Reports & Research

Are rising storm costs and inaccurate roof assessments impacting your bottom line?

Now available to stream, The Science of Roof Risk master class will equip you with the latest strategies and techniques to master roof risk assessment.

• Enhance your roof risk assessment by 60X
• Improve your combined ratio
• Reduce storm-related roof claims
• Strengthen new business selection

What we cover:

Your presenters, Ross Martin (VP, Risk Analytics) and Sam Fetchero (Head of Marketing) will share with you:

• The Problem of the Roof:  Uncover the underlying factors driving rising storm losses and why traditional risk assessment methods fall short.
• The Science Behind Predicting Losses: Explore key factors impacting  roof risk and loss prediction, including roof age, condition, complexity, and peril-specific models.
• Accuracy-focused Risk Models: Discover advanced modeling techniques that enhance predictive accuracy.
• Understanding Storm Climatology: Learn how storm climatology impacts roof risk and how to integrate these insights into your risk assessment strategies.
• Real-World Results: Witness a comparative analysis of these predictive factors using actual carrier data. Understand the strengths and weaknesses of each approach.
• Priorities of Leading P&C Insurers: 
  See what your peers asked with valuable insights to take back to your team.

Who Should Watch?

This video is ideal for Executives, Product Managers, Actuaries, Underwriters, and CAT Modelers committed to enhancing their roof risk assessment capabilities. 

Bonus Guide

As a bonus for watching, you'll receive a downloadable study on the latest roof risk assessment strategies: Preparing for the Storm: The Insurers Guide to Roof Risk.

Access Now

From Costly Water Losses to Millions in Savings

Non-weather water claims are a leading cause of property insurance losses, costing insurers over $20 billion annually. 

Join us for a FREE live webinar where our experts will discuss the latest trends, challenges, and insights to help you mitigate non-weather water risk.

What We'll Cover

Our experts Rob Silva, ACAS (Director of Customer Success) & Sam Fetchero (Head of Marketing) will present:

• Current Trends: Understand the rise in severity and total loss costs of non-weather water claims.
• Risk Assessment Challenges: Learn why traditional methods fall short in assessing non-weather water vulnerability.
• Key Risk Factors: Identify the main drivers of non-weather water damage.
• Strategic Insights: Discover strategies to improve your management of non-weather water claims.
• Z-WATER in Action: Experience our new AI-powered model that predicts non-weather water risk with unparalleled accuracy.
• Interactive Q&A: Get your questions answered by our experts.

Who Should Attend

This webinar is ideal for Executives, Product Managers, Actuaries, Underwriters, and CAT Modelers committed to enhancing their understanding and management of non-weather water risks. 

Bonus Content

As a bonus, you'll receive our exclusive infographic, "Below the Surface: Research Reveals Knowledge Gap in Homeowner Water Loss Prevention and Coverage."

This research gives key insights into water loss experiences, coverage details, homeowner protection measures, and information on water shutoff devices and heater conditions.

Register Now

It’s hard to overstate how important the roof is from an insurability standpoint. The roof represents significant risks and potential opportunities, making it a critical focus area for insurers. This has become even more important in recent years as the impact of severe convective storms is often reflected in roof losses. Understanding this, ZestyAI has released new research for property insurers called The Insurers Guide to Roof Risk.

Download The Insurers Guide to Roof Risk

In an era where the severity and frequency of roof-related claims are on the rise, particularly due to the increasing impact of severe convective storms, innovative tools and strategies are essential. The Insurers Guide to Roof Risk provides actionable insights to improve risk assessment, underwriting processes, and overall business strategy.

What’s Inside the Guide?

The Insurers Guide to Roof Risk includes:

• Roof Failure Factors: Learn the underlying contributing factors behind why older roofs fail more often.
• Beyond Roof Age: Discover why roof complexity, condition, and climate are more important than roof age alone.
• Identifying Missing Risk Factors: Understand the key factors to roof risk that most traditional models miss.
• Advanced Risk Segmentation: See how using machine learning and new data sources can split risk more than 60 times better than traditional models.
• Portfolio Optimization: Access a comprehensive toolbox to optimize your portfolio and new business selection to generate exponential lift versus traditional models.

