The ProblemHow It WorksDemosRegulatoryAboutContact
The Enforcement Gap

AI agents act before
any check occurs.

Every governance tool reports after the fact. Regulators have named the gap. Vendors have disclaimed liability. The institution holds the exposure. GRACE was built for the moment before — the only moment that matters.

The Core Problem

The action comes first.
The check never comes.

Agentic AI systems make decisions and execute actions in milliseconds. Model alignment is probabilistic. Post-hoc review is retrospective. There is no standard mechanism to enforce authorization at the individual tool-call level before execution.

SR 26-2 · Footnote 3 · Verbatim · April 17, 2026

“Generative AI and agentic AI models are novel and rapidly evolving. As such, they are not within the scope of this guidance. Nonetheless, a banking organization’s risk management and governance practices should guide the determination of appropriate governance and controls for any tools, processes, or systems not covered in this document.”

Federal Reserve SR 26-2, April 17, 2026. Most relevant to banking organizations with over $30 billion in assets, with risk-based applicability to others.

Three Converging Liability Vectors

Regulatory: SR 26-2 excludes GenAI

Regulators expect examination evidence for systems that have no defined evidence standard.

Legal: courts place liability on the deployer

Vendor contracts cap indemnification at 12 months of fees — no relationship to potential regulatory fines.

Insurance: ISO GenAI exclusions active Jan 1, 2026

Carriers now specifically exclude generative and agentic AI incidents from standard coverage.

The Record Problem

When the examiner asks,
what does the institution produce?

A regulator requests the governance record for an AI-assisted decision. The institution goes to the AI vendor. The vendor provides its own log. That is not a defensible examination record.

You don’t own the record

Vendor audit trails are vendor property. An independent governance record must be institution-owned and institution-sealed.

Logs record. They don’t enforce.

Audit logs capture what happened. An examiner wants to see that a policy check occurred before the action — not a record of the action itself.

Which policy version governed it?

If your AI system cannot produce the policy version, authority level, and threshold state that governed each specific decision — sealed and tamper-evident — you cannot reconstruct the governance record.

What Existing Tools Miss

Every existing tool operates
on the wrong side of execution.

Tool CategoryWhat It DoesWhat It Does Not Do
Governance dashboardsReport on AI risk metrics over timeDo not intercept individual actions before execution
Model risk management toolsValidate traditional statistical models under SR 26-2SR 26-2 Footnote 3 explicitly excludes agentic AI from scope
Vendor audit logsRecord what the AI system did after executionVendor-owned. Cannot prove pre-execution policy check occurred
AI safety guardrailsFilter model outputs for content policyProbabilistic, operate inside the model, no cryptographic enforcement record
GRACEIntercepts every agentic AI action before execution. Evaluates against policy. Seals a cryptographically tamper-evident institution-owned record.Closes all four gaps simultaneously

See how GRACE closes each of these gaps.

The enforcement architecture, six states, and the Policy Action Packet.