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H2O.ai

H2O AI Cloud

Composite Score

7.3 /10

CX Score

7.7 /10

14 Reviews Write a Review

What is H2O AI Cloud?

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models.

Company Details

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Awards & Recognition

H2O AI Cloud won the following awards in the Machine Learning Platforms category

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5 Top Rated Capabilities

3 Top Rated Features

2024

4 Top Rated Capabilities

3 Top Rated Features

2023

H2O AI Cloud Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on H2O AI Cloud.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

80 Likeliness to Recommend

1
Since last award

96 Plan to Renew

1
Since last award

86 Satisfaction of Cost Relative to Value

2
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+88 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love H2O AI Cloud?

0% Negative

6% Neutral

94% Positive

Pros

Helps Innovate
Continually Improving Product
Inspires Innovation
Efficient Service

Feature Ratings

Average 79

Data Ingestion

Pre-Packaged AI/ML Services

Data Exploration and Visualization

Feature Engineering

Algorithm Recommendation

Performance and Scalability

Algorithm Diversity

Openness and Flexibility

Model Tuning

Model Monitoring and Management

Ensembling

Vendor Capability Ratings

Average 81

Breadth of Features

Product Strategy and Rate of Improvement

Ease of Customization

Ease of Implementation

Business Value Created

Quality of Features

Ease of Data Integration

Usability and Intuitiveness

Ease of IT Administration

Vendor Support

Availability and Quality of Training

H2O AI Cloud Reviews

Role: Information Technology
Industry: Technology
Involvement: IT Leader or Manager

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Easy to apply advanced models

Likeliness to Recommend

8 /10

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Role: Information Technology
Industry: Finance
Involvement: IT Leader or Manager

Validated Review

Anonymous Reviewer

Submitted Apr 2022

provides value at economical price

Likeliness to Recommend

7 /10

Pros

Helps Innovate
Continually Improving Product
Enables Productivity
Efficient Service

Cons

Less Generous
Under Delivered
Less Transparent

Aman F.

Role: Information Technology
Industry: Consulting
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Aug 2021

Good product

Likeliness to Recommend

4 /10

What differentiates H2O AI Cloud from other similar products?

Easy implementation

What is your favorite aspect of this product?

Easy to use

What do you dislike most about this product?

Can't use in every usecase

What recommendations would you give to someone considering this product?

Limited usecase

Pros

Helps Innovate
Continually Improving Product
Appreciates Incumbent Status
Performance Enhancing

Cons

Less Fair
Less Generous
Under Delivered

Latest Research

H2O AI Cloud

What is H2O AI Cloud?

Company Details

Need Assistance?

Awards & Recognition

H2O AI Cloud Ratings

80 Likeliness to Recommend

1 Since last award

96 Plan to Renew

1 Since last award

86 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

+88 Net Emotional Footprint

How much do users love H2O AI Cloud?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Feature Engineering Ability to extract and build features from raw data.

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Model Tuning 'Ability to fine-tune models based on monitoring feedback within the platform.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Ensembling 'Ability to combine ML models for best results.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

H2O AI Cloud Reviews

Easy to apply advanced models

Likeliness to Recommend

Pros

provides value at economical price

Likeliness to Recommend

Pros

Cons

Aman F.

Good product

Likeliness to Recommend

Pros

Cons

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Title

1
Since last award

1
Since last award

2
Since last award

Feature Ratings

Data Ingestion

Pre-Packaged AI/ML Services

Data Exploration and Visualization

Feature Engineering

Algorithm Recommendation

Performance and Scalability

Algorithm Diversity

Openness and Flexibility

Model Tuning

Model Monitoring and Management

Ensembling

Vendor Capability Ratings

Breadth of Features

Product Strategy and Rate of Improvement

Ease of Customization

Ease of Implementation

Business Value Created

Quality of Features

Ease of Data Integration

Usability and Intuitiveness

Ease of IT Administration

Vendor Support

Availability and Quality of Training