Nymnio – Making Crypto Accounting Easier

Hacker News

Hey HN Community, I've been working on a project called Nymnio ( https://nymnio.com ) that simplifies crypto accounting. It's a tool that takes in an Ethereum address and churns monthly reports on your USDT, USDC, and DAI transactions. The reports include revenue, expenses, profits, and balance. The idea came from my frustrations with keeping track of transactions. Traditional accounting methods often need to catch up when dealing with crypto transactions, especially when using different addresses. Nymnio is a proof of concept at this stage. I've built it using create-t3-app, a CLI tool with several pre-configured libraries, and Redis for caching. I would love your feedback and suggestions. Also, if you have any ideas for additional features or improvements, I would love to hear them.

Visit product View on Hacker NewsMay 14, 2023

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, monthly · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

36%36% 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 · Strong signals: revenue, profit · Missing: arr, mrr, saas

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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