Download Now

Annual Wildfire Season Overview provides insights to assist insurers in effectively managing wildfire risk.

ZestyAI has released its annual Wildfire Season Overview for 2024. This year’s guide provides critical insights carriers need to stay ahead of the rapidly evolving wildfire landscape. Offering more than just data, this year’s guide is designed to help insurers make informed risk decisions in some of the country’s most volatile states. 

Download ZestyAI's 2024 Wildfire Season Overview 

This year’s guide includes: 

• Countrywide Wildfire Impact Analysis: Understand how wildfires are affecting regions beyond traditional hotspots like CA, including significant events in TX & NM.
• Future Wildfire Trends: Explore predictions for the 2024 wildfire season and understand the long-term implications of current conditions on wildfire risks.
• Regulatory Insights: Stay updated on the latest regulations affecting wildfire risk assessment insurance practices.
• AI-driven Risk Models: Learn how ZestyAI's Z-FIRE model accurately predicts wildfire risks and assists insurers in making informed decisions.
• Property-Level Risk Assessments: Discover the importance of granular, property-specific risk evaluations to improve underwriting accuracy and transparency for consumers.

Download Now

Costing insurers approximately $19 billion every year, roof claims stand as the primary driver of property insurance losses.

Traditional methods of obtaining roof age information are deeply flawed. Most carriers depend on policyholder or agent-reported data, which is often inaccurate, leading to blind spots in assessing property risk. In a recent ZestyAI survey, 63 percent of homeowners reported not knowing the age of their roof if they were not in their homes the last time it was replaced.

Join our expert panel for a deep dive into leveraging roof age analytics for a cutting-edge underwriting process and gain insider knowledge on:

• The Leading Cause of Claims: unveil the hidden truths behind roof-related claims and the costly consequences of outdated assessment methods.
• A New Era of Data: Learn about ZestyAI’s pioneering approach to roof age analytics, incorporating building permits, historical imagery, and AI for a comprehensive view
• Precision at Scale: See how to apply precise, AI-driven roof age data across your entire portfolio for consistent and reliable underwriting and claims decisions
• Technical Decision Making: Empower your actuaries and underwriters with the insights needed to enhance risk selection and optimize pricing strategies
• Efficiency in Operations: Streamline inspections and operations, focusing resources where they’re needed most, improving time-to-quote, and enriching the customer experience
• Best Practices: Learn how leading carriers are using roof age, roof condition, and peril-specific models to improve risk selection and lower combined ratios 

This transformative session is available on demand. Learn how to enhance accuracy, efficiency, and profitability in property insurance.

Save Your Spot

In an ever-evolving regulatory environment, staying informed and adaptable is crucial. Our latest interactive guide, "When Innovation and Regulation Meet", offers a comprehensive toolkit for navigating the complexities of insurance compliance and the integration of AI technologies. 

What's Inside?

• Regulatory Landscape Map: Delve into a detailed state-by-state analysis, uncovering the intricacies of filing laws and approval speeds.
• Staying Ahead of Regulation Changes: Learn how to stay prepared and ensure your compliance strategies are future-proof, aligning with the latest regulatory expectations.
• Essential AI Partner Checklist: Choosing the right AI partner is crucial for success. Our guide offers a meticulous checklist for selecting a partner that is not only compliant but also transparent and supportive, ensuring you make an informed decision.
• Emerging Regulatory Concerns: What do you need to know about privacy, bias, and AI oversight?
• Real-World Applications: Discover how ZestyAI's collaborative approach with regulatory entities has led to successful model approvals across the United States. 

Why This Guide?

