Resources

We’re proud to share that ZestyAI has been named to Sønr’s 2025 Beyond Boundaries Scale50, recognizing the top 50 established insurtechs driving measurable impact and transformation across the global insurance industry.

Produced by Sønr, a leading market intelligence firm tracking more than four million companies worldwide, the Beyond Boundaries 2025 report identifies the innovators redefining insurance through AI, data, and collaboration.

This year’s analysis underscores a clear shift in the market: the age of experimentation has given way to execution and scale—where efficiency, resilience, and real-world outcomes define success.

At ZestyAI, we’re proud to be part of that evolution. Our Decision Intelligence Platform brings together property-level data, predictive AI models, and Agentic AI automation to help insurers see, price, and manage risk with precision and confidence.

Trusted by carriers and regulators across the U.S., ZestyAI’s solutions deliver measurable improvements across underwriting, rating, reinsurance, and regulatory workflows—helping insurers make faster and more data-driven decisions.

Matt Connolly, Founder and CEO of Sønr, said:

The insurance industry has long talked about change. And now, we’re seeing it happen. After years of incremental steps, the market is finally embracing the opportunities technology brings - and the impact is tangible.

Read the full report: Beyond Boundaries 2025

DUAL North America Inc.’s (“DUAL”) personal property division has selected ZestyAI’s Z-STORM™ model to enhance storm-risk underwriting and pricing as it continues its rapid US expansion.

The partnership equips DUAL with sharper risk differentiation, more accurate underwriting and pricing, and a stronger foundation for sustainable growth in regions increasingly affected by severe convective storms.

By adopting ZestyAI’s severe convective storm model, DUAL will strengthen its ability to identify and price the combined effects of hail and wind with greater precision. This will enable faster, more informed decisions and profitable expansion while maintaining regulatory compliance.

The collaboration reflects DUAL’s continued investment in advanced analytics and technology to support long-term growth.

The specialty program administrator, offering more than 40 insurance products and surpassing $1.3 billion in gross written premium in 2024, continues to broaden its capabilities across commercial, specialty, and personal lines.

Luke Wolmer, Chief Actuary at DUAL, said:

“As we continue to grow across personal property lines, having accurate risk prediction at the property level is crucial."

Z-STORM gives us a more nuanced understanding of storm vulnerability, helping us recognize differences in risk that traditional models overlook. This enhances our team’s confidence in pricing decisions and will support our continued expansion across the U.S.”

Z-STORM is an AI-powered risk model that evaluates the combined effects of hail and wind to predict the frequency and severity of storm-related damage at the property level. By analyzing the interaction between local climatology and the unique characteristics of every structure—including roof condition, material, and surrounding exposure—the model delivers precise, property-specific insights into storm vulnerability.

In September 2025, ZestyAI introduced mitigation-aware scoring to its severe convective storm suite, allowing insurers to dynamically adjust risk scores to reflect verified improvements such as roof replacements, upgraded materials, or corrected property data. This enhancement gives carriers a scalable way to recognize mitigation within pricing and underwriting workflows, advancing transparency and regulatory alignment.

Attila Toth, Founder and CEO of ZestyAI, said:

“DUAL’s adoption of Z-STORM reflects a forward-thinking approach to storm risk management."

"By applying property-level risk analytics and mitigation-aware scoring, DUAL is positioned to underwrite more precisely, grow responsibly, and strengthen community resilience across the regions that are most exposed to extreme weather”.

ZestyAI’s storm models are regulatory reviewed and ready to use across the Great Plains, Midwest, and U.S. South, regions most impacted by severe convective storms, and are actively used by carriers for rating and underwriting.

ZestyAI today announced the expansion of ZORRO Discover™ to all property and casualty insurance lines.

ZORRO Discover analyzes millions of state filings to surface real-time regulatory and market intelligence, giving carriers actionable insights to make faster, more confident decisions. Carriers using the platform have reduced adverse selection, accelerated regulatory approvals by up to 50%, and expanded analytical capacity more than 20-fold—turning what was once a manual, fragmented process into a source of strategic advantage.

The platform now delivers unified visibility across all P&C lines, including Commercial Auto and Property, Personal Auto and Property, Financial and Specialty Lines, Liability and Professional Lines, Workers’ Compensation, and Administrative filings—covering every major filing type across the United States.

Built on ZestyAI’s Agentic AI platform, ZORRO Discover scales decision intelligence across the insurance industry, transforming over a decade of U.S. insurance filings into a single, transparent system of insight. Carriers can instantly benchmark competitors, analyze rating trends, and anticipate regulator feedback and objections in real time, turning regulatory filings from a compliance requirement into a strategic advantage.

