Props AI – A Free Tool for Cost-per-User Visibility for Open AI

Hacker News

Hey HN, I am excited to launch Props AI. A Free tool that provides cost-per-user insights and visibility for you apps built on Open AI's API. For those of us building GenAI apps, There is a disparity between how we pay for LLMs (Tokens) and how we charge for them (Per month). Its hard to know your COGS or Unit Level Economics with a single bill at the end of each month from Open AI, so I build a free lightweight proxy and data pipeline that to utilise the "user" field in the competition requests and track the breakdown in usage per customer. In the future I hope to add integrations to stripe to enable frictionless Usage-based billing. I would love your feedback <3

Visit product View on Hacker NewsFeb 5, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, stripe · Missing: mac, agents, macos

95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, pipe · Missing: https docs, just released, exist

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% 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

20%20% 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

19%19% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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