Data governance & privacy
India- and US-based vendor offering deterministic tokenization for sensitive values used in LLM prompts and AI pipelines, with policy-controlled unmasking that requires an explicit request and sufficient caller permissions. Documentation covers tokenization mechanics; discovery, lineage, consent and audit logging are not described.
commercial · generally available · Research snapshot 2026-09-06
Visit the official product source ↗Data governance & privacy · Runtime authorization & controls
Useful conversation with: Application security engineer, Privacy engineer, AI platform lead.
Demonstrate masking a support ticket before it goes to an LLM, then an unmask request being denied because the active policy does not permit it.
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
Replaces sensitive values with deterministic, non-sensitive tokens that can be stored, logged, shared and processed in AI and analytics workflows, including LLM prompts and AI pipelines.
Limit: Documentation does not state detection coverage or accuracy for automatically identifying sensitive values.
Documented by provider
Tokens are reversible only when an explicit unmask request is made, the active policy allows unmasking and the caller has sufficient permissions; unmasking is never automatic.
Limit: The policy engine, role model and whether unmask events are logged are not documented on this page.
Documented by provider
A masking API identifies and substitutes personally identifiable information in text with secure tokens, keeping tokens consistent for the same value and token name.
Limit: The help-centre page is dated 2023, so current API surface may differ.
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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