Case Study · Augmantis for DART Warranty Group

AI Claim Creator Agent

Conversationally capturing warranty claims, validating policy eligibility in real time, and automatically creating structured claim records; eliminating manual data entry while ensuring complete, accurate, and policy-compliant claim submissions.

claim-intake-session.log
Hi! I can help you file a warranty claim.
What's your vehicle's VIN?
1FTFW1E5XLKE12345
Got it — verified. What issue are you experiencing?
Transmission —
3rd gear slip
Understood. Filing your claim…
✓ CLAIM RECORD CREATED
claim_id DWG-88213
vin 1FTFW1E5XLKE12345
issue Transmission – gear slip
status verified
filed_in 2m 14s

Client

DART Warranty Group

Built By

Augmantis

Industry

Auto Warranty / TPA

Solution Type

AI Claim Adjudication Agent
Executive Summary

Intelligent AI-Powered
Claim Creation

The warranty and insurance companies often get FNOL submissions through long and cumbersome forms which annoy customers and result in missing, erroneous, and inconsistent data. Missing car details, faulty VIN numbers, invalid miles, and data entry are common issues which result in inefficiency in the claims process.

To address such problems, Augmantis, backed by eComStreet, developed the AI Claim Creator Agent which turns conventional claims intake into a smart conversation-based process. The AI takes care of the conversation with the customer, validates each and every response provided by the customer, checks if the warranty is still valid, and creates enterprise claim records out of the conversation automatically.

🤖

Conversational Intake

Automates claim entry through an AI-enabled conversational interface that facilitates claims submission through conversations between customers and the repair shop using natural language processing technology.

🔍

Real-Time Authentication

Validates the identity of the customer and confirms their eligibility for warranty services based on live policy data from the enterprise’s database systems.

🛡️

Dynamic Data Validation

Continuously validates customer inputs using deterministic business rules to verify VINs, odometer readings, dates, and required fields before data enters enterprise claims systems.

☁️

Automated Record Generation

Automatically converts validated conversations into structured, enterprise-ready claim records aligned with backend database schemas, eliminating manual data entry and accelerating downstream claim processing.

The Problem

Building Reliable Conversational Claim Intake Through
Deterministic AI

Enterprise claim creation demands far more than conversational AI. Every customer response must be validated, policy eligibility must be confirmed, and claim records must comply with enterprise data standards before entering downstream claims workflows.

Challenge 01

Preventing Invalid Data from Entering Enterprise Systems

The Obstacle

Traditional conversational chatbots primarily focus on understanding user intent but often accept incomplete, incorrectly formatted, or logically inconsistent information. Invalid VINs, inaccurate odometer readings, improperly formatted dates, and ambiguous customer responses frequently create poor-quality claim records that require manual correction before processing can begin.

The Innovation

Augmantis engineered a Stateful Validation-First Architecture that combines conversational AI with deterministic backend validation. Instead of immediately storing customer responses, every interaction passes through Python-driven validation logic that evaluates:

  • VIN length and formatting
  • Numerical conversion for mileage
  • Date validation
  • Required field completion
  • Enterprise business rules
If invalid information is detected, the AI pauses the conversation, clearly explains the issue, and guides the customer toward the correct input before allowing the workflow to continue. This approach ensures only validated, enterprise-ready information enters downstream claims systems.

Challenge 02

Verifying Coverage Without Complex Authentication

The Obstacle

Customers expect a frictionless claims experience, yet insurers must ensure only eligible contract holders can initiate warranty claims. Traditional authentication methods introduce unnecessary friction while increasing abandonment rates.

The Innovation

The AI Claim Creator Agent incorporates an Automated Live Policy Verification Gateway. Using only the customer's Last Name and Vehicle Identification Number (VIN), the platform securely queries enterprise policy databases in real time. If an active contract exists, the AI:

  • Authenticates eligibility
  • Retrieves customer information
  • Pre-populates vehicle details
  • Personalizes the conversation
  • Continues claim creation
If no valid contract is found, the conversation ends securely before unnecessary processing or database records are created. This intelligent gatekeeping reduces fraudulent claim attempts while significantly improving customer experience.

The Solution

Intelligent AI-Powered
Claim Creation

The AI Claim Creator Agent combines conversational AI, deterministic validation, live policy verification, and enterprise workflow automation to create complete, accurate, and policy-compliant warranty claims without manual data entry.

