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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Our platform utilizes AI to transform and enhance your core risk data, linking your properties while improving the data in your submissions for optimal insurance results driven by resilience-focused ROI. Archipelago simplifies the management of property data, earning the trust of risk managers, brokers, and insurers for proactive commercial property risk management. It is specifically created to accommodate the diverse range of buildings found in any portfolio, facilitating connections among all stakeholders in the property insurance sector for improved results. The traditional collaboration methods among risk managers, insurers, and brokers to safeguard properties and handle risk are often cumbersome and outdated. Transition to a platform that is designed to unify, streamline, and automate the property placement process for the best possible outcomes. By sourcing and translating real estate data along with thousands of documents into insurance-ready formats for Statements of Value, modeling, and desktop evaluations, AI enhances efficiency in risk management. This innovative approach not only saves time but also reduces the likelihood of errors, ultimately leading to more effective risk mitigation strategies.

Description

In recent decades, extreme wildfire conditions have surged by 50% as a result of climate change, leading to a staggering $31 billion in property damages. Consequently, many insurance firms have chosen to withdraw coverage from homes and businesses in California, significantly impacting their profitability. Terrafuse's innovative wildfire AI risk scores assess the true likelihood of property combustion a year in advance. Our wildfire risk solution empowers insurance providers to underwrite a broader range of businesses while limiting non-renewals to properties deemed to have the highest risk of burning, and it allows them to price premiums according to actual risk levels. We enhance our models by analyzing over 50 interconnected environmental factors, such as building density, dead fuel moisture, and vegetation types, to evaluate loss severity over time. Additionally, we incorporate atmospheric physics into our models through sophisticated machine learning methodologies, ensuring a comprehensive understanding of wildfire risks. This approach not only aids in better risk assessment but also fosters a more resilient insurance market in the face of escalating wildfire threats.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Archipelago

Country

United States

Website

www.onarchipelago.com/platform

Vendor Details

Company Name

Terrafuse AI

Founded

2018

Country

United States

Website

www.terrafuse-ai.com

Product Features

Commercial Real Estate

Brand Management
CRM
Cash Flow Analysis
Critical Date Alerts
Deal Management
For Appraisers
For Brokers
For Investors
For Property Managers
Portfolio Management
Strategic Planning

Product Features

Risk Management

Alerts/Notifications
Auditing
Business Process Control
Compliance Management
Corrective Actions (CAPA)
Dashboard
Exceptions Management
IT Risk Management
Internal Controls Management
Legal Risk Management
Mobile Access
Operational Risk Management
Predictive Analytics
Reputation Risk Management
Response Management
Risk Assessment

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