Joint AI across organizations,
data never exposed.

Secure AI collaboration is a method of running joint AI workloads across organizations where no participant shares their raw data. Each organization's data is processed inside a Trusted Execution Environment (TEE) — hardware-enforced memory isolation that prevents other parties and the platform operator from reading the inputs. Only the agreed result is released, with cryptographic proof of exactly what computation produced it.

By running the shared computation inside a Trusted Execution Environment. Each party's dataset is encrypted and only decrypted inside the TEE, which is verified by remote attestation before any data is released. The other parties — and the operator of the platform — never see the raw data. This is technically distinct from federated learning (which leaks information through gradients) and data clean rooms (which require legal rather than technical trust).

Multi-party computation (MPC) for AI is a category of techniques that allow multiple parties to jointly compute a result — a trained model, an inference output, or an analysis — without revealing their inputs to each other. TEE-based MPC, which Prism AI uses, achieves this through hardware isolation rather than cryptographic protocols, making it practical for large AI workloads where pure cryptographic MPC would be computationally prohibitive.

Yes. Prism AI was designed for exactly this use case. Each bank contributes its transaction data to a joint AML model inside a TEE. The model trains or runs inference on the combined data, but each bank's raw records are never exposed to the other banks or to the platform operator. The resulting model — or a combined risk score — is the only output shared.

TEE-based collaboration satisfies GDPR data minimization (Article 5(1)(c)) because no raw personal data is transferred to other parties — only the result. The technical guarantee is stronger than a data processing agreement: attestation proves that raw data was never accessible to other participants. Cross-border transfers under Article 44 are also simplified because the data itself does not cross borders — only the computation result does.

A data clean room provides a managed environment where parties can run queries on each other's data with contractual controls on what can be extracted. The trust is legal, not technical — if the clean room operator or another party wanted to extract raw data, they could. Prism AI uses hardware TEEs to make this technically impossible: the platform operator cannot read the data because the hardware enforces the boundary, not a contract.