Solutions · AI Governance

System inventory. Risk tiering. Framework crosswalks.

The complete AI governance surface — built on evidence, not documentation. Every policy enforceable at decision time. Every decision auditable to the specific framework obligation.

Most AI governance programs are documentation in search of enforcement. Veridra is enforcement in search of no more documentation than you actually need.

The gap governance programs run into

A typical enterprise AI governance program has three artifacts: a policy document, a risk register, and a set of model cards. These are necessary. They are not sufficient. When a regulator asks "did your systems follow your policy on this specific decision?", the policy document is an input to the question, not the answer. Veridra is the answer — the cryptographic evidence that a specific system, with a specific risk tier, applied the governance policies in force at the moment the decision was made.

The governance surface, end to end

System inventory with live classification

Every AI system in your enterprise registered with owner, purpose, risk tier, jurisdictional applicability, and the specific regulatory obligations that apply. Changes to any of these are tracked as signed diffs. The inventory is not a spreadsheet; it is a live artifact that becomes part of every decision record.

Risk tiering aligned to regulatory taxonomies

Systems are tiered using the EU AI Act categorization (prohibited / high-risk / limited / minimal) and your own custom schemas in parallel. A system in lending, employment, or critical infrastructure is automatically flagged as high-risk with the full Article 9/12/14/15 obligation set attached.

Framework crosswalks on every decision

A single signed decision record can be examined through multiple regulatory lenses. Which Article 9 risk-management obligations were satisfied? Which NIST AI RMF functions applied? Which SR 11-7 control area? The crosswalk data (in veridra-frameworks) is updated as regulations evolve; your evidence inherits the updates.

Policy-as-code with enforcement at decision time

Governance policies written in Rego, version-controlled in Git, and enforced at the signing gateway. The policy version in effect becomes part of the decision record. Policy changes are reviewed, approved, and themselves signed before taking effect — so the governance process around governance is itself evidenceable.

Why governance without enforcement fails
The enforcement gap is the audit gap
An AI governance policy that is not enforced at decision time creates a gap: the governance team believes one thing is happening; the production system is doing something else. This gap is where regulators find material weaknesses, and where class-action counsel finds fact patterns. Veridra closes the gap by making the policy executable at the signing layer — what you say you do is what you cryptographically prove you did.

Integration with existing programs

Veridra does not replace your existing governance program; it supplies the evidence layer your program lacks. Your model risk framework, your ethics review process, your incident response procedures — all continue unchanged, with Veridra becoming the substrate that makes them evidenceable. For organizations using ServiceNow, Archer, or similar GRC platforms, Veridra outputs flow into those systems as the authoritative evidence source.

The first 30 days
What a new governance integration actually looks like
Week 1: inventory your live AI systems; tier them against EU AI Act + SR 11-7 as applicable. Week 2: wrap the highest-risk system with the Python or Node SDK; first signed decisions flow. Week 3: your governance team generates the first framework crosswalk report. Week 4: first pack delivered to an internal auditor or external examiner for test. From there, the rest of the portfolio onboards on the same substrate.