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I built an API to generate PDF invoices from JSON

Hacker News

I built an API to generate PDF invoices from JSON

Hi HN, I'm Daniel. I built a simple and straightforward API: you POST a JSON payload with your invoice data, and it returns a secure, presigned URL to a generated PDF. The goal is to make invoicing a single, reliable API call so you can get back to your main product. I also used this as a personal challenge to move away from my old LAMP stack background and build something new with Python/FastAPI, Next.js, and a serverless architecture on GCP and AWS. For the HN community, I've set up a promo code: HEYHN100 If you sign up, you can redeem it in your dashboard for 100 free credits (on top of the 10 you get by default). The credits don't expire. I'm here to answer any questions and would genuinely appreciate any feedback or technical critiques you have. Thanks for checking it out.

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1points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% 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: new, single, code · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, 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
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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
16%16% 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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Extract invoices & PDFs into JSON with one API call

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