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Verta + Scribd

Scribd accelerates model delivery with Verta MLOps


Faster model packaging
& development


Multiple model
deployment paths


Deployment process

The Challenge

No easy way to track, monitor, or reproduce models

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.”

Model management was always a bespoke process

Each model was managed differently, which was inefficient and made collaboration difficult. “Product teams want to move as efficiently as possible—they don't want to waste time trying to figure out platform-level questions like, ‘What should be the standardized way to manage our models?’

No way to proactively find problems in production

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.

Serving models to production was a slow process

“Every time anyone wanted to create a new model, it had to go through an external team, wait for a couple of days and then come back to them,” recalls QP. “That was really painful.”

“We are impressed with Verta’s scalable and feature-rich model management platform. And the team goes above and beyond to provide excellent customer support.”

Qingping (QP) Hou,

Senior Engineer, Core Platform

The Solution

Verta provides MLOps solutions that enable high-velocity Data Science and Machine Learning teams to deploy and operate models at scale.

Verta Experiment Management and Registry

“With Verta, we could make model registry and management fully self-service — where they don't have to rely on us anymore,” says QP. “Having this centralized place to manage models makes it a lot easier for teams to collaborate.”

Verta Inference easily deploys models into production

“Previously, in order to spin up a new endpoint for a model, we had to create a new Git repository and set up a new pipeline in Jenkins. There are so many steps that have been replaced by a single button click in Verta. Teams are starting to take notice, and it’s brought efficiency to our entire MLOps workflow.”

Verta works seamlessly with Scribd’s existing infrastructure

“With Verta, all the systems — production, staging, development — all interact with a single entity: the Verta API. For the infra team in particular, this alleviated a lot of headaches.”

Verta ensures security and compliance

Verta allows Scribd to maintain compliance and data security controls. “With Verta, we get compliance and production readiness assurance in one solution. Previously we had to pick one of these two, but now we get both in a single system. That was a big change for us.”




Digital Content Library


Scribd is the world’s most fascinating digital library, providing unlimited access to high quality content that enriches people’s daily lives.  

The company utilizes machine learning to optimize search, make recommendations, and improve new features.

Try Verta today