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What is Total Loss Pro?

The auto insurance industry has seen a troubling 20 percent increase in total loss claims, particularly concerning collision and liability losses. Many insurers continue to face challenges with fragmented total loss operations, leading to elevated costs, dissatisfied customers, and a lack of effective oversight. Enter Total Loss Proâ„¢ from Vemark: this cutting-edge solution aims to transform the often burdensome total loss claims process into a more efficient and adaptable system that can keep pace with rapid changes in the industry. By utilizing this platform, insurers can expedite settlements, subsequently improving policyholder satisfaction. Moreover, it enhances employee morale by alleviating the frustrations that arise from outdated processes. The platform also promotes greater visibility and transparency, enabling informed, data-driven decision-making. Given the intricate nature of total loss auto claims in contrast to standard repair claims, Total Loss Pro acts as a cloud-based tool that streamlines every phase of the complex salvage vehicle process, ultimately benefiting both insurers and their clients. Additionally, by adopting this all-encompassing solution, insurance carriers can embrace a more proactive claims management approach, ensuring a seamless experience for everyone involved while also positioning themselves for future challenges.

What is MarvelX AI?

Insurance claims are the flagship use case for MarvelX, an agentic AI company serving financial services and highly regulated industries. Its AI claims agents run autonomous claims processing end to end: a claim arrives as a first notice of loss (FNOL), gets its policy validated, is adjudicated, and moves to settlement, so work that took days is finished in under an hour. The buyer list spans P&C, motor, travel, health, life, and embedded insurers plus MGAs and TPAs. Edge cases are escalated to human reviewers rather than forced through, a human stays in the loop on every decision, and the output is audit-ready. There is also a standalone option, AI document data extraction for insurance, for teams that want structured fields from documents (each carrying a source reference) without automated decisioning. MarvelX is extending this agent architecture into other regulated workflows, including KYC/KYB verification for notarial services, and connects to the systems teams already use: HubSpot plus the Dutch registries KVK, RDW, and SchadeGarant.

Media

Media

Integrations Supported

HubSpot CRM

Integrations Supported

HubSpot CRM

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Price on request
Pricing is scoped to claim volume and workflows deployed. Get in touch for a quote.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Vemark

Company Location

United States

Company Website

vemark.com/totallosspro/

Company Facts

Organization Name

MarvelX.ai

Date Founded

2025

Company Location

Netherlands

Company Website

www.marvelx.ai

Categories and Features

Claims Processing

Adjustor Management
Case Management
Claim Resolution Tracking
Co-Pay & Deductible Tracking
Compliance Management
Customer Management
Electronic Claims
Forms Management
Paper-Based Claims
Payor Management
Policy Administration

Categories and Features

Claims Processing

Adjustor Management
Case Management
Claim Resolution Tracking
Co-Pay & Deductible Tracking
Compliance Management
Customer Management
Electronic Claims
Forms Management
Paper-Based Claims
Payor Management
Policy Administration

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