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Cut 50%+ on the Cloud (AWS / GCP / Azure)

Hacker News

Cut 50%+ on the Cloud (AWS / GCP / Azure)

Hi HN community! My name is Kane and I'm on the product team at www.usage.ai , a cloud cost optimization company. After honing our product on AWS, I'm excited to announce our availability for customers on GCP and Azure! At a high level, Usage insures committed use-discounts (CUDs) to reduce commitment risk and enable higher savings for companies on the cloud. With traditional CUDs, you commit to a certain level of usage over a specified period in exchange for discounted rates from the cloud provider. However, if your actual usage falls short of the committed amount, you may not fully realize the savings and may even end up paying more than you would have on an on-demand basis. Insured CUDs takes the concept of committed-use discounts a step further by adding an insurance component to mitigate your commitment risk. With our Insured CUDs, your commitments to public cloud providers are fully insured by Usage and backed by a cash-back guarantee. If your actual usage falls below the committed amount, the insurance steps in to cover the difference, ensuring that the you receive the full benefit of the CUD without the risk of overpaying. Pricing: We only charge a percentage of savings. In exchange for a portion of the savings, we insure the full value of the commitment. Are you currently trying to lower your public cloud costs? Visit our website our reach me directly (kane@usage.ai) to ask about the special we're running for the HN community!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% 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.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
39%39% 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
22%22% 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

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