The use case: how FASHN AI deploys Sentry
FASHN AI uses Sentry for error monitoring, tracing and logs across its multi-stage AI image generation pipeline. It also uses Sentry alerts and webhooks to automatically reroute traffic to fallback providers when an endpoint degrades.
More reported results
Figures published in Sentry’s case study. They are not independently measured by usedby.
Issues that used to take about an hour to identify and fix now take 5 to 10 minutes.
In the customer’s words
The biggest win is that Sentry doesn't just find what the problem is, it also does something about it.Other companies using Sentry
Customers across industries, with public evidence.
Animation Digital NetworkConfirmed
AnthropicConfirmed
ArcadeConfirmed
AtlassianConfirmed
BasetenConfirmed
BitnamiConfirmedGo straight to the source
Based on Sentry’s published case study. We check the public evidence; the results are reported by the vendor.
sentry.io- Last checked
- Nov 12, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: ~90%Checked
Printed word for word on the page, near the name of FASHN AI.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of FASHN AI.
- FASHN AI uses SentryChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
With Sentry’s help we’ve built a closed-loop system that keeps uptime high and engineers from being paged,” Bochman says.