Data governance & privacy
Skyflow's pattern for isolating sensitive values in a data privacy vault so prompts, training sets and RAG content carry tokens instead of raw identifiers, with role-based re-identification for authorized processes. It governs sensitive fields rather than discovering data estate-wide, and requires application changes to adopt.
commercial · generally available · Research snapshot 2026-09-06
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Useful conversation with: Privacy engineer, Platform architect, CISO.
Show me a RAG flow where the vault de-identifies customer records before embedding and only a privileged role can re-identify the values in the answer.
Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.
Documented by provider
A Detect vault stores detected entities and their tokens so data can be de-identified at collection and re-identified under governance controls during training and inference.
Limit: Documentation page describes the pattern, not detection accuracy or entity coverage.
Documented by provider
Roles and access controls govern re-identification, with permissions allowing data to be fully or partially revealed only to validated users and authorized processes.
Limit: Does not document audit logging of re-identification events on this page.
Vendor claim
Skyflow for GenAI is presented as detecting and redacting sensitive data during collection, model training, fine-tuning, RAG and inference, including data flowing into and out of generative AI agents.
Limit: Product page; agent-specific integration mechanics are not described.
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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