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For Research Teams

RosettaScience and RosettaInsight -- reproducible, governed, multi-cloud research computing.

Overview

Research teams need powerful compute without the overhead of cloud operations. Most researchers are not cloud engineers -- and they shouldn't have to be. RosettaHub's MetaCloud gives principal investigators and researchers self-service access to HPC, GPU, and general-purpose workloads across AWS, Azure, GCP, Alibaba Cloud, OVH, and OpenStack -- with grant-aligned budgets, reproducible environments, and zero cloud expertise required.

The platform's value goes beyond multi-cloud: it makes cloud computing accessible to a much wider audience. A researcher who has never opened the AWS Console can launch an HPC cluster, snapshot their environment, and share it with collaborators -- all through formations and one-click workflows.

Key Capabilities

Reproducible Environments via Formations

Formations are cloud-agnostic recipes that capture an entire research environment. The research workflow follows a natural cycle:

Clone a public or shared formation Customize packages and data Launch on any cloud Snapshot your work Share with collaborators Publish to the marketplace Iterate

Because formations are cloud-agnostic, an environment built on AWS deploys identically on Azure or GCP -- enabling cross-institutional collaboration without lock-in.

Grant-Aligned Budget Delegation

RosettaHub's cloud operations layer maps directly to how research is funded:

Level Maps To Controls
Organization Department or Institute Top-level budget pool
Sub-Organization Research Group Delegated budget with transfer rights
Project Grant or Experiment Dedicated cloud accounts with hard spending limits
User Individual Researcher Zero, one, or more dedicated cloud accounts with personal budgets -- or participation in a project's cloud accounts via project roles

Roles can be assigned directly to users or inherited from the organizations they belong to. A user with no personal cloud accounts can still work within a project's cloud accounts through assigned project roles.

Budget enforcement is real-time and event-driven -- not based on billing lag. If a grant allocation is exhausted, new launches are blocked immediately.

Self-Service Portals

Researchers access pre-approved formation catalogs without filing IT tickets. Administrators define guardrails (instance types, regions, spending limits) and researchers operate freely within those boundaries.

Data Management and Sharing

Formations bundle data and compute together, so researchers receive everything they need in one click -- no separate data configuration step.

Capability How It Helps Researchers
Formations bundle data + compute Storage mounts are part of the formation template. Launch an environment and the datasets are already there.
Shared storages Share storages (S3, EFS, EBS) with fine-grained access control. Curated datasets can be shared read-only while each researcher has personal writable space.
Cross-cloud data mounting Mount AWS S3 data on a GCP instance -- cloud boundaries are transparent for data access.
Scoped dataset views Map specific folders within a large S3 bucket to individual MetaCloud storage artifacts, giving teams focused access to the data they need.
Private marketplace Publish formations (with dataset mounts) to institutional catalogs -- effectively a research service and data catalog.
URL-based sharing Share a dataset-configured formation as a link. Collaborators deploy it with data already mounted, on their own budget.

Multi-Cloud HPC and GPU

Launch HPC clusters (AWS ParallelCluster), Spark/Hadoop clusters (EMR, Dataproc), and GPU instances (NVIDIA) from a single interface. Spot and preemptible instances reduce costs by up to 90% for fault-tolerant workloads.

AI and GenAI Integration

Researchers can access cloud AI services -- AWS Bedrock, SageMaker, and others -- through federated console access while RosettaOps governs the budget. GPU formations provide compute for model training and inference.

Capability Status
GPU formations for ML training Available
Federated access to cloud AI services (Bedrock, SageMaker, Vertex AI) Available
AI/LLM usage tracking and budgeting Coming Q2 2026
MCP server for AI-powered research operations Coming Q1 2026
ResOps Agents for AI-driven governance Coming Q2 2026

Trusted Research Environments

For research involving sensitive data, RosettaHub supports Trusted Research Environments aligned with the Five Safes framework. Project isolation, encrypted storage, SSO, RBAC, and compliance policies provide strong coverage across Safe People, Projects, Settings, and Data. Egress controls (Safe Output) are being strengthened with Gitea airlock and Amazon Macie integrations.

RosettaInsight on AWS Marketplace

RosettaInsight is RosettaHub's MetaCloud offering on AWS -- one-click GPU/CPU instances, pre-built template-based environments, and team collaboration tools delivered as a self-service platform. Researchers launch compute, share environments, and work with familiar tools (Jupyter, RStudio, VS Code) without needing AWS expertise.

Free Tier Available

RosettaInsight includes a free tier (up to 4 GB RAM) with Jupyter, RStudio, and VS Code environments -- ideal for evaluating the platform with a small research group. Paid plans start at $10/month per 8 GB RAM.

View on AWS Marketplace

Next Steps