Data governance & privacy
Tonic.ai's de-identification product for unstructured text. It scans files and strings with named-entity models, then redacts or replaces sensitive values with consistent synthetic substitutes for use in LLM prompts, RAG corpora and training sets, with guided review. Governance features beyond RBAC and SSO are not documented.
commercial · generally available · Research snapshot 2026-09-06
Visit the official product source ↗Data governance & privacy
Useful conversation with: Data engineer, Privacy engineer, ML platform lead.
Show me a guided redaction project that de-identifies a folder of PDFs, then the SDK call that redacts a live prompt with the same entity configuration.
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
Textual scans dataset files to identify sensitive values and lets users redact or replace them, including guided redaction projects with human review before output files are downloaded.
Limit: Documentation does not state detection accuracy or language coverage.
Documented by provider
A REST API and Python SDK redact text strings and manage datasets and user access, and a Textual MCP server can receive requests from an external AI agent.
Limit: The MCP server's authentication and scoping model is not described on these pages.
Vendor claim
Role-based access controls and single sign-on are listed as enterprise security features of Textual.
Limit: Product page listing; no permission model documentation was fetched.
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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