projectEureka™ | AI and simulation workspaces, organized by project

Built for workgroups and projects

AI notebooks on one stack, simulations on another, data somewhere else. projectEureka™ connects people, data, and compute in one project-centric platform so teams can ship models, sims, and research.

Project-centric A project holds the people, the apps, and the data
AI & simulation apps Jupyter, VS Code, Linux desktop, and more
Your environment Deploy on AWS, GCP, or on-prem Kubernetes
Multi-cloud buckets Attach AWS S3 and GCP GCS to the project

How it works

Create a project, launch apps next to your data, attach storage, and save a flow you can submit again. App containers and flow containers come from the public catalog.

1. Start a project Name it, set storage, invite collaborators.

2. Launch apps in the browser Jupyter, VS Code, terminal, and more, with cores, RAM, and GPU visible at a glance.

3. Keep data next to the work Project storage plus external AWS and GCP buckets, under project-based security.

4. Saved flows Compare two runs, a short training check, simulator shots, and a summary. Each one is ready to submit.

Virtual workstation and apps alongside your data

Secure, consistent virtual workstations

People still use laptops and desktops as clients. The heavy AI and simulation environment is a secure virtual workstation next to project data, consistent for the team.

App containers for Jupyter, VS Code, RStudio, a Linux desktop, and more. A simple install downloads the container once, then the project launches it.
Flow containers for OpenFOAM, GROMACS, BLAST, PyTorch, and other jobs inside a saved flow
Work that persists after devices sleep or leave the network
GPU-ready virtual desktops when teams need more than a notebook

Browse the catalog → · How install works →

Apps and jobs that keep running

Apps and jobs keep running after the laptop sleeps. You supervise them from the browser, under the project's access.

Under the project's access, next to the data
Keeps running when devices sleep or leave the network
Access from anywhere to check status and continue
From the project: a running app stays on the card, where you can stop it, delete it, or connect

How campus and labs use this → · Architecture view →

A running desktop stays on the project. Stop, delete, or connect from the card.

Deploy the environment where you need it

Run projectEureka™ on AWS, Google Cloud, or on-prem Kubernetes. Attach object storage from AWS and GCP buckets to the same project.

Environment placement: AWS, Google Cloud, or on-prem Kubernetes
Multi-cloud buckets: bring AWS S3 and GCP GCS into the project workspace
Project-level security for storage and collaborators
Shared platform model for research, education, and enterprise deployments

Home, project files, an external bucket, and a managed bucket. This picture is Google Cloud Storage. On AWS, the same action creates an Amazon S3 bucket.