Verta Model Deployment

Deploy Models Faster and Safely, at Scale

Verta Model Deployment enables you to safely release models using CI/CD best practices.

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Deploy, serve, and scale models safely and reliably.

Model Deployment and Serving

Deploy models to production with a single click

Generate predictions for both batch and real-time processing

Integrate with your CI/CD pipeline using open APIs

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Safe Deployment Through Best Practices

Configure canary deployment for incremental rollouts, setup auto-rollback options

Optimize infrastructure parameters like compute resources, environmental variables

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Scale Inference Service

Scale-up and scale-out with our high volume, low latency prediction service

One framework that supports both batch and streaming inference serving

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Take a Tour

One platform, all of your model delivery needs.

Manage

Manage

Full-lifecycle model management from experiment tracking to production registry

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Deploy

Ensure production-quality operations with reliable governance and auditing.

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Operate

Reliable batch and real-time inference & serving on any k8s infrastructure.

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Monitor

Keep models relevant with real-time decay monitoring and logging.

Compatibility

We integrate with your AI-ML stack.

Verta supports all of these popular platforms and frameworks—plus many, many more.

Don't take our word for it. See what others are saying.

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

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LeadCrunch's Data Science teams create Machine Learning models that help B2B companies find better prospects faster.

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A leading collaboration platform utilizes ML to prevent abuse, make recommendations, and improve user experience.

Try Verta Today

Run Verta as SaaS, On-prem, or in your VPC.