All case studies
How Greybeam got clear EC2 spend visibility without leaving their workflow using Pump View
$7300+
Saved on AWS with zero manual effort
6%
AWS bill reduction on autopilot
4
Automated cost reports replacing manual checks
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Overview
"AWS Cost Explorer never gave us the quick, clear view of EC2 spend we needed. Pump View plugged right into our workflow without replacing anything, and now I can see exactly where our infrastructure dollars are going without digging through filters. For a small team, that kind of visibility on autopilot is a big deal."
Seth McCombs
Founding Infrastructure Engineer
Greybeam builds drop-in query engines that route Snowflake read workloads to more cost-efficient alternatives like DuckDB, saving their customers an average of 86% on Snowflake compute. The early-stage team of under ten runs its own infrastructure on AWS while expanding into write workloads and GCP support. As a company whose entire value proposition is cutting cloud costs for others, keeping their own AWS spend lean and visible is non-negotiable.
Industry
Data Infrastructure Software
Integrations
Location
San Francisco, CA
Pump services
Pump View
Use Case 1
Replacing AWS Cost Explorer with a Dashboard That Actually Works
The feature Seth relies on most is Pump View's spend tracking for EC2. Before Pump, getting a clear picture of compute costs meant logging into AWS Cost Explorer and working through filters and views that weren't built for quick answers. For a small team that needs at-a-glance visibility, not a 15-minute investigation every time someone asks "what are we spending on compute?", the native AWS tooling fell short.
With Pump View, Seth can see EC2 spend broken down in a way that makes sense without the friction of AWS's native interface. The dashboard gives him a running picture of where infrastructure dollars are going, which matters when the team is making decisions about scaling workloads or evaluating whether they can reduce the need to spin up additional compute resources for internal testing.
Use Case 2
An Addition to the Stack, Not a Replacement
One thing Seth emphasized is that Pump works as an addition to their existing tools, not a replacement. Greybeam sits between platforms like Looker and Snowflake, helping customers route queries more efficiently. They apply the same philosophy to their own infrastructure tooling: they don't rip things out, they layer on capabilities where gaps exist.
Onboarding reinforced this. Setup connected directly to their AWS account and didn't require the team to change how they work. Pump started surfacing spend data without demanding that Greybeam restructure anything. For a team of under ten where everyone wears multiple hats, zero-friction adoption is the difference between a product that gets used daily and one that gets abandoned after a week. Seth and the engineering team now have a cost visibility layer running in the background that simply wasn't there before.
Use Case 3
Keeping Their Own AWS House in Order While Scaling Their Customers
Greybeam is in an unusual position: they sell cloud cost reduction to their customers while running their own infrastructure on AWS. Every dollar they waste on their own compute is a dollar that could go toward building the product that saves their customers 86% on Snowflake. Before Pump, there was no easy way to keep a pulse on their own AWS spend without pulling an engineer away from product work.
Pump Save runs in the background, automatically optimizing Greybeam's AWS commitments without requiring engineering attention. Combined with the visibility from Pump View, Seth and the team can stay focused on building their query routing platform while Pump handles the cost optimization they'd otherwise have to do manually. As Greybeam scales into write workloads and GCP, that automated savings layer becomes more important, not less.
Pump’s impact
From the first week, Pump changed how Greybeam's engineering team tracks AWS spend. Seth stopped relying on AWS Cost Explorer for EC2 visibility and moved to Pump View as his primary dashboard for understanding where infrastructure dollars go. The switch eliminated the friction of navigating native AWS tooling and gave the team a faster, cleaner way to answer cost questions.
Beyond the dashboard, Pump shifted how Greybeam thinks about cloud cost management as an ongoing practice rather than an occasional check-in. The engineering team no longer needs to pull someone off product work to investigate spend. Pump View surfaces the data automatically, and Pump Save optimizes commitments in the background. For a company of under ten, removing that operational overhead matters.
Looking ahead, Greybeam plans to expand to GCP over the next one to two years as they build out multi-cloud support for their customers. They're also moving from read-only workloads into write workloads and building what Seth describes as a "query engine of query engines." As their infrastructure footprint grows across providers, Pump's multi-cloud visibility and automated savings will scale alongside them.