As the regulatory framework becomes increasingly complex, having a reliable and insightful resource is indispensable. Our guide is tailored for insurance professionals seeking to enhance their regulatory strategy, embrace AI innovation responsibly, and achieve a competitive edge in the market.

Ready to get up to speed on 2024's regulatory environment? Access the guide.

As we close out 2024, we’re taking a moment to reflect on a year defined by deeper partnerships, relentless innovation, and measurable progress in the insurance industry.

Watch the video message from our CEO, Attila Toth, to learn more about the milestones we achieved and what’s next for ZestyAI.

Strengthening Relationships

This year, we deepened our collaborations with existing partners and welcomed new customers across the country. Nearly half of the top 100 insurance carriers now trust ZestyAI to deliver precise, AI-driven insights that enhance underwriting, streamline operations, and address emerging risks in high-peril areas.

Innovation That Delivers Value

At ZestyAI, innovation is never just for its own sake—it’s about delivering actionable value that solves real-world challenges. In 2024, we launched:

• Z-WATER™: Our new model that predicts non-weather-related water damage claims, helping carriers identify and mitigate this growing risk.
• Roof Age: Leveraging historical imagery and building permit data to provide accurate roof condition insights for better underwriting and risk management.

We also delivered substantial enhancements to Z-PROPERTY™, our leading property insights platform:

• Increased Coverage and Improved Hit Rates: Ensuring more comprehensive and reliable property assessments.
• New Features: Including driveway condition insights and support for multi-structure properties, enabling insurers to prioritize resources and streamline inspections.

Tremendous Regulatory Momentum

This year brought significant progress in regulatory approvals, further validating ZestyAI’s solutions in key markets like California, Texas, and Colorado. Our models continue to set a benchmark for responsible AI adoption, ensuring insurers can confidently integrate advanced property risk insights into their workflows.

Delivering Performance Across Perils

ZestyAI’s AI-powered models continued to prove their value under the industry’s most challenging conditions:

• Z-FIRE™: Recognized as the gold standard for wildfire risk across the U.S.
• Z-HAIL™: Predicting hail claim frequency and severity with up to 58 times greater accuracy than traditional models.
• Z-WIND™ and Z-STORM™: Delivering granular risk assessments for wind and storm-related risks.

These innovations are helping insurers reduce loss ratios, improve profitability, and ensure coverage availability where it’s needed most.

Looking Ahead to 2025

As we move into the new year, ZestyAI remains committed to revolutionizing risk management through AI-driven precision and proven performance. We will continue to help insurers navigate emerging challenges, drive efficiency, and build a more resilient future for their policyholders.

From all of us at ZestyAI, thank you for being part of this journey. Wishing you a wonderful holiday season and a successful year ahead.

The California Department of Insurance (CDI) has introduced significant updates as part of its Sustainable Insurance Strategy. These new bulletins and draft regulations aim to accelerate regulatory approvals, embrace forward-looking models, and address critical reinsurance challenges.

But what do these changes mean for insurance carriers—and how can you prepare?

On January 29, 2025, we hosted a webinar, California’s Evolving Insurance Landscape: The Future of Insurance in the Golden State. 

Designed for Legal & Compliance professionals, Product Managers, Underwriters, Actuaries, and Risk & Innovation leaders, the discussion featured expert insights from:

• Michael Peterson, Deputy Commissioner of Climate & Sustainability, California Department of Insurance
• Karen Collins, VP, Property & Environmental, APCIA
• Bryan Rehor, Head of Regulatory Affairs, ZestyAI

Missed the live event but want to gain actionable insights from industry leaders at the forefront of California’s insurance evolution? Watch on demand now!

ZestyAI, the leading provider of AI-powered climate and property risk analytics solutions, has received regulatory approval from the Iowa Insurance Division for its Severe Convective Storm suite, including Z-HAIL, Z-WIND, and Z-STORM. 

This approval marks a critical milestone in helping insurers address the growing challenges posed by severe weather in one of the Midwest’s most storm-affected states.