Layer
01
AI & Agentic Workflows

Conversational Claim Intake & Guided AI Interaction

The AI Claim Creator Agent eliminates conventional web forms for claims and integrates a smart conversational flow that leverages Amazon Bedrock Foundation Models. Instead of having users fill out long forms, the AI intelligently converses with the customer or the repair facility and gathers all the information required to create a claim, using previous answers to inform subsequent questions.

Amazon Bedrock Conversational AI Agentic Workflows Natural Language Understanding
Layer
02
Retrieval Architecture

Real-Time Contract Authentication & Coverage Validation l

Prior to claim creation, AI first validates customer eligibility by matching the claimant's Last Name and Vehicle Identification Number (VIN) with live databases of enterprise policies. If an active policy is found, it is instantly authenticated, enabling customer and vehicle details to be filled in automatically within the chat session. This ensures that any invalid or non-active policy cannot create a fraudulent claim.

Live Policy APIs VIN Validation Coverage Verification Enterprise Integration
Layer
03
Document Intelligence

Intelligent Data Validation & Auto-Correction

The system utilizes a deterministic validator that continually checks each customer input prior to progressing further in the dialogue process. The business rules for validation in Python validate the VIN number format, check for the correct number of digits in the form of 17, transforms natural language values into structured data, ensures logical odometer numbers, and ensures field requirements are met.

Python Validation Business Rules Engine Real-Time Validation Data Quality Assurance
Layer
04
Data & Storage

Automated Schema Mapping & Claim Record Creation

After the validation of customer data, the AI will be able to generate structured enterprise claims out of natural language dialogue. The symptoms, the description provided by the customer, as well as all other relevant information, is logically structured into pre-defined back end databases, allowing for claims to be created in a standardized manner.

Schema Mapping Structured Data Claims Database Enterprise Automation
Security & Governance

Enterprise-Grade AI
Infrastructure

The AI Claim Creator Agent is built on a secure, cloud-native architecture capable of supporting high-volume conversational claim intake across enterprise warranty and insurance environments.

🔒Amazon Bedrock Foundation Models

Enterprise-grade foundation models understand customer conversations, interpret natural language, and generate structured responses throughout the claims intake workflow.

  • Natural language understanding
  • Context-aware conversations
  • Enterprise AI reasoning
  • Intelligent response generation

🛡️ Agentic AI Workflows

Agentic AI coordinates backend services, executes validation logic, invokes enterprise APIs, and manages conversational workflows autonomously.

  • Autonomous orchestration
  • Intelligent tool calling
  • Workflow automation
  • Enterprise integrations

📋 Stateful Validation Engine

Python-based deterministic validation continuously verifies customer inputs before allowing the conversation to progress.

  • VIN validation
  • Mileage verification
  • Date validation
  • Business rule enforcement

⚙️ Enterprise API Integration

Secure APIs connect conversational workflows with warranty management systems, policy databases, CRM platforms, and enterprise claims software.

  • Policy lookup
  • Customer retrieval
  • Vehicle information
  • Claim creation APIs
Business Impact

Enterprise Impact of Intelligent Claim Creation

Complex form-filling and manual intake were replaced with a seamless, 24/7 conversational experience.

75%+

Reduction in Intake Time

In a fraction of the time compared to typical web forms, conversational AI collects necessary data and automatically generates structured claim records while guiding users in an intelligible manner.

~98%

Initial Data Accuracy

Stateful, dynamic validation logic intercepts and corrects invalid user inputs (e.g., VINs, dates, odometers) in real-time before database ingestion.

0

Manual Data Entry Hours

The AI parser completely eliminates the need for intake staff to manually transcribe or re-format customer problem descriptions into the core database.

Eliminates incomplete and inaccurate claim submissions through deterministic real-time validation.

Automatically verifies active warranty coverage before claim creation, reducing fraudulent or ineligible claim requests.

Generates structured enterprise-ready claim records without manual data entry or administrative intervention.

Accelerates First Notice of Loss (FNOL) processing while reducing claim intake time from several minutes to only a guided conversation.

Improves downstream claims automation by ensuring every claim begins with complete, validated, and policy-compliant information.

Reduces operational costs by minimizing manual data correction and administrative processing.

Technology Stack

Built On Production-Grade AWS

Every component chosen for enterprise reliability, security, and cost efficiency.

Amazon Bedrock
Bedrock Knowledge Bases
Amazon S3 Vectors
Bedrock Converse API
Bedrock Guardrails
AWS Lambda
Amazon EventBridge
Lambda Function URLs
AWS IAM
MongoDB Atlas
BSON Decimal128
Hybrid-RAG
Multimodal Foundation Models
Agentic Tool Calling
Native FM Parsing
Hierarchical Chunking
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