Aggregion DataLabs & CleanRoom vs BeeKeeperAI (EscrowAI)

Aggregion DataLabs & CleanRoom is an environment for building and running models on data shared by multiple partners. Its workflow spans cataloging, discovering partner datasets, developing models in protected DataLabs, performing CleanRoom calculations, and activating results. Partners connect through a virtual data warehouse, with structured and semi-structured data supported. DataLabs virtual machines depersonalize data and apply distortion models during development. Listed languages include Python, R, PySparc, Scala, and Java. The architecture includes adapters for RDBMS, Hive, and Kafka, plus an advanced integration API. Intel SGX hardware-level encryption is described for enclave memory during shared computations. A decentralized protocol governs metadata, permissions, rights, approvals, and related collaboration actions. Scripts may be reviewed, approved, scheduled, or invoked through API, with execution logs kept on an immutable ledger. Deployment can be cloud or on-premise, and customers choose hosting for the DataLab and enclave. Pricing is available on request.

BeeKeeperAI’s EscrowAI is a confidential AI computing environment for protecting models and data while controlling AI-agent actions. It runs data and models inside a hardware-isolated Trusted Execution Environment, with encryption inside that environment, in transit, and at rest. An immutable ledger records computations and autonomous-agent activity. Governance controls authorize agent actions and can enforce or revoke permission when an agent acts outside approval or attempts to leave the protected environment. EscrowAI can run open-source and open-weight models in its secure environments. BeeKeeperAI says it can be hosted in the cloud or on premises, including an Azure confidential-computing setup using Intel SGX enclaves. Healthcare workflows support dataset creation, labeling, segmentation, and annotation. Data remains in an organization’s protected cloud storage and uses primary rather than synthetic or de-identified data. The paid product has pricing on request and no listed public trial.