The use case: how AfterQuery deploys Daytona
AfterQuery builds custom environments for training and evaluating AI agents, and uses Daytona to provision isolated, long-running sandboxes on demand, replacing an in-house GKE cluster. It versions each task's sandbox with Snapshots so trials start from the latest saved state.
More reported results
Figures published in Daytona’s case study. They are not independently measured by usedby.
40+ hours of engineering time saved weekly
In the customer’s words
As a frontier applied AI research lab, the infrastructure we need often does not exist. Daytona broke that trend. Their efficient, intuitive runtime platform now powers the sandbox infrastructure for our entire environments program.Other companies using Daytona
Customers across industries, with public evidence.
AsteroidConfirmed
BenchFlowConfirmed
CapyConfirmed
HandshakeConfirmed
Laude InstituteConfirmed
MartianConfirmedGo straight to the source
Based on Daytona’s published case study. We check the public evidence; the results are reported by the vendor.
daytona.io- Last checked
- Oct 27, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 86%Checked
Printed word for word on the page, near the name of AfterQuery.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of AfterQuery.
- AfterQuery uses DaytonaChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Thanks to Daytona's detailed documentation and simple API, AfterQuery replaced their GKE setup with fully managed sandbox infrastructure in a single day.