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For risk carriers

Underwrite AI labour. Price the risk you're already on the hook for.

Every E&O, D&O, and cyber policy now indirectly covers AI-enabled work. Nobody is pricing the correlated failure modes. We give carriers, reinsurers, and PE diligence teams a reproducible RiskBundle — the same evidence SeaOtter delivers to the rated enterprise, reframed for the balance sheet that absorbs the loss.

Request a sample RiskBundle →

Why this page exists

The rated enterprise has an incentive to game its own score. You don't — you want the bad news, and you want it first. That is why the risk-carrier view is a separate surface with separate deliverables.

The underwriter's problem is not 'is this firm good at AI?'. It is 'how correlated are their AI failure modes with everyone else I insure, and what is the tail?' That is a portfolio question the rated firm cannot answer about itself.

What we measure

Five metrics, per workflow, refreshed on a cadence you set. Plain-English definitions; full methodology under NDA.

Correlation exposure

How concentrated the insured is on any one model provider, fine-tune, or vendor stack. High values mean a single outage cascades across insureds you share.

Cascade topology

Dependency depth and fan-out of AI-mediated steps. Tells you how far a silent-failure propagates before a human catches it.

Degradation surface

The set of input distributions where model quality quietly drops below the human floor. Maps your largest unpriced loss mode.

Tail loss estimate

P95 and P99 dollar loss under a named scenario (model outage, upstream data poisoning, regulator halt). Not a headline number — an auditable simulation.

Control adequacy

Residual risk after the insured's own controls (human-in-the-loop, canarying, roll-back, vendor diversity). Drives premium credits.

Sample RiskBundle

Hypothetical Fortune-500 ML team. Numbers are illustrative — real bundles are delivered under NDA.

Sample output
Subject
Mid-market insurer, applied-ML underwriting team
Workflow
Portfolio rebalancing (weekly)
  • Correlation exposure0.78Single frontier-model provider; shared with 61% of peer portfolio.
  • Cascade depth4Four AI-mediated steps before a human reviewer sees output.
  • Degradation surface11% of inputsOut-of-distribution regions where accuracy drops below manual baseline.
  • P99 tail loss$2.4MUnder scenario 'model_outage_7d' with existing controls.
  • Control adequacyB−Canarying partial; rollback tested quarterly; no vendor-diversity plan.

Underwriter recommendation

Price with a 12% loading against peer-median; eligible for 4% credit on proof of second-provider fallback within 90 days.

Illustrative only. Live RiskBundles include methodology appendix, scenario definitions, and a reproducible scoring harness.

Pilot offers

Three entry points, matched to the buyer inside your firm who is already on the hook.

Single-tenant scan

$50K

One insured, one workflow, one report. NDA. 2-week turnaround.

  • ✓Full RiskBundle on a single insured
  • ✓Methodology appendix and scenario library
  • ✓Debrief with your underwriting team
  • ✓Credits against an Underwriting Feed if you upgrade
Request details →

Underwriting feed

$250K/yr

Ongoing risk feed for one carrier across all AI-exposed insureds. Monthly refresh.

  • ✓Monthly RiskBundle per insured in scope
  • ✓Portfolio-level correlation + concentration dashboards
  • ✓Early-warning alerts on provider-level events
  • ✓Carrier-only briefings with the methodology team
Request details →

Catastrophe model

Custom

For reinsurers and large PE diligence teams. The Verisk/RMS analogue for AI-labour risk.

  • ✓Industry-wide cascade simulations
  • ✓Scenario co-development with your actuarial team
  • ✓Federated contribution from participating carriers
  • ✓Board-level disclosure artifact
Request details →

Get a sample RiskBundle

Redacted sample of the bundle shown above, delivered within one business day. No sales call required.

We never share your name or firm. No sales sequence — one email with the sample, then nothing unless you reply.

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