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Executive Summary

SaaS companies spending more than $50K annually on cloud infrastructure struggle to understand where their money goes, especially when running multi-tenant Kubernetes clusters where costs are shared across customers, features, and teams. Engineering teams can see the AWS bill but cannot easily attribute a spike to a specific customer's workload or a newly deployed microservice, while CFOs need non-technical explanations for why cloud spend jumped 40% quarter-over-quarter. The status quo involves brittle spreadsheets, AWS Cost Explorer tags that break when infrastructure changes, and manual Slack conversations between engineering and finance that waste 5-10 hours per month at companies spending $100K+ yearly on cloud. The MVP would be a read-only connector to AWS, GCP, or Azure that ingests billing data and Kubernetes metrics, then surfaces a dashboard showing cost per customer, per environment, and per service with week-over-week trends. You would start with just AWS and Kubernetes since 60%+ of venture-backed SaaS companies use this stack, focusing on companies with 10-100 engineers where the VP Engineering or Head of Infrastructure feels pain but lacks time to build internal tooling. Pricing could be $500-2,000 per month based on cloud spend tiers ($50K-200K annual spend, $200K-500K, $500K+), targeting $25K-50K ACV from companies that view this as cheaper than hiring a dedicated FinOps engineer at $150K+ salary. This market is compelling now because the 2022-2023 funding pullback forced every SaaS company to scrutinize cloud costs, moving FinOps from a nice-to-have at unicorns to a must-have at Series A companies. The $12B market size assumes 400K global SaaS companies with meaningful cloud spend and tools capturing 2-5% of infrastructure budgets as software fees, though realistically you would target the 50K venture-backed companies spending $50K+ annually where there is budget authority and willingness to pay. Gartner's prediction of 75% formal cloud cost management by 2025 suggests tailwinds, but you are racing against both enterprise players moving downmarket and infrastructure platforms like AWS building native cost allocation features. The first validation step would be conducting 20 problem interviews with VPs of Engineering at Series A-C SaaS companies to confirm they spend meaningful time on cost attribution and would pay $1K+ monthly for automated visibility. The likely GTM path is founder-led outreach to engineering leaders in your network, then content marketing around Kubernetes cost optimization to capture inbound, eventually building a sales team once you reach $1M ARR with 40-60 customers. The biggest risk is that AWS, GCP, and Azure improve their native cost allocation tools enough that companies accept "good enough" free solutions rather than paying for third-party software, or that the problem is acute only during fundraising quarters and companies churn after 3-6 months once they have identified and fixed their largest cost leaks.

Executive Summary

Why Now

Cloud spend has become the second or third largest operating expense for SaaS companies post-2022, as VCs shifted from growth-at-all-costs to unit economics scrutiny. AWS, GCP, and Azure pricing complexity has increased 15-20% annually with new instance types and services, making manual optimization unsustainable. Kubernetes adoption (now 60%+ of SaaS workloads per CNCF 2023) creates dynamic resource allocation that traditional cost tools struggle to map to business logic. Inflation and slower growth rates mean CFOs now review cloud bills monthly instead of annually, creating board-level urgency that did not exist pre-2021.

Pain Points

Engineering teams spend 5-10 hours per month investigating cloud cost spikes that do not correlate with user growth, pulling time away from feature development

SaaS companies overprovision compute and storage resources by 30-50% because rightsizing requires deep AWS/GCP expertise and fear of performance degradation

Finance and engineering teams lack shared visibility into which services, features, or customers drive cloud costs, causing friction during budget reviews

Cloud cost optimization for SaaS infrastructure

Executive Summary

Cloud cost optimization for SaaS infrastructure

Executive Summary

Executive Summary

Why Now

Pain Points

MVP Preview

Market Validation

Market Opportunity

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Validation Questions

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