Sold by: Altair EngineeringÂ
Deployed on AWS
Altair AI Hub connects people, processes and systems to ensure AI delivers business impact. Enterprise-wide collaboration, decision automation, deployment and control.
Overview
Altair AI Hub extends the Altair AI platform with enterprise-wide collaboration, decision automation, deployment, and control. It connects people, processes, and systems to ensure AI delivers business impact.
Empower people of all skills to collaborate and create AI solutions. Share, reuse and deploy models and processes in a project-based, version-controlled, central environment that improves collaboration and governance. Automate important tasks like retraining models, preparing, cleaning and continuously scoring data. Radically speed up predictive model creation and run 100's of models in parallel. Easily integrate analytic results into business processes and applications with a rich set of interactive dashboards, connectors, BI integration and web-service APIs.
Highlights
- Altair AI Hub's projects, dashboards and multi-user access let contributors throughout your organization collaborate on predictive analytic process development and deployment.
- The embedded Notebooks provide the perfect way for python code to be used across a project.
- Altair AI Hub allows you to run computationally intensive tasks on enterprise hardware freeing up your workstation or laptop computers, for improved productivity and faster time to value.
Details
Sold by
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
m4.2xlarge Recommended | $11.56 |
h1.8xlarge | $57.79 |
i3.8xlarge | $57.79 |
x1.32xlarge | $358.30 |
r4.16xlarge | $92.47 |
m4.large | $11.56 |
p2.16xlarge | $138.70 |
g3.4xlarge | $23.12 |
h1.4xlarge | $23.12 |
p3.16xlarge | $138.70 |
Vendor refund policy
No refunds
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Additional details
Usage instructions
Start a new VM based on the image (Open the EC2 console, go to the AMIs section and find the latest Altair RapidMiner AI Hub AMI. Provide at least 32 Gb RAM for it. In the instance details section, enable 'Auto-assign Public IP'. Use a security group that allows at least TCP connections through ports 80, 443 (home page), 5080 (deployment administration) and 22 (SSH). Wait until the instance starts and 10 additional minutes for all the RapidMiner Services to start. To access these services in this VM you need to connect to the url http://[public IP or name of the instance]. The password is the id of the VM.
Resources
Vendor resources
Support
Vendor support
Contact support here
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Altair Engineering
By ecosystem.Ai
Top
100
In Business Intelligence & Advanced Analytics, ML Solutions
Top
100
In Generative AI, Analytic Platforms, Business Intelligence & Advanced Analytics
Top
100
In Generative AI, Analytic Platforms, ML Solutions
AI generated from product descriptions
Machine Learning Collaboration Platform
Enterprise-wide collaborative environment for developing, sharing, and deploying AI models with version control and multi-user access
Computational Resource Management
Capability to run computationally intensive machine learning tasks on enterprise hardware, optimizing computational resources
Notebook Integration
Embedded Jupyter-style notebooks supporting Python code development and execution within project workflows
Model Deployment Automation
Automated processes for model retraining, data preparation, cleaning, and continuous scoring across multiple models
Analytic Integration Framework
Rich set of interactive dashboards, connectors, business intelligence integration, and web-service APIs for embedding analytic results into business processes
Machine Learning Environment
Low-code platform combining behavioral social science with real-time machine learning for creating prediction projects
Model Serving Capabilities
Robust platform for integrating AI models into websites, apps, call centers, and other systems with comprehensive API access
Prediction Infrastructure
Includes Prediction Server, Workbench, Notebooks, and Client Pulse Responder for end-to-end machine learning project management
Real-Time Analytics
Supports dynamic experimentation, feature engineering, and real-time inference with scoring capabilities
Development Tools
Provides Jupyter Notebooks with default Python libraries and Grafana dashboard for performance tracking and visualization
Data Science Collaboration Platform
Provides a unified environment for data workers to collaborate and deploy data science solutions across an organization
Low-Code Analytics Workflow
Enables intuitive data processing through a low-code, no-code analytics platform accessible to users with diverse technical backgrounds
Cloud-Native Architecture
Supports scalable, team-controlled execution with a cloud-native infrastructure design
Workflow Deployment Management
Allows secure sharing, monitoring, and deployment of analytical workflows across enterprise environments
Multi-Disciplinary Data Processing
Supports data analysis and processing for users from business, technical, and data science backgrounds
Standard contract
No
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