In 2024, Iowa experienced five billion-dollar severe weather events, with hailstorms driving billions in damages and insurance losses. In one instance, a hailstorm caused $2.4 billion in damage, underscoring the urgent need for innovative tools to assess and manage storm-related risks.

ZestyAI’s Severe Convective Storm suite delivers property-specific risk assessments, enabling insurers to predict and mitigate extreme weather impacts with precision. Designed with regulatory compliance at its core, Z-HAIL is validated using actual loss data and provides a clear breakdown of the top three risk drivers for each score. This transparency empowers insurers to make informed decisions and share actionable insights with policyholders. 

By analyzing climatology, geography, and building characteristics, ZestyAI equips insurers to identify high-risk properties, allocate resources strategically, and encourage proactive risk-reduction measures among policyholders.

"This approval empowers our carrier partners to act quickly and confidently in addressing Iowa’s severe weather challenges," said Bryan Rehor, Director of Regulatory Affairs at ZestyAI.

"By streamlining subsequent filings, we help insurers save time and resources, ultimately making high-quality property insurance more accessible to Iowa homeowners."

ZestyAI’s Severe Convective Storm suite has already received approvals in other key hail belt states, including Texas, Colorado, Illinois and Indiana, with additional filings in progress. These models enable insurers to move beyond reactive damage assessments, improving their ability to assess and manage storm-related risks at a granular, property-specific level.

With this approval, ZestyAI continues to lead the charge in equipping insurers with the tools they need to navigate an era of climate uncertainty, ensuring communities and insurers alike can better weather the storm.

                           Scaling a complex system of machine learning models while delivering real-time insights is no small feat. ZestyAI’s engineering team reimagined its architecture to overcome these challenges, leveraging NVIDIA’s Triton Inference Server and introducing the “Monster Pod.” This transformation halved API response times, increased throughput by 10x, and cut cloud costs by 75%. Dive into how strategic experimentation and innovative design unlocked efficiency and positioned ZestyAI for future growth.                        

By Andrew Merski, VP, Engineering 

The Challenge: A Complex and Scaling System

Business Context

At ZestyAI, we deliver critical insights to insurance clients using machine learning models. Our API processes a significant volume of data, including imagery, geolocation, and structured data, to produce real-time results. The complexity of each request places immense demands on our infrastructure:

• Synchronous API Calls: Each request must be processed in real-time, with all insights delivered back to the client in a single response. Low latency is non-negotiable, as our clients’ workflows rely on immediate feedback.
• Multiple ML Models Per Request: Each request may invoke up to 30 ML models, ranging from computer vision models analyzing aerial imagery to models synthesizing geospatial and tabular data.
• Growing Model Catalog: The catalog of ML models we deploy continues to expand, driven by both customer needs and internal innovation. Each new model adds additional complexity to the system.
• Exceptional Reliability: Our clients in the insurance sector demand a system that operates flawlessly, with uptime and accuracy critical to their decision-making processes.

Previous Architecture: A Decentralized Model

In our previous system, each ML model operated as an independent microservice. Each model scaled independently, and each instance required its own GPU. While functional, this architecture introduced critical issues:

• Resource Underutilization: GPUs were underutilized, with non-GPU tasks consuming significant time.
• Scaling Challenges: Periods of high API traffic put additional strain on system components, leading to some inefficiencies.

• Capacity Limitations: The previous architecture had constraints that limited scalability, which could have restricted future growth.

This architecture also resulted in significant operational complexity. Each model’s independent deployment meant substantial manual effort in testing, scaling, and troubleshooting. Cloud costs also escalated rapidly as new models were added, creating diminishing returns for each improvement in service quality. 

The Solution: A Centralized Architecture with Triton

Faced with scaling challenges and rising customer demand, we reimagined the entire architecture. At the heart of the solution was NVIDIA’s Triton Inference Server, a tool designed for efficient multi-model serving.

