Skip to content
shadowiq
Use case · Model risk management (MRM)

Model risk management, evidence-first.

A registry is only useful if it's always current. ShadowIQ's model registry generates itself from discovery, keeps lineage alive, and signs every change — so your MRM committee gets a register they can trust.

What this is

Summary

ShadowIQ model risk management (MRM) combines an auto-populated model and agent registry with continuous evaluation, lineage tracking, DPIAs, and cryptographically signed change records — aligned to SR 11-7, EU AI Act Article 17, and ISO 42001.

How it fits · explainer

The before / after, in one picture.

PROBLEM · BEFORE SHADOWIQ
Model registry that's always out of date because it depends on people to update it.
siqSOLUTION · WITH SHADOWIQ
Discovery feeds the registry. Every deploy, fine-tune, and routing change is captured automatically — and signed.
PILLARS ENGAGEDDiscoverEvaluateEvidence
Where it hurts

You've heard this one before.

  • Model registry that's always out of date because it depends on people to update it.
  • No clear lineage from a generative feature back to its training data.
  • Committee reviews based on slide decks, not live data.
  • 'Which model is currently in production' is a surprisingly hard question to answer.
What we do about it

Three moves.

  1. 1
    Registry that writes itself.

    Discovery feeds the registry. Every deploy, fine-tune, and routing change is captured automatically — and signed.

  2. 2
    Lineage from data to decision.

    Training sets, evaluation runs, policy versions, and production traffic all chained. Answer 'what touched customer X's data' in seconds.

  3. 3
    Committee-ready reports.

    Model cards, DPIAs, and risk scorecards generate on demand and carry their own cryptographic receipts.

Outcomes

Numbers, not adjectives.

100%
live model coverage
< 15 min
model card generation
O(log n)
evidence lookup time
Frequently asked

Asked, answered, sourced.

SR 11-7 components (model development, implementation, use, validation, governance) each map to ShadowIQ artifacts: registry, evaluations, gateway decisions, challenger tests, and signed audit trails.

Yes. Register a challenger, run it in shadow mode alongside the incumbent, compare eval scores, policy-hit rates, and user-impact metrics. Promote when evidence says so.

Model cards follow the Mitchell et al. format with extensions for EU AI Act Article 13 (transparency) and ISO 42001 clauses. OSCAL export available.

Ready to see the signet in motion?

Your 30-minute demo. A signed audit trail by the end of it.

We'll wire ShadowIQ into one live workload, block a prompt injection in real time, and hand you a cryptographic receipt — before the meeting ends.