The Underwriting & Audit Decision Platform
NewNow available on MCP
Home
Data Solutions
LRO — Lessor’s Risk Classification Risk Intelligence
Agentic AI
GIA Lite — Appetite ARKUS — Risk Insight GIA — Eligibility CHRIS — Premium Audit
Data Foundation
The Data Foundation
Explore
Solutions Overview Technology Insurance Sector
About us
Our company Team Journey
Resources
Articles Resource center
AI Assistants
ARKUSRisk Discovery & Intelligence

Self-service risk discovery.

ARKUS searches for deeper risk-discovery insights — operating hours, alcohol service and other contextual factors that enrich underwriting and sharpen every decision.

Precision, speed & compliance

Meet ARKUS — agentic AI for risk analysis.

ARKUS automatically identifies risk signals by business class, analyzes exposures and flags potential risks for submissions and renewals in real time — then continuously learns from every evaluation.

  • Intelligent, context-aware insights for comprehensive evaluation

  • Automatically identifies risk signals by business class

  • Analyzes exposures and flags potential risks in real time

  • Transparent risk and exposure data for trustworthy decisions

  • Integrates effortlessly, preserving data integrity, security and continuity

Risk Signals · Discovered
HR
Operating hoursOpen 24/7 — overnight exposure
0.94Elevated
AL
Alcohol serviceOn-premise liquor license found
0.89Review
CK
Commercial cookingFryer on site — matches class
0.97In appetite
FT
Foot trafficHigh-volume retail footfall
0.82Noted
ARKUS insight4 signals surfaced with confidence and source, ready to underwrite.
Understanding ARKUS

Two jobs. One risk engine.

ARKUS answers specific underwriting risk questions — "does this business handle hazardous materials?", "is this business involved in food preparation?" — consistently and at scale, and it can be taught brand-new risk questions from just a handful of real examples. Every question is scoped by client, segment and risk ID, and its answer logic lives as reusable, versioned skills.

  • Answers risk questions, consistently.

    Given a business, ARKUS resolves the right skills for that client + segment + risk ID and answers using them as context, so the same question is evaluated the same way every time.

  • Learns new risk questions from examples, not code.

    A subject-matter expert supplies a few real yes / no snippets plus the question and its intent — ARKUS generates the detection logic itself, live-streaming its reasoning. No rule-writing, no engineering cycle.

  • Answer logic lives as versioned skills.

    Each risk question is backed by reusable skills that are scoped, history-tracked and promoted like software — one consistent way of answering "does this business do X".

Ask ARKUS a risk question
Q
Risk question"Does this business do commercial cooking?"
Scoped
A
AnswerYes — fryer & grill detected on site
Confident
SK
Skills usedactivity-verification + intent-aware
AU
Audit traillogged with source & skill version
Traced
ARKUSSame question, same answer, every time, at any volume.
Train, don’t code

Teach a new risk question in examples, not code.

ARKUS’s core differentiator: an underwriting expert hands it a few real examples, and it writes, tests and ships the detection logic itself — with the rigor of a software release, not a spreadsheet edit.

  • Start from about five real examples.

    A handful of genuine yes / no snippets, the risk question, and its intent: that is the entire input a subject-matter expert needs to provide.

  • It multiplies them into a robust training set.

    From those few examples ARKUS generates far larger sets of synthetic yes, no, and "contextual no" examples, so the model generalizes instead of memorizing.

  • It self-checks and self-repairs.

    Deterministic policy checks catch malformed or ambiguous logic; ARKUS sends itself targeted fixes (up to two automatic passes) before anything reaches the external validator.

  • It reinforces what it just learned.

    The moment a model is generated, ARKUS auto-composes two supporting skills (an activity-verification check and an intent-aware check), so the new question is immediately more robust.

  • It promotes like software.

    Every trained skill moves through a controlled DEV → QA → PROD pipeline with generated diffs between environments — full review and auditability.

Training pipeline · versioned
1
Examples + question + intent~5 real yes / no snippets
Input
2
Generate detection modelreasoning streamed live
AI
3
Policy check + self-repairup to two automatic passes
Vetted
4
External validationindependent rule check
Valid
5
Promote DEV → QA → PRODwith generated diffs
Shipped
AUDITEDEvery generation, validation & promotion is versioned and history-tracked.
Unmatched results

Augments underwriting workflows.

Enhanced accuracy

Sharper risk classification and insight precision, minimizing premium leakage and optimizing pricing.

Operational efficiency

Cut manual effort and processing time, freeing underwriters for high-value work.

Regulatory agility

Stay ahead of evolving compliance standards with AI-powered updates.

ARKUS workflow

From signal to decision.

1

Identify signals

ARKUS surfaces risk signals by business class to prepare the file for underwriting.

2

Analyze exposures

Exposures are analyzed and potential risks flagged for submissions and renewals.

3

Enable the decision

Prioritized, explainable insights are handed to the underwriter, with sources.

Why it matters

Judgment calls become consistent answers.

  • Consistent, automated answers: risk questions that used to need a person to read and interpret get answered the same way every time, at any volume.

  • Underwriting experts train the AI directly — a new risk question takes a handful of examples, not a development cycle, shortening "we need to check for X" to "the system checks for X".

  • Nothing goes live untested — layered validation (policy checks, self-repair, external validation) vets every new question from multiple angles before it touches a real submission.

  • Auditable, not silent — every generation, validation and promotion is versioned, and question edits are flagged as material or cosmetic so leadership always knows what changed.

  • Powers the risk layer under GIA — the same skill engine feeds the per-product reasoning inside GIA, so "does this business do X" is answered one consistent way across the platform.

Governance & trust
ED
Every edit classifiedmaterial vs cosmetic
Versioned
PR
Controlled promotionDEV → QA → PROD with diffs
Reviewed
HX
Full history logevery skill change tracked
Auditable
ARKUSConfiguration changes get the rigor of a code deployment.
Why it matters

Misclassification is a quiet, compounding source of premium leakage and appetite error.

4 code sets
NAICS, SIC, workers' comp and ISO GL, resolved and cross-walked in one pass
Both vintages
2017 and 2022 NAICS at 2-, 6- and 8-digit depth, side by side
Every code scored
A calibrated confidence and reasoning trail on each classification

See ARKUS on your own submissions.

Bring a live submission. ARKUS will surface the risk signals and show its sources.

Request an ARKUS demo