Sold by: RELEVANCE LAB
Deployed on AWS
RLCatalyst Research Gateway is a solution built on AWS, and provides a self-service portal with cost and budget management that helps consume AWS resources for Scientific Research.
Overview
RLCatalyst Research Gateway is a solution built on AWS, and provides a self-service portal with cost and budget management that helps consume AWS resources for Scientific Research. It can be easily integrated into existing AWS customer accounts. It provides 1-Click AWS Service Catalog assets. budget management and data access with secure governance. Universities and Research Institutions can adopt this solution with minimal upfront investments. It is available in both SaaS and Enterprise models.
Highlights
- Accelerates Scientific Research using AWS resources with cost and budget governance
- Simple, secure, self-service portal with 1-Click AWS Service Catalog assets like Sagemaker, EC2, S3 etc.
- Built on AWS and available in SaaS and Enterprise models
Details
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Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Small | 1-10 Named users can be provisioned in the system for concurrent use | $1,000.00 |
Medium | 11-25 Named users can be provisioned in the system for concurrent use | $2,000.00 |
Large | 26 - 100 Named users can be provisioned in the system for concurrent use | $3,000.00 |
Dimensions summary
You buy this product through a contract based on the number of named users you provision for concurrent use. Three options set different user ranges. Small covers 1-10 named users, Medium covers 11-25 named users, and Large covers 26-100 named users. The tiers scale by how many people you need to access the platform, so you pick the range that matches your team size. All three deliver the same secure research computing capabilities; only the supported user count differs.
Top-of-mind questions for buyers
A named user is a specific person provisioned in the system for concurrent use. Each person you set up occupies one named-user slot, regardless of how often they log in. You count the individuals who need access, not simultaneous sessions or devices.
Each tier supports a set user range: Small covers 1-10, Medium covers 11-25, and Large covers 26-100 named users. When your provisioned users pass a tier's upper limit, you move to the tier that covers your new count. The move is not automatic; you select the tier matching your team size.
All three tiers deliver the same platform: secure research environments, cloud resource access, project and budget tracking, cross-charging for cost allocation, and governance controls. Only the supported named-user count differs between Small, Medium, and Large. Tier choice does not change the features you receive.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Support
Vendor support
As per support guide rlcatalyst@relevancelab.com /
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 RELEVANCE LAB
By Domino Data Lab
By Cloudwick
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In High Performance Computing
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In Data Warehouses, Data Governance, Analytic Platforms
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Self-Service Portal
Provides a self-service portal enabling users to provision resources without manual intervention or administrative overhead.
AWS Service Catalog Integration
Integrates with AWS Service Catalog to enable one-click provisioning of pre-configured assets including SageMaker, EC2, and S3.
Cost and Budget Management
Implements cost tracking and budget management capabilities to monitor and control AWS resource consumption.
Secure Governance and Access Control
Enforces secure governance with data access controls and security policies for resource management.
AWS Account Integration
Integrates seamlessly into existing AWS customer accounts without requiring separate infrastructure deployment.
Multi-Tool Ecosystem Support
Access to open-source and commercial tools including Jupyter, RStudio, SAS, Anaconda, MATLAB, and distributed compute frameworks like Spark, Ray, Dask, and MPI with one-click integration.
Integrated MLOps Workflows
Built-in workflows and automation for model development, deployment, and monitoring across the entire machine learning lifecycle with enterprise-grade process controls and governance.
Multi-Cloud and Hybrid Deployment
Support for deployment across public cloud, hybrid, and multi-cloud environments with Domino Nexus, enabling workload execution across any compute cluster in any cloud, region, or on-premises.
Model Governance and Reproducibility
Audit-ready platform with turnkey model governance, monitoring, remediation capabilities, and reproducibility controls to satisfy compliance and regulatory requirements.
Seamless Cloud Integration
Native integration with Amazon SageMaker for flexible model deployment and inference, with ability to export models to SageMaker or access SageMaker models within the platform.
Native AWS Service Integration
Native API integration with over 60 AWS services including Amazon Redshift, AWS Glue, Amazon QuickSight, and Amazon SageMaker for immediate data access without additional development.
Unified Data Management
Ability to unify all data types including unstructured, semi-structured, and structured data from both data warehouse and data lake environments across multiple workloads.
Built-in Data Catalog
Integrated data catalog functionality for search and sharing of data assets across the organization.
Access Control and Security Management
Centralized platform for managing users, roles, permissions, and security policies across all data and analytics workloads.
Data Ingestion and Transformation
Connectors, data pipelines, and ELT capabilities supporting single file upload, batch processing, and streaming data ingestion with transformation capabilities.
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