Spiraling costs with no visibility
A large healthcare enterprise operating across multiple regions had watched its cloud bill climb steeply for three consecutive years. Despite significant investment in AWS and Azure infrastructure to support patient data platforms, analytics workloads, and digital health services, the engineering team had no clear picture of where the money was actually going.
Kubernetes clusters - the backbone of their microservices architecture - were running at just 30-40% utilization, yet were being billed at 100% capacity. Idle namespaces from deprecated services lingered unnoticed, accumulating costs month after month. Reserved instance coverage was poorly managed, leaving expensive on-demand spend in place where it could have been optimized away.
The team lacked dedicated FinOps expertise. Engineers were focused on reliability and feature delivery, not cost governance. Without visibility, accountability, or automation, cloud waste had become a structural problem - not an operational one.
AI-FinOps from day one - no new hires
Nudgebee's AI-FinOps Assistant connected to their AWS and Azure environments within hours - no dedicated FinOps hire required. It immediately began building a unified cost topology across 4,500+ instances, integrating directly with their CI/CD pipeline to map every dollar of spend to a specific team, service, and environment.
Beyond the automation, Nudgebee surfaced cost attribution data directly to engineering teams - making every engineer cost-aware without turning them into FinOps specialists. Cost culture became embedded in the daily workflow, not bolted on as an afterthought.
$1.2M saved. Zero headcount added.
The $1.2M in annual savings freed up budget that was redirected into digital health initiatives - accelerating the development of patient-facing applications and data analytics capabilities. The engineering team now operates with full cost visibility, automated governance, and the confidence that their cloud environment is continuously optimized.