Modern underwriting. Your models and data never leave your walls.
The same intelligence your competitors are adopting — deployed on infrastructure you control, grounded in your own claims and loss history, and fully cited. Your proprietary models and risk data stay inside your walls, always.
Nine lives. Zero leaks. Proprietary models protected by architecture, not by promise.
Every claim you feed a public AI risks your proprietary models.
Your risk data, loss runs, and book of business are proprietary — and your models are the edge. Public AI exposes both to third-party processing that sits outside any audit.
Where does it show up? In the everyday rush — claims and underwriting data pasted for speed. The data leaves your walls — and an audit is what shows where.
1Model exposure
Your proprietary underwriting models leak into a public tool.
2Claims-data leakage
Claims and loss runs in a public tool are a reportable breach.
3Regulatory risk
State regulators expect documented safeguards on consumer data.
4Lost edge
The carriers that win use AI safely on their own history.
Four capabilities. Your data. Your walls.
Private Retrieval (RAG)
“Ask questions of our own documents.” Cited answers across your entire corpus — without a byte leaving your control.
Document Intelligence
OCR and extraction turn claims, loss runs, and policies into a searchable, cited database.
Grounded Drafting
Reports, reserves memos, and client communications drafted from your templates — with citations, not hallucination.
Workflow & Compliance
Reserve, coverage, and audit-trail flags surfaced automatically — grounded in your data.
Where it applies, claim by claim.
The same private engine, pointed at the work your firm actually does.
Claim & loss-run search
Cited search across claims, loss runs, and prior settlements.
Risk & policy review
Anomaly and coverage flags surfaced from your data.
Reserve & model support
Cited analysis grounded in your loss history.
Regulatory readiness
Documented, audit-ready controls for your reviewers.
Policy & procedure review
Cited search across carrier policies and procedures.
Treaty & cedant data
Confidential processing of treaty and cedant records.
Not waivers — an architectural answer.
State Insurance Regs
Consumer-data safeguards upheld by design, never by a policy promise.
NAIC
Model and data-governance expectations met by architecture.
GLBA
Nonpublic personal information protected by design.
Data Privacy Laws
Aligned with evolving state privacy rules.
A disciplined, named framework — not a scramble.
Assess
Audit current exposure, map your data, and define your target state.
Deploy
Stand up hardened, self-hosted open-source models sized to your workload.
Manage
Ongoing updates, monitoring, and security — so it stays current and defensible.
Train
Make your people fluent, safe users — competence becomes a firm capability.
Straight answers for your partners.
Can we use AI on claims and underwriting data at all?
Is this just a server running ChatGPT?
How does this protect our proprietary models?
What do our auditors and regulators see?
Do we need to change everything at once?
Who runs the system day to day?
Your data never leaves your walls. Ever.
Open-source models running on your own infrastructure — no upload, no third-party terms, no unverifiable promise. Just an auditable system you control.
- Self-hosted. Open-source weights running on hardware you own or lease.
- Fully audit-ready. Documented stack and configuration for your reviewers.
- Wholly sovereign. No third-party data processing on proprietary risk data.
- Independently verifiable. Security you can prove, not a promise you must trust.
Five minutes. Zero risk. See exactly what your firm is exposing right now.
Start with the Confidential Privilege Audit — we’ll show you where you stand before you commit to anything. You own the read, with or without us.
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