analysis: the multi perspective deliberation, formal verification of every claim, the independent adversarial audit, the grounding check with its decision recorded and disclosed on every run, the machinery health attestation (that one already blocks certification outright), and honest tiers. Rolling out: turning the grounding gate's disclosure into a hard automatic block, which is a single switch I flip once the confidence calibration is fitted on real outcomes, plus independently re verifiable proof certificates and calibrated confidence scores. I would rather tell you exactly which is which than let you assume. One thing I want to be straight about. Formally verifying AI output is not new, and at least one major cloud provider does it well. What I have not found anywhere is a system that makes the certify or abstain call its own verdict on an open ended question, and that refuses to certify when its own machinery is degraded. My ask: give it a genuinely hard question from your own field and watch what it does. Honestly, I would love it if you caught it abstaining. That is the product working, not failing. Happy to take any question, especially the skeptical ones.