AI retrieval
Scoped by tenant, case, document accessibility, hashed metadata, post-validation, and stale vector rejection on the hardened path.
Trust Center
A central trust portal for teams evaluating Caseflow before bringing legal, investigative, inheritance, and other confidential case records out of fragmented tools and into one workspace.
Caseflow trust materials support procurement, security review, privacy assessment, and AI governance discussions with clear language about how the system handles sensitive casework.
The access, authorization, AI safeguards, and auditability controls around your central case record.
Controlled AI processing, permission-aware retrieval, vector filtering, human review workflows, retention, deletion, and known limitations.
How workspace content, account data, collaboration records, support communications, billing metadata, and AI-assisted processing are handled.
Terms for professional account use, customer content, collaboration permissions, generated outputs, and third-party services.
Cookie, local storage, service worker, installable app, localization, preference, and authentication-state disclosures.
Support for onboarding, moving into the workspace, account access, workflow questions, and privacy or AI handling concerns.
The strongest trust areas are the main AI retrieval path, tenant/case/document scoping, permission-aware context rebuilding, and confirmation-gated AI write actions.
Scoped by tenant, case, document accessibility, hashed metadata, post-validation, and stale vector rejection on the hardened path.
Migrated document views request permission-checked short-lived access links instead of reusing stored token URLs.
AI output is positioned as assistive and reviewable, with professional decisions left to users.
Some legacy or out-of-scope surfaces still require migration plans, and public pages avoid claiming that every URL, attachment, or processing path has identical controls.