Grace Hill — CTO Outreach + Baseline Scope

To: Chris Fontan, CTO, Grace Hill (the technical counterpart) · cc the warm intro path From: Richard (founder) · Re: a 45-minute AI-governance working session

The message (founder → CTO, warm, honest — paste-ready)

Chris —

Congrats on the AI push — Gracie, Intelligence+, the PerformanceHQ insights layer. You're moving fast in exactly the right direction, and you're doing it in the one industry where AI governance isn't optional: fair housing.

That's why I wanted to reach out directly. HUD's 2024 guidance put AI used in housing-related functions squarely under the Fair Housing Act — and it reaches the technology provider, not just the operator. Gracie answers fair-housing and compliance questions today. That's a strength worth protecting with a little governance scaffolding around it — model disclosure, a human-in-the-loop on the consequential answers, a documented basis. Not a rebuild; documentation and a couple of controls.

We built govrn for exactly this: a baseline that inventories every AI feature, scores it across three lenses (tech, security, and AI-specifically), and hands you a prioritized, defensible path — the kind of thing your board and Aurora will want to see as the AI strategy scales toward an exit.

I'd love 45 minutes. I'll come with a Grace-Hill-specific mirror already built from your public footprint — so it's a working session, not a pitch. If it's useful, we scope a fixed-fee baseline from there.

Worth a look?

— Richard

Notes for Richard:

  • The line that gets it forwarded to their General Counsel: fair-housing + "reaches the technology provider." Keep it.
  • Frame as honest control-gap, never "your AI is biased." That's a lawsuit-bait sentence and it's not what we found.
  • The Aurora / exit-readiness angle is real leverage with a PE-owned company — governance posture is diligence-relevant.

The ask

A 45-minute paid-baseline working session (or free intro → paid baseline). On the call: confirm how many AI features/models are in production and what data each touches. That number sets the baseline scope.

Baseline scope (what we'd propose after the call)

govrn AI Inventory & Risk Baseline — Grace Hill

  • Deliverables: complete AI-BOM (every feature + data access + owner); three-lens posture scored against their evidence; the fair-housing control review (the hero); prioritized remediation path; an independent attestation (firewalled); a board/PE-ready one-pager.
  • Hero focus: Gracie fair-housing oversight + model disclosure; resident-data secondary-use; shadow-AI sweep.
  • Effort / fee: ~$15–30K, 3–4 weeks, human-led (the platform/monitoring is a separate follow-on retainer — we don't lead with it).
  • Explicitly not: a bias verdict, a rebuild, or "live monitoring" we haven't connected. We mark what's real.

Follow-on (the annuity, later)

Once the baseline lands: the living platform — connect the controls to continuous monitoring, re-score as their AI ships, standing posture report for the board. Monthly/yearly. That's where govrn becomes recurring — but it's step two, earned by a clean baseline.

GC test

Every line in the readout, the demo, and this outreach cites a named authority (HUD, NIST, ISO) or is marked a control-gap-to-confirm. If their General Counsel reads it, nothing should make them wince. That's the bar.