Software Alternatives, Accelerators & Startups

AI & Analytics Engine VS H2O.ai

Compare AI & Analytics Engine VS H2O.ai and see what are their differences

AI & Analytics Engine logo AI & Analytics Engine

Accessible AI for everyone. AI-powered machine learning platform to clean, transform and model your data, and deploy and manage ML projects, simply, quickly and cost-effectively.

H2O.ai logo H2O.ai

Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.
  • AI & Analytics Engine Landing page
    Landing page //
    2020-09-23

The PI.EXCHANGE AI & Analytics Engine (the Engine) is a Data Science and Machine Learning (ML) platform that empowers everyone, even novice users, to affordably build high-performance ML applications in minutes or hours, not weeks or months.

The easy-to-use connected toolchain provides everything you will need to go from raw data to predictions and insights within a single pipeline. Manual and repetitive machine learning tasks are automated, and the Engine's intelligent features help guide the user end-to-end. So, whether you are building a small pilot project with no dedicated data science resources, or are deploying large-scale enterprise ML systems, you can equip your existing team with the right tool to build meaningful solutions, fast. The Engine gives users the flexibility to customize their ML pipeline from scratch for classification, regression, time-series, or clustering problems or to select an ML solution template to develop their ML application. While both ML development options are guided and require no-coding experience, the latter requires only articulation of business requirements and problem context via a few key steps - everything else is taken care of.

Notable AI solutions include: Customer Churn Prediction Leveraging your manufacturing data to build predictive maintenance strategies Predict online fraudulent transactions and reduce false positives and; Optimize logistics decision-making

  • H2O.ai Landing page
    Landing page //
    2023-10-25

H2O.ai

Website
h2o.ai
Pricing URL
-
$ Details
Release Date
2012 January
Startup details
Country
United States
State
California
Founder(s)
Cliff Click
Employees
10 - 19

AI & Analytics Engine features and specs

  • Smart Data Preparation
    We smartly recommend actions to perform on your dataset to amplify hidden signals within your raw data
  • Model Recommender and Performance Prediction
    Save time and resources, get recommended the machine-learning algorithm best suited to your data with an automatic view of the models' performance prior to training.
  • Flexible Deployment
    Whether you need the flexibility and agility of a cloud solution, robust on-premise security, and controls or a hybrid solution that integrates with your existing ecosystem of technologies. We support all major cloud providers and can deploy flexibly to your needs.
  • Model Life-cycle Management
    The one-click deployment automatically turns on monitoring of your model. Data submittedto the model for prediction is automatically logged and checked continuously for drift.

H2O.ai features and specs

  • Open Source
    H2O.ai provides open-source machine learning and AI tools that allow developers and data scientists to access and modify the source code, enabling greater customization and transparency.
  • AutoML
    H2O.ai's AutoML functionality significantly reduces the time and effort required to build and deploy machine learning models by automating key parts of the data science workflow.
  • Scalability
    The platform is designed to handle large datasets efficiently, both on single machines and in distributed environments, making it suitable for enterprise-level applications.
  • Wide Range of Algorithms
    H2O.ai supports a diverse set of machine learning algorithms, including deep learning, gradient boosting, and generalized linear modeling, among others.
  • Integration
    It seamlessly integrates with popular data science tools and platforms, such as R, Python, and Spark, facilitating ease of use in existing workflows.
  • Enterprise Support
    H2O.ai offers enterprise-level support and additional features through its Driverless AI product, which can be attractive for businesses seeking professional services and scalability.

Possible disadvantages of H2O.ai

  • Learning Curve
    The platform can have a steep learning curve for beginners, particularly those who are not familiar with programming or data science concepts.
  • Cost
    While the open-source version is free, the enterprise version (Driverless AI) comes with a significant cost, which may be prohibitive for smaller organizations or individual practitioners.
  • Resource Intensive
    The platform can be resource-intensive, requiring substantial computational power and memory, potentially limiting its accessibility to those with high-end hardware or cloud resources.
  • Complexity
    Despite the AutoML features, advanced users may find certain functionalities and customizations complex, necessitating deep technical knowledge and experience.
  • Limited Visualization Tools
    Compared to some competitors, H2O.ai offers fewer built-in data visualization tools, which may necessitate the use of additional software to fully understand and interpret data.

