Model Deployment

Scalable model deployments with just a few clicks

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Model deployment
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A model deployment framework for all kinds of ML models

  • Deploy models built in the frameworks of your choice
  • Automate the model containerization process at runtime
  • Support for models written in multiple languages (Python, R, Scala, etc.)
  • Vendor agnostic

Continuously serve prediction results to your applications

  • The REST API endpoint for interactive requests
  • Dynamically consume the best model from multiple models based on traffic behavior
  • Determine model performance through A/B testing
  • Safely promote and demote models
  • Fallback strategies when models are not responsive
  • Test models in a production environment before deployment
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We'll take care of your infrastructure management

  • Auto-scaling based on model traffic
  • System monitoring dashboard for DevOps
  • Alerting and health checks

Score your models on large datasets

  • Offline batch scoring
  • Pull and join data from multiple sources
  • Feed data to your models and store their outputs
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Deploy models faster

Cut the time it takes to deploy a model from a couple of months to just a couple of hours.

Deploy models faster

Cut the time it takes to deploy a model from a couple of months to just a couple of hours.

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Learn more about Datatron’s Deployment Module

Datatrone

Datatron's Deployment Module for Machine Learning Models

Read more about Datatron and Model Deployment by checking out our white paper.

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