Why Triton?

Triton enabled:

• Shared GPU resources across models.
• Ensemble models to define workflows using configuration rather than code.
• Extensive benchmarking tools for performance optimization.
• Support for various backends, including Python and Pytorch.

However, Triton required significant investment in layers of customization to meet our needs. Its low-level interface and lack of native autoscaling demanded a tailored implementation.

New Architecture: The Monster Pod

To maximize Triton’s potential, we introduced the “Monster Pod,” consolidating all models and supporting microservices into a single Kubernetes pod. Key features included:

• Single-host model serving: All models resided in a unified Triton instance.
• Integrated workflow management: The workflow orchestrator and other microservices were co-located with Triton.
• Streamlined scaling: Each pod functioned as an independent unit, simplifying horizontal scaling.

This “Monster Pod” approach offered numerous benefits:

Improved Resource Utilization

• Maximized GPU usage by serving multiple models per instance.
• Reduced the overhead associated with multiple nodes and microservices.

Simplified Testing and Benchmarking

• Each pod contained all necessary components, enabling comprehensive testing in isolation.
• Benchmarking provided clear insights into throughput and resource requirements.

Reduced Scaling Overhead

• Eliminated dependency on Istio for internal traffic management.
• Simplified node provisioning and scheduling.

Predictable Costs

• Each pod corresponds to a fixed node cost, allowing accurate cost planning. 

Lessons Learned

This project revealed critical insights that extend beyond Triton or even ML systems:

1. The "Microservices vs. Monolith" Debate Isn’t Binary
Architectural decisions don’t have to be all-or-nothing. For instance, while our deployment consolidated models into a single pod, we retained microservices for other aspects of the platform. Evaluating “single vs. many” decisions at multiple levels allowed us to optimize each layer independently.

2. Understand the Bottlenecks Before Designing Solutions
Identifying the root causes of inefficiency—scaling overhead, resource underutilization, network traffic—helped us design a system that addressed these challenges holistically rather than incrementally.

3. The Power of Consolidation
Integrating multiple components into a single deployment reduced complexity, improved performance, and simplified scaling. This approach may not suit every scenario, but in our case, it delivered transformative results.

4. Be Open to Temporary Solutions (Flexibility Leads to Innovation) 
The “Monster Pod” started as a quick workaround but became a permanent fixture due to its outsized impact. Being open to experimentation unlocked unexpected benefits, such as easier resource planning and reduced operational complexity.

Business Impact

Rebuilding our ML inference platform was a bold move that paid off. The new architecture produced dramatic improvements across key metrics:

• Latency: API response times were halved.
• Capacity: System throughput increased by 10x, eliminating the previous capacity ceiling.
• Cost Efficiency: Cloud costs for model serving dropped by 75%.

These gains position us to scale with growing demand while maintaining industry-leading performance. Additionally, the simplified architecture has freed up engineering resources to focus on innovation rather than maintenance.

While Triton Inference Server played a critical role, the real success lay in our architectural decisions and willingness to rethink the status quo. This project underscores the value of experimentation and the importance of tailoring solutions to meet unique challenges.

The lessons learned from this journey will continue to inform our approach to system design and scalability as we look ahead. The Monster Pod has not only transformed our current capabilities—but has also set the stage for future growth and innovation.

For a deeper dive into the technical details, check out Andrew Merski’s original blog on Medium.

In an industry as established and thoughtful as insurance, bold innovation isn’t always easy to come by. ZestyAI is working to change that by integrating artificial intelligence into the core of how insurers manage risk, optimize pricing, and drive growth.

We are honored to receive two recognitions this year, highlighting the growing role of technology in driving meaningful progress and affirm our commitment to being a trusted partner for property insurers navigating an ever-evolving landscape

Leading the Way in P&C Insurance Technology

ZestyAI has been named one of the Everest Group’s Leading 50™ Property & Casualty (P&C) Insurance Technology Providers for 2024. This recognition celebrates technology providers that are transforming the P&C insurance sector through advanced platforms and solutions.

