Regulated AI

Provide evidence for embedding-backed decisions.

When an examiner, a regulator, or a plaintiff asks for evidence about the embeddings behind a decision, logs are reconstructed after the fact. Mnemo registers each embedding in the decision pipeline when it is generated, and later checks whether a presented vector resolves to that registration.

01Where it applies

The vector-first filter.

If your decision pipeline uses embeddings (document intelligence, copilot decisions, RAG-based reasoning, embedding-based risk scoring) and that decision is subject to regulatory review, Mnemo applies.

02Why it matters

Decisions should include evidence.

ValidMind, ModelOp, and Modelscape handle lifecycle. The gap is evidence at the embedding layer.
03What this does

Each embedding under a decision has a registered vector_uid.

Every embedding used in a regulated decision carries a vector_uid registered in your tenant at embed time, alongside the model_id label your pipeline declared. verify() confirms a presented vector resolves to that registered vector_uid in your tenant. Mnemo does not attest which model produced a vector or a decision.

04Scope

What Mnemo does not do.

Does not replace your system
Does not interpret regulation for you
Does not detect fraud on its own
Does not produce model documentation

Mnemo focuses on one layer: attaching identity to embeddings and verifying them when they are used.

Mnemo Verify checks whether a submitted vector resolves to an object registered to the caller's Mnemo account or namespace. verified=false is a safe outcome, not an error, and not proof that a vector is foreign. Verify does not establish the truth, authorship or ownership of the content behind a vector.

05Who this is for

Head of Model Risk. Head of AI Platform reporting to CRO. CCO. CISO at regulated entities. General Counsel for malpractice-adjacent legal tech.

06Why teams adopt it
  • Model risk teams asking for evidence at the embedding layer.

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