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OpenAI Cost Monitoring

Hacker News

OpenAI Cost Monitoring

Hi HN, My name is Ben Schaechter and I’m Co-Founder and CEO of https://vantage.sh - a cloud cost visibility and optimization platform. We just added support for monitoring OpenAI costs and usage to Vantage and I wanted to share a demo we put together with HN as I thought people might find it interesting: https://www.youtube.com/watch?v=CzAOU1-uMrM In early April we started getting requests from customers to add OpenAI cost support specifically as it was a bit opaque as to what exactly was driving costs. The way this works is that it uses an undocumented API available from OpenAI - I asked ChatGPT how to get this info and this is what it recommended. The OpenAI team said this was fine to use but is subject to change in the future which is why this feature is in beta right now. This new integration uses an OpenAI API key to report on costs by organization, operation (i.e “Completion”), and model (i.e. “GPT-4”). It also allows you to forecast your OpenAI costs and set up billing alerts in Slack if costs begin to increase rapidly. I’d love to know what people think on this and if you have any feedback good or bad for us to improve this moving forward. You can register an account and connect OpenAI in a few seconds here: https://console.vantage.sh/signup

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, slack, new · Missing: mac, agents, macos
85%85% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
52%52% 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: way · Missing: mobile apps, ios, personal
49%49% 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
39%39% 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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