Research without infrastructure friction.
AI, GPU, engineering and scientific computing environments for academia and research. From a single student project to institution-wide research programs.
Audience
Institution-wide research computing infrastructure with per-department isolation and governance.
Dedicated compute environments for multi-year programs with data sovereignty and reproducibility.
Self-service GPU environments for your lab. No tickets, no waiting, budget-controlled access.
Persistent workspaces with GPU access, pre-configured frameworks, and reproducible execution trails.
Classroom-ready environments with standardized tooling, ephemeral or persistent, instructor-managed.
Cross-functional teams working on applied research with enterprise-grade collaboration and security.
Environments
GPU training, fine-tuning, inference pipelines. PyTorch, TensorFlow, JAX, and Hugging Face pre-installed.
GROMACS, OpenFOAM, numerical methods. MPI-ready clusters with high-bandwidth interconnects.
CAD, FEA, CFD, structural analysis. GPU-accelerated solvers with visualization pipelines.
Satellite analytics, GIS, spatial AI. Petabyte-scale raster and vector processing at GPU speed.
NeRF, Gaussian Splatting, photogrammetry. End-to-end pipelines from capture to publishable assets.
Research paper processing, OCR, NLP. Automated literature review, citation graphs, and knowledge extraction.
Platform
AI engineering interface. Orchestrate workflows, manage experiments, and execute capabilities through a unified control plane.
Persistent GPU environments with domain-specific tooling. 11 workbench families spanning AI, science, and engineering.
Domain-specific tooling and execution skills. 350+ capabilities across 25+ engineering and research disciplines.
From T4 through H100. Auto-scaling GPU clusters with RDMA interconnects, NVMe storage, and burst capacity.
Deployment
Fully managed on Nebula infrastructure. Zero ops overhead with auto-scaling, monitoring, and SLA-backed uptime.
Deploy in your institutional data center. Full control over hardware, data residency, and network topology.
Split between cloud burst and local compute. Sensitive data stays on-prem while elastic workloads scale to cloud.
Disconnected environments for sensitive research. Full platform capability without external network dependencies.
Governance
Complete data and compute separation between organizational units.
Per-project and per-researcher spending limits with real-time dashboards.
Connect to institutional identity providers. Shibboleth, Azure AD, Okta supported.
Data residency controls ensuring compliance with institutional and national policies.
Export datasets, models, and visualizations in formats ready for journals and conferences.
Every computation is hash-verified and lineage-tracked for full reproducibility.
From a single experiment to institution-wide research programs.