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What is navio?

Elevate your organization's machine learning capabilities by utilizing a top-tier AI platform for seamless management, deployment, and monitoring, all facilitated by navio. This innovative tool allows for the execution of a diverse array of machine learning tasks across your entire AI ecosystem. You can effortlessly transition your lab experiments into practical applications, effectively integrating machine learning into your operations for significant business outcomes. Navio is there to assist you at every phase of the model development process, from conception to deployment in live settings. With the automatic generation of REST endpoints, you can easily track interactions with your model across various users and systems. Focus on refining and enhancing your models for the best results, while navio handles the groundwork of infrastructure and additional features, conserving your valuable time and resources. By entrusting navio with the operationalization of your models, you can swiftly introduce your machine learning innovations to the market and begin to harness their transformative potential. This strategy not only improves efficiency but also significantly enhances your organization's overall productivity in utilizing AI technologies, allowing you to stay ahead in a competitive landscape. Ultimately, embracing navio's capabilities will empower your team to explore new frontiers in machine learning and drive substantial growth.

What is HPE Ezmeral ML OPS?

HPE Ezmeral ML Ops presents a comprehensive set of integrated tools aimed at simplifying machine learning workflows throughout each phase of the ML lifecycle, from initial experimentation to full-scale production, thus promoting swift and flexible operations similar to those seen in DevOps practices. Users can easily create environments tailored to their preferred data science tools, which enables exploration of various enterprise data sources while concurrently experimenting with multiple machine learning and deep learning frameworks to determine the optimal model for their unique business needs. The platform offers self-service, on-demand environments specifically designed for both development and production activities, ensuring flexibility and efficiency. Furthermore, it incorporates high-performance training environments that distinctly separate compute resources from storage, allowing secure access to shared enterprise data, whether located on-premises or in the cloud. In addition, HPE Ezmeral ML Ops facilitates source control through seamless integration with widely used tools like GitHub, which simplifies version management. Users can maintain multiple model versions, each accompanied by metadata, within a model registry, thereby streamlining the organization and retrieval of machine learning assets. This holistic strategy not only improves workflow management but also fosters enhanced collaboration among teams, ultimately driving innovation and efficiency. As a result, organizations can respond more dynamically to shifting market demands and technological advancements.

Media

Media

Integrations Supported

MLflow
Microsoft Azure
Plotly Dash
TensorFlow

Integrations Supported

HPE Ezmeral

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

craftworks GmbH

Company Location

Austria

Company Website

www.craftworks.ai/navio

Company Facts

Organization Name

Hewlett Packard Enterprise

Date Founded

2015

Company Location

United States

Company Website

www.hpe.com/us/en/solutions/ezmeral-machine-learning-operations.html

Categories and Features

Machine Learning

Not specified

ML Model Management

Not specified

Categories and Features

Machine Learning

Not specified

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