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Scribd has several ML models running in production. But according to QP, Scribd’s Senior Engineer, Core Platform, “We didn’t really have a consistent way to keep track of these models — how many models we had in production or what types of models they were.”
Without a way to systematically track and monitor models, Scribd couldn't flag performance degradation in a fully automated fashion. Engineers would learn of issues in production through manual testing or customer feedback.
Download this case study to learn how Verta delivered 10X faster model packaging, consolidated multiple model deployment paths, and standardized the deployment process for Sribd.
- Vendor:
- Verta
- Posted:
- Nov 4, 2021
- Published:
- Oct 7, 2021
- Format:
- Type:
- Case Study
