EUCLID
AI-powered fraud & anomaly detection

A second set of eyes on every insurance lead you ingest.

AI-powered insurance lead fraud & anomaly detection. Euclid scores every inbound lead across three risk engines, surfaces the patterns that matter, and routes only what needs a human to your analysts.

Log inSee how it works
Savings delivered$1M+Saved for customers · to date
Monthly volume500K/moLead records processed · and growing
False-positive rate< 12%Industry average · ~30%
SOC2-oriented controlsHIPAA-oriented safeguardsBuilt for carriers, MGAs & TPAs
01 / pipeline

How a lead moves through Euclid

  1. 01

    CSV upload & layout detection

    Auto-maps unknown file formats via LLM.

  2. 02

    Validate & enrich

    Email + phone APIs · PII tokenized before prompts.

  3. 03

    3-engine risk scoring

    Identity · Fraud · Health — run in parallel.

  4. 04

    Composite score & tier

    Single 0–100 Euclid Score · Low / Med / High.

  5. 05

    Results, reports & analyst review

    Routed queues · audit trail · top-5 reasons.

See the platform in action
02 / scoring engines

Three engines, one Euclid Score

IR · Identity Riskw = 0.80

Synthetic identity detection

Fake PII, disposable contacts, duplicate identities, and product-eligibility mismatches across the inbound book.

Enriched · ZeroBounce, Abstract APIs
FS · Fraud Signalw = 0.20

Organized fraud patterns

Cross-lead phone/email reuse, agent submission velocity, and network-graph anomalies across your book.

Graph · 35 catalogue rules · 6 pattern families
HR · Health Riskw = 0.10

Comorbidity scoring

Age, BMI, smoker status, chronic conditions — weighted combinations flag eligibility risk and inflated-risk leads.

Clinical · weighted comorbidity matrix
Composite Score Formula
IRC = 0.8 × IR + 0.2 × FS
Euclid Score = 0.9 × IRC + 0.1 × HR
  • Low< 35
  • Medium35 – 64
  • High≥ 65

Every lead receives a single, explainable 0–100 Euclid Score and a Low, Medium, or High tier — built from consistent signals, not guesswork.

03 / human + machine

AI orchestration meets analyst judgement

AI assistance · powered by Theo

LLM-assisted intake and explanations

Euclid uses an LLM assistant, Theo, to detect the layout of unfamiliar CSV formats, generate plain-English risk explanations for each lead, and answer natural-language questions over your scored book.

  • Layout detection
  • Risk explanations
  • NL Q&A

Manual review

Analyst queues

High-risk and borderline leads are routed to analyst queues. Human review is the final gate — Euclid surfaces the top 5 weighted risk reasons per lead to accelerate triage.

  • Top-5 reasons
  • Audit trail
  • Override & feedback
04 / market

Why now

Insurance fraud detection market

$7.2B (2025) $20.2B by 2031 · 19% CAGR

ML deployment among global insurers

62% in 2025 · and rising

Security & compliance
  • Immutable audit logging
  • Organization-level data isolation
  • Secure, role-based authentication
“Euclid gave us one consistent view of risk across every lead we process.”

Placeholder attribution — Fraud Operations Lead

See Euclid on your own data

Log in to upload a lead file and get a scored, explainable risk report.

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