Confidential and Verifiable Execution for Sovereign Data, AI, and Agents

Some of the most valuable AI work requires computing on sensitive data. Data holders can’t risk exposing that data, AI developers can’t risk exposing their intellectual property (IP), and autonomous agents add new risks. BeeKeeperAI’s EscrowAI® platform lets AI compute on sensitive data inside the data holder’s secure environment without exposing the data or the model, and it constrains what agents can do. Each step, from attestation to output release, runs under automatically enforced controls and is recorded in an immutable audit ledger.

EscrowAI runs in hardened trusted execution environments on AMD SEV-SNP and Intel TDX, with NVIDIA H100 confidential GPUs. On top of the hardware, the platform’s multi-party workflow automates attestation-gated key release, schema-based output checks, the audit ledger, and ephemeral environments that are commissioned for each job and decommissioned afterward. Because these controls apply during execution, they extend to agentic AI, limiting what agents can access, what they can release, and what persists after each compute cycle.

The platform is built for enterprise and multi-party collaborations in high-stakes, regulated sectors, including national security and defense, healthcare, life sciences, and oil and gas. It supports the AI lifecycle from training through deployment and inference, as well as agent workflows on raw data, with no masking, no data movement, and no IP exposure. Icahn School of Medicine at Mount Sinai and Morehouse School of Medicine used EscrowAI to enable AI developers to test models on real-world patient data in days rather than months. It was the first operational deployment certified under the Coalition for Health AI’s assurance process.

Spun out of the University of California, San Francisco, in 2022, BeeKeeperAI holds 14 patents.