I built a tool to automate estimate creation

Hacker News

Hey HN, I’m a software engineer based in Switzerland, working a regular 9–5 and doing some freelancing on the side. Balancing both can get pretty stressful, so I looked for ways to save time and focus on the parts that actually bring value. That’s why I built my latest tool: Quotka. Quotka helps freelancers and small teams create professional quotes quickly and accurately. You just input the client info and a short project description, and the AI generates a detailed quote with tasks and estimated time. You can customize it, export it as a PDF, or send it directly to the client via email. Now, instead of spending hours tweaking a Word template, I can focus on doing actual work in my free time. I’d love to get your feedback to help improve Quotka. What do you think? Is there anything I’m missing? Happy to answer your questions. :)

Visit product View on Hacker NewsApr 29, 2025

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

86%86% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: email, tasks · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

39%39% 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

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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.

Correct prediction on native model

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