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Chemistry AI – A step-by-step chemistry solver for students

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Chemistry AI – A step-by-step chemistry solver for students

Hi HN, I’m an indie developer building Chemistry AI – a web-based chemistry solver for high-school and college students. Motivation: I saw many students searching for “chemistry AI” and mostly getting generic chatbots or math tools. I wanted something focused on chemistry that actually explains the steps, not just the final answer. What it does: - You can type a question or upload a photo of a worksheet. - The AI reads the problem and shows transparent, step-by-step reasoning. - It covers topics like equations, stoichiometry, acids/bases, equilibrium, thermodynamics, and basic organic mechanisms. - There are two modes: “Just Answer” for quick checks and “Thinking” for detailed solutions. Tech: It’s a browser-based app using modern JS/React on top of hosted LLM + vision models via APIs. I’d love feedback on: - Whether the explanations feel clear/useful for real homework. - What features you’d want as a student or tutor (e.g., practice mode, export to PDF, etc.). - Any concerns around misuse or ways to better encourage learning vs just copying answers. Link: https://chemistryai.chat/ Happy to answer any questions. Thanks for taking a look!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: answers, way · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, models, using · Missing: mac, agents, macos
42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
15%15% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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