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.
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
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 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.
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
What counts as one named user for billing purposes?
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.
If my team grows past my tier's user range, how does the cost change?
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.
What capabilities are included regardless of which user tier I choose?
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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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.
Self-Service Infrastructure Access
One-click, governed access to data, tools, and compute resources through a self-service portal with support for open-source tools including Jupyter, RStudio, SAS, Anaconda, MATLAB, and distributed compute frameworks like Spark, Ray, Dask, and MPI.
Centralized Knowledge Management
Central hub for AI operations and knowledge across the enterprise enabling reproducibility, reusability, and cross-functional collaboration with audit-ready platform capabilities.
Integrated MLOps Workflows
End-to-end model development, deployment, and monitoring capabilities within a unified platform with support for preferred tools and languages, including seamless integration with Amazon SageMaker.
Multi-Cloud and Hybrid Deployment
Support for deployment across public cloud, hybrid, and multi-cloud environments through Domino Nexus, enabling workload execution across any compute cluster in any cloud, region, or on-premises infrastructure.
Model Governance and Compliance
Turnkey model governance, monitoring, and remediation with robust controls for compliance, reproducibility tracking, and audit-ready processes designed for regulatory requirements including GxP processes.
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 Identity Management
Centralized management of users, roles, permissions, and security policies within a single platform.
Data Ingestion and Transformation
Support for multiple data ingestion methods including single file upload, batch processing, and streaming with ELT capabilities for data transformation.
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