# How FASHN AI Went From 4-Hour Outages To Automatic Fixes With Sentry

> Learn how FASHN AI uses Sentry's Error Monitoring, Logs, Tracing, alerts, and webhooks to cut time-to-fix by 90% and automatically reroute traffic away from degraded AI endpoints — turning 4-hour outages into fixes that resolve themselves.

**URL:** https://sentry.io/customers/fashn/

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**Company:** FASHN AI

FASHN AI builds the generative models behind virtual try-on, AI fashion models, and model-swapping for fashion brands, turning a single product photo into studio-quality campaign imagery. Founded by husband-and-wife team Dan and Aya Bochman, the self-funded startup runs on a long chain of AI endpoints — image analysis, captioning, generation, video, and uploading — each one a separate model, a separate provider, and a separate way to fail. FASHN uses Sentry's Error Monitoring, Logs, and Tracing to instrument every stage of that pipeline separately, so a "generations are slow" complaint can be traced to the exact component at fault rather than hours of manual log digging. Issues that used to take about an hour to identify and fix now take 5 to 10 minutes. Going further, FASHN built a closed-loop failover system on Sentry's alert rules, webhooks, and API: when an external endpoint deviates from its healthy baseline, Sentry fires a webhook and FASHN's servers reroute traffic to a backup provider automatically, then route it back once Sentry detects recovery. Four-hour downtimes that once required a manual judgment call and a redeploy now resolve without an engineer being paged.

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*Source: [sentry.io/customers/fashn/](https://sentry.io/customers/fashn/)*