PZU

K0NSULT x PZU

INSURANCE CLAIMS AUTOMATION DEMO
ENTERPRISE DEMO

Use Case: AI-Powered Insurance Claims Processing

Problem: PZU processes 500,000+ claims annually. Manual triage creates bottlenecks, inconsistent decisions, and compliance gaps in regulated insurance operations.

Solution: K0nsult deploys an AI agent network handling Intake, Classification, Decision, and Audit. Each claim flows through governed agents with human-in-loop escalation for complex cases.

87%
Auto-resolved
3.2s
Avg classification
100%
Audit coverage
14d
Deploy time

* Illustrative demo metrics based on simulated workflow. Actual results vary by implementation.

Workflow Pipeline

Step 01
INTAKE
Claim submitted via portal, email, or API
Step 02
CLASSIFY
AI categorizes: auto, health, property, life
Step 03
DECISION
Approve, reject, or escalate to adjuster
Step 04
AUDIT
Full trail: who decided, why, when

Live Dashboard — Simulated Claims

Claim IDTypeAmountStatusAgentTime
CLM-2026-00412Auto Collision12,400 PLNAPPROVEDK0-CLAIMS-013.1s
CLM-2026-00413Health — Surgery48,900 PLNESCALATEDK0-CLAIMS-021.8s
CLM-2026-00414Property — Flood87,200 PLNREVIEWK0-CLAIMS-034.5s
CLM-2026-00415Auto — Theft34,000 PLNAPPROVEDK0-CLAIMS-012.7s
CLM-2026-00416Life Insurance150,000 PLNPENDINGK0-CLAIMS-04

* Illustrative demo metrics based on simulated workflow. Actual results vary by implementation.

Demo Scenarios

LOW RISK

Simple Water Damage

Pipe burst in kitchen. Policy active, documentation complete, photos attached. Estimated damage 4,200 PLN.

Auto-approved → Payout initiated → Customer notified within 5 min
MEDIUM RISK

Vehicle Collision Claim

Two-car accident, police report filed. Estimated repair 18,500 PLN. Requires workshop estimate verification.

Human review → Documentation requested → Adjuster assigned → 48h SLA
HIGH RISK

Incomplete Fire Claim

Residential fire, 120,000 PLN claimed. Missing fire department report. Inconsistent damage description.

Escalated → Investigation required → Field adjuster dispatched → Fraud check

Why K0nsult

Governance-first execution — Every action passes through policy engine before execution. Block, warn, approve, escalate.

Human override at any stage — Operator can review, modify, or reject any AI decision. Full control, zero blind automation.

Complete audit trail — Every decision, every override, every timestamp. Exportable evidence pack per case.

Deployable in 7–14 days — Not a concept. Production-ready pilot with operator panel, audit logs, and governance rules.

Implementation Timeline

Day 1-2
Discovery & Data Mapping
Map PZU claim types, rules, SLA thresholds
Day 3-5
Agent Configuration
Configure intake, classification, and decision agents with PZU business logic
Day 6-8
Integration & Testing
Connect to PZU systems, run parallel processing, validate accuracy
Day 9-11
Audit & Compliance Setup
Configure audit trails, KNF compliance checks, GDPR data handling
Day 12-14
Go-Live & Monitoring
Production deployment with real-time dashboards and escalation flows

Deploy This for Your Team

Production-ready in 7-14 days. Not a concept — a working system with full audit trail.

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