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ProsperOps

Autonomous cloud discount management with ML

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ProsperOps uses machine learning to continuously optimize cloud commitment coverage including Savings Plans and Reserved Instances, achieving Effective Savings Rates of 40% or more on AWS, GCP, and Azure. It provides autonomous discount management with a performance-based pricing model where ProsperOps shares a percentage of the savings generated, aligning costs with actual value delivered.

ProsperOps automates the complex task of managing cloud commitment purchases across AWS Savings Plans, Reserved Instances, and equivalent programs on GCP and Azure. The ML engine continuously analyzes workload patterns, forecasts future compute demand, and optimizes the portfolio of commitments to maintain maximum discount coverage without over-committing. This dynamic approach achieves significantly higher savings than static annual planning.

The platform handles the mechanics that make manual commitment management difficult: balancing flexibility against discount depth, managing expiring commitments, adjusting for workload changes, and navigating the different discount vehicles across multiple cloud providers. Teams get savings visibility dashboards showing Effective Savings Rate, waste metrics, and optimization recommendations with full transparency into every automated action.

ProsperOps operates on a performance-based pricing model where the company shares a percentage of the savings generated, ensuring alignment between vendor cost and customer value. This model means ProsperOps only earns when it saves customers money, making it a low-risk investment for organizations spending six to eight figures annually on cloud infrastructure.

Pricing

Performance-based (% of savings generated)

Platforms

AWS, GCP, Azure, Savings Plans, Reserved Instances

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