The Everest Group evaluated companies based on metrics such as revenue derived from P&C-focused technology, value chain coverage, and innovation in product offerings and partnerships.

ZestyAI earned accolades in two categories: Emerging Risks Intelligence and Assessment (Climate) and Risk Intelligence for Property Insurance.

These honors reflect the proven performance of our AI-driven platform under the most challenging conditions. From the devastating California wildfires of 2020 and 2021 to the unprecedented 2023 convective storm season, our models—Z-FIRE, Z-HAIL, Z-WIND, and Z-STORM—have consistently delivered reliable insights and results

Shaping the Future of Climate Risk Analytics

Chartis Research ranked ZestyAI 47th out of 175 organizations in climate risk analytics, recognizing our significant contributions to addressing climate risk challenges in insurance. This acknowledgment highlights our commitment to tackling secondary perils—including wildfire, hail, wind, and severe convective storms—through advanced AI-powered property insights and predictive models.

Our platform-driven approach, grounded in climate science, equips insurers with actionable, peril-specific insights. These tools empower them to navigate the complexities of climate risk, adapt to an evolving regulatory and environmental landscape, and optimize risk management strategies.

Driving Innovation and Excellence

This year’s recognitions join a growing list of accolades celebrating our contributions to innovation and excellence. ZestyAI has been named one of Forbes’ Top Startups to Work For in America, as well as one of Inc. 5000’s Fastest Growing Private Companies in America. Additional honors include recognition on the Deloitte Technology Fast 500, inclusion in the CB Insights Insurtech 50, an AI Breakthrough Award for Machine Learning, and a PropertyCasualty360 Insurance Luminary award for Risk Management Innovation.

 These accolades inspire us to keep pushing boundaries, delivering exceptional value, and pursuing our mission to create a more sustainable and resilient insurance ecosystem.

ZestyAI, the leading provider of climate and property risk analytics solutions powered by AI, has partnered with American Farmers & Ranchers Mutual Insurance Company (AFR), a trusted name in rural insurance in Oklahoma for over 100 years.

The partnership leverages ZestyAI’s aerial imagery and risk modeling solutions to enhance AFR’s property risk assessment and streamline underwriting processes.

With nearly 100% aerial imagery coverage across the contiguous U.S., ZestyAI’s platform delivers superior hit rates, unparalleled image quality, and peril-specific risk models for wildfire, wind, and hail—empowering AFR to assess risk at a granular, property-specific level.

Kimball Lynn, Director of Underwriting & Operations at AFR, said, “While our primary focus was aerial imagery, we quickly realized that ZestyAI’s solutions for assessing peril-specific risks like wind, hail, and wildfire made them a multifaceted underwriting solution. In Oklahoma, where  wind and hail are constants, their severe convective storm risk-scoring capabilities stood out.”

“The shift to ZestyAI's broader coverage footprint and more consistent, accurate, up-to-date imagery has improved our underwriting approach."

Carriers often face challenges with aerial imagery providers covering only 75%-80% of the U.S., leaving gaps in rural areas and outdated visuals. ZestyAI solves this by integrating data from all major aerial imagery providers, achieving nearly 100% hit rates with more recent imagery.

This approach ensures precise insights into property risks—such as roof quality, lot debris, and driveway condition—empowering insurers with a complete, up-to-date view.

Kimball Lynn added,

"ZestyAI’s training and platform are intuitive, which made for a smooth adoption, and the onboarding experience and ongoing support have made for a strong partnership so far.”

Attila Toth, Founder and CEO of ZestyAI, emphasized AFR’s proactive approach:

“AFR's foresight in preparing for emerging risks is setting an example for other carriers and demonstrates their dedication to innovative risk management and protecting their communities. We're proud to partner with a company that shares our commitment to proactive, data-driven risk management.”