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The three revenue streams

This is where all the study material pays off: how a producer license becomes “Glacis with underwriting capability.” Grounded in the Glacis one-pager and the Law360 article (Heidi Lawson). GROUNDED · Glacis GROUNDED · Law360

The strategy has evolved. Volume 2 rewrites stream 2: Glacis no longer aims to hold the book — a syndicate writes the paper, Glacis stays the independent evidence layer. See the independence thesis.

Glacis is “The Evidence Layer for AI” — cryptographic attestation of governed AI decisions, zero data egress (only hashes cross the trust boundary; it runs in the customer’s environment), declarative policy enforcement at runtime, and native mapping to frameworks (NIST AI RMF, ISO 42001, EU AI Act, HIPAA, SOC 2, Colorado AI Act). GROUNDED · Glacis

A producer license is the legal on-ramp that converts that capability into underwriting — the ability to sell and price risk, not just sell software.

# Stream What Glacis sells Who pays License/capability prerequisite
1 Underwriting (SaaS) The evidence layer to insurers/MGAs so their AI underwriting/claims emit audit-grade, attested evidence (satisfying the NAIC AI Model Bulletin + Evaluation Tool). Insurers / MGAs None (it’s software) — but the regulatory tailwind drives demand.
2 Producer / MGA A Tech E&O policy for healthcare AI, sold + underwritten on a carrier’s paper via Glacis software, for commission + profit share. Healthcare-AI vendors (insureds), via the carrier This is what licensing unlocks: producer license → entity license (DRLP) → appointment → delegated authority.
3 TPA Claims error-source attribution (which model/decision caused a loss) → claim-adjusting revenue. Insurers / self-insured plans Separate TPA/adjuster authorization (VERIFY per state).

GROUNDED · Glacis GROUNDED · Law360

How each stream maps to the regulatory hot zones

Section titled “How each stream maps to the regulatory hot zones”

Every stream sits inside the highest-scrutiny zone identified in the Law360 article — which is exactly why governance-as-a-feature is the differentiator: GROUNDED · Law360

  • Underwriting SaaS → the AI Systems Evaluation Tool checklist becomes a product-requirements spec (governance, model inventory, bias testing, documentation). See 01 evaluation tool.
  • Producer / MGAhealthcare is the highest-AI-adoption (92%) and highest-claims-litigation line (Cigna), so a healthcare-AI MGA must be governance-native. See 07 Tech E&O for healthcare AI.
  • TPA → claims AI is the hottest litigation zone (State Farm, Cigna); attribution maps directly to explainability/documentation demands. See 02 AI claims litigation.
  • Cross-cutting: Glacis-as-software-vendor is itself a “third party” under the NAIC’s broad definition — a future-licensing threat and a moat (Glacis already produces the documentation regulators will demand). See 01 third-party WG.

Streams 1 and 3 can run on software/TPA authority, but stream 2 — the MGA — is the one that turns Glacis into an underwriter, and it is gated entirely on licensing. That’s why this whole academy exists: licensing is Step 1 of the on-ramp. The full sequence is on the next pages.

Glacis’s own discipline — bind every claim to what is actually governed/mediated, no overclaim — is the same rule this academy runs on: teach stable concepts, cite the docs, and never fabricate a volatile number. The product and the study aid share a spine. GROUNDED · Glacis

01 The flywheel

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