The use case: how Greptile deploys Hatchet
Greptile uses Hatchet to run and scale its codebase indexing workflows, which parse code and generate and embed docstrings for LLM-based code search. Hatchet provides resumable workflow steps, per-worker run limits, fair distribution of work across concurrent users, and a dashboard for monitoring runs.
More reported results
Figures published in Hatchet’s case study. They are not independently measured by usedby.
the team was able to double their number of users in just 2 weeks!
Other AI tools used by Greptile
Other public relationships recorded on usedby.
Explore Greptile’s AI stack
Hatchet users in DevTools & Infrastructure
Companies in the same sector, with public evidence.
See all Hatchet customers
Go straight to the source
Based on Hatchet’s published case study. We check the public evidence; the results are reported by the vendor.
hatchet.run- Last checked
- Nov 13, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 50%Checked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Greptile.
- Greptile uses HatchetChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
With Hatchet, Greptile has been able to process massive codebases like the Linux kernel, Python, and VS Code. Failed workflow runs have been reduced by 50% and the team was able to double their number of users in just 2 weeks!