AI & Analytics Engine videos

The AI & Analytics Engine

H2O.ai videos

[Demo] Predicting Healthcare Outcomes with H2O.ai

More videos:

  • Review - H2O Just Add Water was the weirdest show...
  • Review - H2O wireless phone service full review 2019
  • Review - H2O Wireless:IS IT WORTH IT Review?
  • Review - H2O.ai VS. OBSERVE.ai: What The AI Race To Market Means
  • Review - H2O.ai Launches H2OGPT and LLM Studio: Build Your Own Enterprise Grade Chatbots

Category Popularity

0-100% (relative to AI & Analytics Engine and H2O.ai)
Data Science And Machine Learning
AI
19 19%
81% 81
Machine Learning
21 21%
79% 79
SaaS
100 100%
0% 0

Questions and Answers

As answered by people managing AI & Analytics Engine and H2O.ai.

What makes your product unique?

H2O.ai's answer:

At H2O.ai, democratizing AI isn’t just an idea. It’s a movement. And that means that it requires action. We started out as a group of like minded individuals in the open source community, collectively driven by the idea that there should be freedom around the creation and use of AI.

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AI & Analytics Engine and H2O.ai

AI & Analytics Engine Reviews

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H2O.ai Reviews

Top 7 Predictive Analytics Tools
If a company is interested in an open-source predictive analytics tool with data mining features, put H2O at the top of the list. It offers fast performance, affordability, advanced capabilities, and extreme flexibility. The dashboard for H2O offers a veritable smorgasbord of actionable insights. However, this tool is more for the expert data science crowd than for citizen...
The 16 Best Data Science and Machine Learning Platforms for 2021
Description: H2O.ai offers a number of AI and data science products, headlined by its commercial platform H2O Driverless AI. Driverless AI is a fully open-source, distributed in-memory machine learning platform with linear scalability. H2O supports widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep...

Social recommendations and mentions

Based on our record, H2O.ai should be more popular than AI & Analytics Engine. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AI & Analytics Engine mentions (1)

  • NEW RELEASE - ML-Solution Templates - Customer Churn Prediction Template
    DISCLAIMER: Hello everyone, my name is Fyona & I work in Marketing at PI.EXCHANGE. I wanted to share an EXCITING news regarding our upcoming release that I think can be helpful to many! The AI & Analytics Engine will be offering a Machine Learning (ML)  Solution Templates, starting with our Customer Churn Prediction Template. Source: about 2 years ago

H2O.ai mentions (3)

  • Major Technologies Worth Learning in 2025 for Data Professionals
    Artificial Intelligence (AI) is becoming a ubiquitous, and dare I say, indispensable part of data workflows. Tools like ChatGPT have made it easier to review data and write reports. But diving even deeper, tools like DataRobot, H2O.ai, and Google’s AutoML are also simplifying machine learning pipelines and automating repetitive tasks, enabling professionals to focus on high-value activities like model optimization... - Source: dev.to / 6 months ago
  • AI Democratization: Unlocking the Power of Artificial Intelligence for All
    Open-Source AI Frameworks: Open-source tools like TensorFlow, PyTorch, and H2O.ai allow developers to build and share AI models. These frameworks are freely available, fostering collaboration and innovation within the AI community. - Source: dev.to / 7 months ago
  • Nginx is now the most popular web server, overtaking Apache
    How about H2O? It's supposed to be significantly faster than Nginx: https://h2o.examp1e.net/. - Source: Hacker News / about 4 years ago

What are some alternatives?

When comparing AI & Analytics Engine and H2O.ai, you can also consider the following products

cnvrg CORE - Free ML Platform for everyone

datarobot - Become an AI-Driven Enterprise with Automated Machine Learning

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Azure Machine Learning Studio - Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

ML Dictionary - Your daily dose of machine learning and deep learning terms