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neptune.ai Features

What are the features of neptune.ai?

Deployment

  • Language Flexibility
  • Framework Flexibility
  • Versioning
  • Scalability
  • Language Flexibility
  • Framework Flexibility
  • Versioning
  • Scalability

Management

  • Cataloging
  • Monitoring
  • Governing
  • Model Registry
  • Monitoring

Operations

  • Metrics
  • Collaboration
neptune.ai Categories on G2

Filter for Features

Deployment

Language Flexibility

Allows users to input models built in a variety of languages. 34 reviewers of neptune.ai have provided feedback on this feature.
89%
(Based on 34 reviews)

Framework Flexibility

Based on 36 neptune.ai reviews. Allows users to choose the framework or workbench of their preference.
94%
(Based on 36 reviews)

Versioning

As reported in 37 neptune.ai reviews. Records versioning as models are iterated upon.
90%
(Based on 37 reviews)

Scalability

Offers a way to scale the use of machine learning models across an enterprise. 31 reviewers of neptune.ai have provided feedback on this feature.
88%
(Based on 31 reviews)

Language Flexibility

Based on 34 neptune.ai reviews. Allows users to input models built in a variety of languages.
85%
(Based on 34 reviews)

Framework Flexibility

As reported in 34 neptune.ai reviews. Allows users to choose the framework or workbench of their preference.
91%
(Based on 34 reviews)

Versioning

Records versioning as models are iterated upon. This feature was mentioned in 35 neptune.ai reviews.
90%
(Based on 35 reviews)

Scalability

Based on 34 neptune.ai reviews. Offers a way to scale the use of machine learning models across an enterprise.
88%
(Based on 34 reviews)

Management

Cataloging

As reported in 32 neptune.ai reviews. Records and organizes all machine learning models that have been deployed across the business.
84%
(Based on 32 reviews)

Monitoring

Tracks the performance and accuracy of machine learning models. This feature was mentioned in 35 neptune.ai reviews.
90%
(Based on 35 reviews)

Governing

As reported in 31 neptune.ai reviews. Provisions users based on authorization to both deploy and iterate upon machine learning models.
83%
(Based on 31 reviews)

Model Registry

Allows users to manage model artifacts and tracks which models are deployed in production. This feature was mentioned in 32 neptune.ai reviews.
84%
(Based on 32 reviews)

Cataloging

Records and organizes all machine learning models that have been deployed across the business. This feature was mentioned in 29 neptune.ai reviews.
82%
(Based on 29 reviews)

Monitoring

Tracks the performance and accuracy of machine learning models. 30 reviewers of neptune.ai have provided feedback on this feature.
90%
(Based on 30 reviews)

Governing

Based on 29 neptune.ai reviews. Provisions users based on authorization to both deploy and iterate upon machine learning models.
85%
(Based on 29 reviews)

Operations

Metrics

Based on 32 neptune.ai reviews. Control model usage and performance in production
83%
(Based on 32 reviews)

Collaboration

Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. This feature was mentioned in 32 neptune.ai reviews.
92%
(Based on 32 reviews)