Need: governed AI and simulations

Governed AI and simulation workspaces on your infrastructure

Give platform and product teams one project-centric place for models, sims, and agents, under your policies, next to the data. Deploy on AWS, GCP, or on-prem Kubernetes.

AI & simulations Models, sims, and apps on one project spine
Your control plane AWS, GCP, or on-prem Kubernetes
Project governance Access, storage, and collaborators by project

Built for enterprise AI and simulation work

One environment where teams ship models and sims on shared infrastructure, with project access next to the data.

Project-centric People, apps, agents, and data hang off the project
AI & simulation apps Jupyter, VS Code, Linux desktop, OpenFOAM, and more
Secure agents Long-running work under project access, not only laptops
Multi-cloud buckets Home dir, project storage, AWS S3 & GCP GCS (more to come)
Running apps in a project workspace
Interactive AI and sim apps
Project and cloud storage resources
Storage next to the work

Why AI and simulation work stalls in the enterprise

Notebooks on one stack, simulation codes on another, datasets in object stores, and desktops that never match. Teams spend too many cycles on setup before they get to models and results.

projectEureka™ is a project-centric platform you deploy on infrastructure you choose: browser apps, secure long-running work, and multi-cloud buckets under project-level access.

  • One spine for the work: Projects organize people, tools, and data for AI and simulation initiatives
  • Environment under policy: Run on AWS, GCP, or on-prem Kubernetes, one deploy target you control
  • Secure virtual workstations: Consistent browser desktops and apps next to data; personal laptops still work as the client

For platform, product, and R&D teams

Enterprise value shows up when multiple groups share a governed pattern: secure, consistent virtual workstations and project environments.

  • Platform teams: Standard place to land AI and simulation workspaces with clear deploy and storage options
  • Product and engineering: Shared projects for model work, evaluation, and simulation support tools
  • Applied R&D: Persistent environments for experiments that must survive overnight and handoffs
  • Security-minded IT: Project-based access, environment you operate, buckets attached under project control
Projects are how teams and data stay organized
Browser launchers for AI and simulation stacks

AI and simulation apps in the browser

Give teams secure, consistent virtual workstations and launchers for AI and simulation work, next to project data. Personal machines remain the client; the heavy environment is shared and governed.

  • Virtual desktops and apps: Jupyter, VS Code, Linux desktop, terminal, OpenFOAM, and related tools in the browser
  • Data adjacency: Open apps where home directory, project storage, and buckets already are
  • Resource visibility: Cores, RAM, and GPU shown on running apps in the UI
  • Handoffs: Shared project context for the next person on the work

Secure agentic work under enterprise control

Agents and long-running AI or simulation jobs should not depend on a laptop that sleeps or leaves the VPN. Run them in the project environment, under project access, and supervise from the browser.

  • Secure project environment: Agent and long-job work next to governed data
  • Keeps running when devices disconnect or people change shifts
  • Access from anywhere your policies allow, in the browser
  • Same platform model as interactive apps: one project spine for people, tools, and storage

Platform overview → · Security architecture →

Long-running work stays in the environment you operate

How an enterprise deployment looks

Same project-centric model as the rest of projectEureka™, licensed for enterprise use on infrastructure you choose.

Environment

One deploy target: AWS, GCP, or on-prem Kubernetes

Project

Team or initiative: name, collaborators, access, and scope

Apps & agents

AI and simulation launchers; secure agents that stay available

Storage

Home directory, project storage, multi-cloud buckets (AWS S3, GCP GCS, more to come)

Enterprise is a licensed path with commercial engagement. Teaching and research free software is a separate path with its own terms; cloud and cluster costs always remain yours.

Multi-cloud buckets attached to the project

Storage next to AI and simulation work

Attach multi-cloud buckets no matter where the environment runs. Teams open apps where the data already lives.

  • Home directory: Personal space for each user in the environment
  • Project storage: Shared space for the team’s initiative
  • Multi-cloud buckets: AWS S3 and GCP GCS today, more to come, usable from AWS, GCP, or on-prem K8s deploys
  • OrangeFS® path: Scale-out parallel storage when jobs outgrow a single mount or object layout

OrangeFS® support → Technical details →

Who it fits

Company capability and direction

Omnibond has delivered cloud HPC and data-adjacent systems at extreme scale. That engineering depth sits behind projectEureka™ today, and behind infrastructure work aimed at job routing, SLURM-friendly batch, dynamic filesystems, and broader platform options over time.

Now / direction → Company capability → Stories →

Start an enterprise conversation

Share your work email. We will follow up on deploy target (AWS, GCP, or on-prem K8s), AI and simulation use cases, storage needs, and pilot scope.

We typically reply to credible requests within a couple of business days. Please use a work or institutional email.

Technical details Research & education path ← Omnibond outcomes