Subscription Billing and Payments for AI

Hacker News

Hey HN, We built Stykite, a billing and payments platform designed specifically for AI companies. It was a manifestation of a problem that I personally faced 6 years ago and even today, setting it up takes weeks/months and various API integration. Even when 99% on SaaS onboarding and billing experience is largely the same (fixed price, seat price or even usage-based). So we asked ourselves a question, can there be something that can let SaaS/AI businesses go live in 10 mins. We're not there yet, but hopefully on the path. Note: - Our documentaion is half broken. (WIP) - We did a UX revamp this month, but still needs some work I guess. Would LOVE any feedback and questions specifically around our "product architecture" which is different from legacy systems out there.

Visit product View on Hacker NewsFeb 24, 2025

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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

83%83% 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 · Missing: mac, agents, macos

64%64% 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

48%48% 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, month · Missing: mobile apps, ios, entrepreneurs

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Acquire.comPre-revenue stage for this audience · Strong signals: saas, subscription · Missing: arr, mrr, revenue

26%26% 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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