DataReconIQ

Hey Product Hunt 👋 I built DataReconIQ while shipping a new app every week and repeatedly running into the same problem: reconciling two datasets safely is still way harder than it should be. Most tools either assume perfect schemas or silently force matches. In real operational and financial data, that’s dangerous. You don’t want automation guessing—you want it to surface uncertainty and let humans decide. So I built DataReconIQ around a human-in-the-loop approach. AI suggests matches, explains confidence, and flags anything unclear instead of forcing it. No brittle scripts, no Excel gymnastics, and no black-box decisions. I’m curious how others handle reconciliation today. Where does it usually break down for you? Thanks for checking it out 🙏