Industry · Research

Collaborate across institutions
without exposing data.

Privacy-preserving collaboration on shared datasets, so research institutions can study together without pooling records or exposing participant data.

Contact SalesView Prism AI
The challenge

Research collaboration requires
sharing data without exposing it.

Multi-institution research creates value by combining datasets — but participant data, proprietary methodologies, and institutional IP cannot be pooled in a shared cloud environment. Researchers need a way to collaborate without exposure.

Data pooling approachUltraviolet Research AI
Participant data ✕ Shared in the clear — ethics and legal risk. Each institution's data stays sealed in a TEE.
Methodology exposure ✕ Research methods visible to all parties. Algorithms sealed; only results shared.
IRB/Ethics requirements ✕ Data sharing creates ongoing compliance burden. No raw data shared; attestation proves it.
Cross-border collaboration ✕ Complex data transfer agreements required. Computation happens locally; only results cross borders.
How Ultraviolet solves it

Leading with Prism AI.

Leads with

Prism AI

Secure AI Collaboration

The collaboration layer for multi-institution research: run shared AI workloads across institutional boundaries inside TEEs, with each institution's data sealed from the others.

  • Multi-institution computation without data pooling
  • Each party's data sealed in a TEE
  • Remote attestation for research reproducibility
  • Free tier for research evaluation
Explore Prism AI
Supported by

Cube AI

When individual institutions need private AI inference on their own data, Cube AI provides the full platform.

Explore Cube AI
— Get started

Research that advances science
without compromising privacy.

Talk to the team about multi-institution AI collaboration, privacy-preserving research methods, and free tier access.

Contact sales View Prism AI
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