Solution · Secure Collaboration

Joint AI across organizations,
data never exposed.

Run shared models and analyses across organizational boundaries with every party's inputs sealed inside a Trusted Execution Environment.

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The challenge

Data sharing for AI collaboration
creates unacceptable risk.

Organizations with complementary data cannot pool it for AI workloads without creating legal, commercial, and security exposure. The result: valuable insights left on the table because no one can trust a shared platform.

Data pooling approachUltraviolet Secure Collaboration
Data access ✕ All parties see all data in the clear. Each party's data is sealed in a TEE — others see nothing.
Trust model ✕ Contractual — hope everyone complies. Cryptographic — attestation proves it.
Legal risk ✕ Data sharing creates ongoing IP and regulatory exposure. No raw data shared; only the agreed result.
Auditability ✕ Hard to prove what happened to shared data. Remote attestation proves exactly what ran.
How Ultraviolet solves it

Leading with Prism AI.

Leads with

Prism AI

Secure AI Collaboration

Run joint AI workloads across organizations inside Trusted Execution Environments — each party keeps its data private, shares only the result.

  • Multi-party computation inside TEEs
  • RBAC + ABAC for dataset and algorithm providers
  • Remote attestation proves what ran
  • Free tier; enterprise tiers for production
Explore Prism AI
Supported by

Cocos AI

The TEE infrastructure Prism AI runs on — hardware-enforced isolation, open-source, Apache 2.0.

Explore Cocos AI
— Get started

Collaborate without
giving up your data.

Talk to the team about Prism AI deployments, multi-party AI workloads, and free tier access.

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Apache 2.0 · Deploy anywhere · No vendor lock-in