Understand what your infrastructure will cost — before you deploy it.

Get honest cost estimates from your Terraform configuration, with assumptions and uncertainty clearly shown. Explore scenarios, share with your team, and make informed decisions before infrastructure is deployed.

See how it works Try it with Terraform

The cost conversation happens too late

You're designing new infrastructure. You're choosing regions, instance sizes, and services. You're making decisions that will affect your monthly cloud bill.

But you don't know what those decisions will cost until after you deploy.

So you guess. You build spreadsheets. You hope. And sometimes, you're surprised.

When the bill arrives, it's too late to change course. The infrastructure is running. The team has committed. The conversation becomes reactive: "Why is this so expensive?" "Can we reduce this?" "What if we had chosen differently?"

These conversations are harder when they happen after deployment. They're harder when you're explaining surprises instead of making informed choices.

Cloud cost shouldn't be a surprise you discover after shipping.

A different approach: cost clarity during design

Before

  • Cost is unclear until deployment
  • Decisions made with incomplete information
  • Conversations happen reactively, after infrastructure is running
  • Assumptions are hidden or forgotten
  • Costs discovered when it's too late to change course

After

  • Cost is visible during design
  • Decisions made with cost implications in mind
  • Conversations happen proactively, before infrastructure is deployed
  • Assumptions are explicit and shown alongside every estimate
  • Costs understood when you can still change course

This isn't about optimization or cost reduction. It's about understanding and conversation. It's about making informed decisions instead of hoping for the best.

How it works

1

Connect your Terraform

Point us to your Terraform files. We read your infrastructure configuration—the resources you're planning to deploy, the regions you've chosen, the instance types you've specified.

2

See an estimated monthly cost

We use official cloud provider pricing APIs to calculate what your infrastructure will cost. The estimate shows a total monthly cost, broken down by service and resource.

3

Understand what drives that cost

See which services drive the most cost. Understand the assumptions behind each estimate—instance counts, usage patterns, pricing assumptions. Every cost item shows its confidence level: high, medium, or low.

4

Explore scenarios safely

What if you deploy to a different region? What if you change instance sizes? Compare scenarios side-by-side. See the cost difference. Make decisions with full information.

5

Share and discuss

Export estimates as CSV or PDF. Share read-only links with your team. Have cost conversations before deployment, not after.

Built for understanding, not optimization

Pre-bill timing

We show costs before deployment, when decisions can still be changed. This isn't about tracking spending or reducing existing costs. It's about understanding costs during design.

Explicit assumptions

Every estimate shows its assumptions. Instance counts, usage patterns, pricing assumptions—they're all visible. You see confidence levels. You know what's certain and what's not. No false precision.

Scenarios without pressure

Compare design alternatives side-by-side. See cost differences. Explore "what if" scenarios. There's no pressure to optimize or reduce costs. Just understanding.

Advisory insights, not commands

AI-generated insights help you understand cost drivers and patterns. They're advisory, not prescriptive. They're grounded in your actual infrastructure, not generic advice.

What this is not

  • A cloud provider bill — These are estimates based on assumptions, not actual usage
  • A cost optimization engine — We don't recommend changes or calculate savings
  • A finance dashboard — We don't track spending or enforce budgets
  • Real-time usage tracking — We estimate from configuration, not monitor actual resources

Being clear about what we're not protects trust and sets correct expectations.

For infrastructure teams who need cost clarity during design

This is for infrastructure engineers, platform teams, and architects who are:

  • Designing new infrastructure from Terraform
  • Evaluating architecture changes and their cost implications
  • Preparing cost estimates for stakeholders
  • Comparing design alternatives before committing

When to use it

  • Planning a new service or environment
  • Considering region changes or multi-region deployments
  • Evaluating scaling decisions (instance sizes, autoscaling)
  • Reviewing architecture changes with cost implications
  • Preparing budget estimates for new projects

What you need

  • Terraform configuration files (or access to a GitHub repository)
  • A few minutes to connect and review estimates
Try it with your Terraform

How this fits with other tools

This product fills a gap in the timeline: the period between designing infrastructure and tracking actual costs. It's not about replacing existing tools. It's about understanding costs during design, so you can make informed decisions before deployment.

Tool
When It's Used
What It Answers
What It Doesn't Answer
Cloud Provider Billing Tools
AWS Cost Explorer, Azure Cost Management
After deployment
"What did this cost?"
"Why did costs spike?"
"How can we optimize?"
"What will this cost?"
"What are the cost implications of this design?"
Engineering Cost Estimation Tools
Infracost
During code review
"Is this too expensive?"
"Does this violate our cost policy?"
"What are the cost trade-offs?"
"How do scenarios compare?"
Spreadsheets / Manual
Google Sheets, Excel
During planning
"What's our budget estimate?"
"What if we change X?"
"What are current prices?"
"What assumptions are hidden?"
This Product
Pre-bill cloud cost clarity
Before deployment, during design
"What will this cost?"
"What assumptions drive this?"
"How do scenarios compare?"
"What did this cost?"
"How can we optimize?"
"Is this too expensive?"

They're not competitors. They're complementary tools for different phases and purposes.