You don't have a visibility problem. You have a root-cause problem.

Visibility wasn't the problem. Root cause was.

Every customer started with mature cost reporting. The breakthrough wasn't more data, it was the layer that explains why costs moved.

Nubank

Homegrown cost transparency platform with full chargeback. Cost Champions in 45+ business units. Could see spend rise, but rarely the reasons.

Net Health

FinOps tools for budgeting and forecasting at the subscription level. Couldn't identify what was wasted, over-provisioned, or misconfigured.

Fanatics Commerce

Already reached the 'Run' phase of FinOps maturity. Reporting was embedded. Costs kept rising anyway.

The money hides where no one is looking.

Items too small to flag individually. Too distributed to address centrally. Surfaced and addressed at scale, they add up.

• 150+detached EBS volumes, individually small, $20K a month collectivelyDolby
• 200+waste types triggering across Nubank's AWS, continuouslyNubank
• OrphansDisks and low-cost items scattered across subscriptions, quietly compoundingNet Health

Generic flags get ignored. Context gets fixed.

Every opportunity arrives with the same four pieces.

Root cause

Why this happened, not just what.

Cost impact

Dollars, not flags.

Suggested fix

With remediation scripts where they exist.

Associated risk

So engineers validate before changing.

Days, not quarters.

When the long tail is surfaced and routed, the math moves fast.

• 10 daysto ROI: recovering the full annual cost of PointFive's contract during the POCNubank
• $300K+in AWS savings within months across S3, EBS, EC2, EKS and RDSDolby
• 1% to 3%Net Health hit its Azure savings target, then tripled the goalNet Health

Measure in recommendations, not dollars.

Tie KPIs to dollars saved and engineers fight over the biggest, easiest fixes. The long tail goes untouched. Net Health measures the number of PointFive recommendations completed, including thoughtful dismissals with documented reasoning. Disciplined evaluation, not blind cost-cutting. Outcome: engineers hit quarterly targets a month ahead of schedule.

• Engineers tackle the long tail, not just easy wins

• Dismissals with reasoning count as completion

• Milestone-based: October to November to December targets

• Performance reviews tied to completion, not appearances

Automation changes the math.

Nubank, storage and databases. A custom pipeline integrates PointFive's GraphQL API into Nubank's internal automation. Dozens of DynamoDB optimizations applied per day with zero engineer involvement.

• 3,000+Autonomous remediations
• 2.5xSavings potential vs. manual remediation
• ZeroEngineer involvement

AI workloads need a pipeline view.

AI workload investigation connects service costs to pipelines, model training, and infrastructure choices. Explore PwC's work on LLM training costs.

• 32BParameter LLM in training
• 8AWS regions mapped end to end
• 5NVIDIA GPU architectures optimized

• What got mapped

  • Data preparation and tokenization
  • GPU training and fine-tuning
  • SageMaker HyperPod clusters
  • FSx for Lustre storage tiers
  • S3 checkpoint distribution across regions

• What was identified: $9K to $15K a month

  11% to 19% cost reduction across snapshot archival, S3 Intelligent-Tiering, data transfer, and instance scheduling.

The savings are the headline. The operating model is the win.

Nubank

Cloud efficiency stopped being a centralized FinOps mandate. It became part of engineering's regular work: clear ownership, trusted data, remediation through existing Jira and ServiceNow workflows.

Blackhawk Network

Optimization shifted from a reporting exercise to an engineering discipline. Teams engage with opportunities as part of their regular work.

Net Health

A savings program became a repeatable model: cloud efficiency improves when KPIs are clear and the work fits existing engineering workflows.