Harbr Data’s finance-first approach to cloud efficiency

The challenge

Harbr Data’s enterprise data marketplace platform runs across customer-owned environments and their own control plane. While most customer workloads sit inside client environments, Harbr Data’s development, testing, and orchestration layers create significant AWS usage.

Engineering was already managing performance initiatives and ongoing product releases, leaving little bandwidth to plan or forecast cloud commitments. Finance lacked a clear view of which workloads drove spend or how that spend would evolve over time. With cloud costs becoming one of the company’s largest operating expenses, Harbr Data wanted a way to strengthen its partnership with AWS, capture more value from its usage, and give finance the confidence to forecast accurately - all without slowing engineering velocity.

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Business impact

Cloud Capital helped Harbr Data move to proactive financial control. By connecting directly to Harbr Data’s billing data, Cloud Capital identified where commitments could safely increase and applied guaranteed savings across all eligible services without requiring any code changes or internal engineering effort.

The result was a 34.7% savings rate on new commitments and a 78.4% reduction in financial risk, with Cloud Capital taking on full liability for any unused commitments. Finance gained a forecasting model that projected spend based on both business growth and technical initiatives. Over time, Harbr Data is projected to save more than $100,000 annually while maintaining full alignment with AWS and complete confidence in its cloud governance model.

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Inside the model

Cloud Capital integrates directly with Harbr Data’s AWS Organization, mapping spend across production and non-production environments and isolating customer-specific workloads. This structured view became the foundation for a shared forecasting model that linked financial plans to engineering roadmaps. By combining Harbr Data’s business growth projections with planned technical initiatives, the model created a single forward-looking view of cloud economics that both teams could understand and act on.

Cloud Capital then increased Harbr Data’s commitment coverage to capture deeper savings while assuming all risk associated with new commitments. Harbr Data’s financial exposure dropped from 100% to just 21.6%, tied only to its remaining legacy agreements. All savings were realized without any engineering intervention or operational disruption. The collaboration strengthened Harbr Data’s AWS relationship by improving commitment utilization, enhancing cost predictability, and ensuring that financial and technical governance moved in lockstep.

Today, Harbr Data’s finance and engineering teams operate from one shared forecast that updates automatically as usage and business conditions change.

“Cloud Capital gives us a clear, reliable view of how our workloads translate into financial impact. It keeps our technical roadmap intact while giving finance the data it needs to plan with confidence.” — Ryan Cauldwell, Engineering Lead at Harbr Data

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