Designing the experience for multi-cloud cost management

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At a glance

The problem

As businesses scale, cloud costs inevitably rise, while fragmented billing data makes every increase difficult to explain and investigate.

What I did

I led the end-to-end product design, shaping the product from early customer problems through strategy, workflows, and delivery.

The outcome

One workspace where a cost change leads to its cause, owner, and next action without leaving the product.

15+

Enterprise contracts where UX was named a deciding factor

25+

Cloud and SaaS providers unified in one place

300+

Customer requests solved

Role

Founding Product Designer

I owned product design from customer insight to launch. With no dedicated PM, I worked directly with founders, engineers, customers, and marketing while managing two designers.

Ownership across the product lifecycle
ActivityDiscoverDefineDesignBuildLaunch
Customer researchOwnOwnNot involvedNot involvedNot involved
Product managementSharedSharedOwnOwnOwn
Interaction designNot involvedOwnOwnSharedNot involved
Design systemNot involvedNot involvedOwnOwnNot involved
PrototypingNot involvedNot involvedOwnOwnNot involved
Product documentationNot involvedOwnNot involvedOwnOwn
QA and releaseNot involvedNot involvedNot involvedOwnOwn
Marketing materialsNot involvedNot involvedNot involvedOwnOwn
Go to marketNot involvedNot involvedNot involvedNot involvedShared

Challenge

Scale design, learn Cloud domain, own product decisions, and maintain delivery speed.

Solution

Introduced lightweight processes, built domain expertise, and established clear ownership and delivery standards.

Before

Reactive delivery

  • No dedicated PM or established product process
  • Customer requests moved directly into delivery based on rough sketches.
  • Limited discovery and testing
  • Inconsistent design files and handoff

Lightweight changes

Structure without slowing down

  • Research and discovery
  • Grooming and focused brainstorming
  • Baseline requirements with space to explore
  • Clear design process

After

More intentional delivery

  • Clearer problems and requirements
  • More informed design decisions
  • Consistent files, reviews, and handoff
  • A shared quality bar for the team

Design Process

Turning customer evidence into product decisions

We turned customer research and product data into product principles and prototypes, then refined them with customers, founders, and engineers.

  1. 01

    Gather Data

    • Interviews and demos
    • Feature requests
    • Analytics and real-world cloud data
  2. 02

    Identify patterns

    • Persona needs
    • Recurring problems
    • Workflow gaps
  3. 03

    Prototype

    • End-to-end flows
    • Interaction concepts
    • Clickable prototypes
  4. 04

    Test and validate

    • Customer feedback
    • Team reviews
    • Live product behavior

In an early-stage startup, not every decision has time for a full validation cycle. Sometimes you need to use the strongest available signal, make the call, ship quickly, and learn from real usage.

Customer Problem

Infra cost complexity was difficult to understand and act on

FinOps teams could see their cloud spending, but struggled to understand why it changed, who owned it, and what action to take.

Fragmented cost data

Each provider and service reported costs differently, forcing teams to reconcile data across consoles and spreadsheets.

Limited root-cause support

Billing tools showed that costs changed but rarely explained why. Teams had to investigate services and resources manually.

Unclear cost ownership

Infrastructure rarely reflected business structures, making it difficult to assign spending to teams, products, or initiatives and track team budgets.

Unclear savings actions

Teams lacked clear guidance on where costs could be reduced and what actions were needed to realize those savings.

These problem areas were identified through 30+ customer demos, interviews and calls, market analysis, and FinOps Foundation research.

Hewlett Packard Enterprise, NVIDIA, ServiceTitan, digital.ai, Strava, Miro, CodeSignal and Level

Product direction

From cloud cost problems to a connected automation workflow

Focus on what matters most

By applying the 80/20 principle, we focused on the 20% of work that addressed 80% of customer needs.

Problem

Fragmented cost data

Solution

Unified provider integrations

Bring cost and resource data from every provider into one workspace.

A row of provider tiles: AWS, Google Cloud, Azure, Kubernetes, Anthropic, OpenAI, Spark, GitHub and MongoDB, trailing off into a more indicator.

Problem

Limited root-cause support

Solution

Progressive investigation

Move from accounts to individual resources. See costs, savings opportunities, and resource status in one place.

A trail from an AWS account through Prod and EC2 Service to one instance, whose read-out shows month-to-date billing, savings, CPU and GPU metrics, coverage, and delete and stop actions.

Problem

Unclear cost ownership

Solution

Rule-based cost allocation

Map shared infrastructure costs to teams, products, initiatives, and budgets without restructuring cloud environments.

One DB Instance at $2,473.11 splitting 30 percent to the ML team at $741.93 and 70 percent to the Backend team at $1,731.18.

Problem

Unclear savings actions

Solution

Accountable action

Connect optimization opportunities to owners, workflows, alerts, and automation.

A weekly schedule feeding $17,696.23 of underutilized resources into a delete action, then out to cloud providers, an approval check, and Slack, Teams and email notifications.

The Product

One workspace for the whole FinOps lifecycle

Some of the core features behind the unified FinOps experience.

Billing Explorer

Investigating a cost change in one workspace

A flexible surface for investigating cloud costs, understanding changes, identifying responsible resources, and uncovering savings opportunities.

The Billing Explorer working: a cost trend chart above a per-service breakdown, with totals, forecast and savings opportunities in the header.
Dimensions

Costs grouped the way the business is organized

A system for organizing cloud costs by teams, products, environments, and business units using custom rules.

Building a Platform Teams dimension from account and service filters, with existing dimensions listed by type and owner.
Opportunities

Recommendations that become trackable work

A connected workflow for identifying savings opportunities, evaluating their impact, and turning recommendations into trackable actions.

Savings opportunities being surfaced and worked through, from the counts in the header to the services behind them.
Automations

Cleanup that runs on a schedule

A flow for turning recurring cleanup into scheduled automations, routed to the people who approve them and the channels that report back.

An automation being built: a schedule, the resources it targets, the action it takes, and where the result is reported.

Closing

Organizing complexity, not removing it

Designing Cloudchipr taught me that simplifying enterprise software rarely means removing complexity. It means organizing that complexity into workflows people can understand, trust, and act on.

As a founding designer, my role extended beyond individual features. I helped shape the product, establish interaction patterns, build the design system, and improve how the team moved from an idea to a tested and released experience.

My most important lesson was learning how to create structure without becoming a bottleneck. In a fast-moving environment, design leadership means making thoughtful decisions quickly, learning new skills when the team needs them, and helping others deliver stronger work.

What's next?

Want to talk about this case study, or have any questions for me? I'd be glad to chat about it.

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