FuturLang – Natural language formal verification

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I built FuturLang, a formal verification system that preserves natural language structure while enabling machine verification. The goal is to make formal proofs more accessible without requiring specialized notation like Coq/Lean/Agda. Example proof structure: (1) It is assumed that: (√2 is rational) (2) This implies that: (∃ integers a, b)... (3) Therefore: (√2 is irrational) I’ve built the language spec, verification engine, and a database of 250+ proofs. But adoption has been minimal, which makes me question if this addresses a real need. Questions for HN: ∙ Is “natural language + formal verification” solving a real problem? ∙ What would need to be true for you to use this instead of Lean/Coq? ∙ Am I building a solution in search of a problem? Honest feedback welcome - trying to decide whether to keep building or move on. GitHub: https://github.com/wenitte/mathematical-intelligence

Visit product View on Hacker NewsJan 30, 2026

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nativeThis product was originally launched on this platform.

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35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

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BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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