The use case: how Snorkel AI deploys Daytona
Snorkel uses Daytona to provision configurable, isolated sandboxes on demand so it can run thousands of long-running agent simulations in parallel when building AI training datasets, environments, and evaluations. Pre-configured snapshots set CPU, memory, disk, and dependencies for each agent workload.
More reported results
Figures published in Daytona’s case study. They are not independently measured by usedby.
1,073,756 sandboxes provisioned with Daytona
In the customer’s words
Daytona delivers scalable sandbox infrastructure that works out of the box. With it, we turn multi‑day runs into hours, which directly improves how fast we ship new datasets and environments.Other AI tools used by Snorkel AI
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Daytona users in Artificial Intelligence
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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
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- Snorkel AI uses DaytonaChecked
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Because Daytona is optimized for sandbox orchestration, Rustem and his team run long-running sandboxes in parallel, evaluating thousands of outcomes in a single pass. This setup saves hours every week, which is redirected toward refining evaluation rubrics and collaborating on new expert datasets.