Kumar Dhuvur, Chief Product Officer and Co-Founder at ZestyAI, said:

“Every corner of P&C faces the same challenge: too many filings and too little time. Now, whether it’s workers’ comp in Texas or commercial auto in California, teams can simply ask ZORRO and get instant, verified insights in real time.”

By analyzing past objections and outcomes, teams can anticipate regulators’ questions before they arise and move filings forward with precision. Live monitoring of new submissions keeps organizations current on competitor moves and market shifts, turning what was once a fragmented, manual workflow into a real-time decision system that helps teams act quickly and strategically.

With its conversational interface, users can simply ask ZORRO to surface insights that once took hours or days to uncover. Product, actuarial, and regulatory teams can now collaborate from a single, auditable source of truth, replacing manual searches and static spreadsheets with transparent, explainable intelligence that drives faster, smarter action.

ZORRO Discover is available now for all property and casualty insurance lines.

Start your trial.

‍

At ZestyAI, we know that better data leads to better decisions. That’s why we’ve invested in a major upgrade to our Roof Age product, trusted by leading carriers to improve risk selection, pricing, and operational efficiency in property insurance.

Today, we’re excited to share what’s new, what’s improved, and how these advancements are already helping carriers strengthen underwriting, rating, and inspection workflows.

What’s New in Roof Age

We’ve taken a holistic approach to improving performance, accuracy, and efficiency. Here’s what you’ll find in the latest release:

Refit model with double the training data

We’ve significantly enhanced the Roof Age model, doubling the size of our training dataset to improve performance across diverse housing stock, roof types, and geographies.

This expanded dataset incorporates more confirmed roof replacement events and broader regional variation, allowing the model to generalize more effectively to different parts of the country, including historically underrepresented regions.

The model is now better able to distinguish between full roof replacements and other types of roof-related activity, such as solar panel installation, patched sections, partial replacements, or home additions.

These events may alter the roof’s appearance or condition, but don’t represent a comprehensive replacement. By learning the subtle visual and contextual cues that separate these scenarios, the model delivers more accurate predictions and reduces the risk of misclassification.

Enhanced estimation for challenging cases

In cases where no building permit is available and roof replacement can’t be clearly confirmed via aerial imagery, our improved Roof Age Estimation Model takes over. This model, now trained on double the dataset, is purpose-built for ambiguity.

It leverages not only imagery and property-level features but also regional climatology, using knowledge of local weather patterns and environmental stressors to inform its estimate.

For example, a roof in the Southeast exposed to intense sun and humidity will age differently than one in the Pacific Northwest or Upper Midwest. Incorporating these regional factors helps improve estimation accuracy, even when direct replacement signals are unavailable.

ZestyAI also establishes a minimum roof age, providing additional clarity and confidence. Using our extensive, 20-year aerial imagery catalog, we can identify the earliest visual evidence of the current roof.

If no replacement activity is detected over a known span of time, we can confidently assert that the roof is at least that old.

This minimum age is then used not just as a floor, but as a valuable input to further refine the overall roof age estimate, narrowing the prediction with greater precision than models limited to single-source or snapshot data.

This capability provides underwriters and actuaries with a powerful, high-confidence signal, particularly valuable for pricing segmentation, inspection prioritization, and risk selection strategies.

Intelligent cross-validation logic

The model doesn’t rely on a single data source. Even when a strong signal like a building permit is available, it cross-validates with high-resolution aerial imagery to detect inconsistencies, like permits that were filed but not followed through, or replacements that occurred without permits.

This layered logic helps ensure predictions are grounded in current conditions, not just administrative records. It also improves detection of fraud, data entry errors, or outdated assumptions in property records.

This logic creates a "trust but verify" framework that boosts both precision and confidence in every prediction.

To illustrate, imagine a home built 12 years ago. The model begins by anchoring to the construction year, then scans forward through our aerial imagery catalog and permit records to assess whether a roof replacement has occurred.

By grounding the analysis in the property's timeline, the model avoids misinterpreting the original roof as a newer installation and increases confidence in identifying true replacement events.

Expanded imagery catalog

We’ve enriched our aerial imagery sources to improve roof verification across geographies. The result: more accurate verification of roof replacements and improved model performance in hard-to-cover geographies.

This helps carriers score more properties with higher confidence, especially in rural or previously under-covered regions.

Confidence scores for every prediction

Every Roof Age prediction now comes with a confidence score, helping carriers make more informed decisions. High-confidence predictions can be fast-tracked for automated processing, while lower-confidence scores can trigger secondary review or inspection.

This added transparency empowers carriers to make risk-based decisions not only on the prediction itself, but on how much to rely on it.

Improved Performance Behind the Scenes

We’ve also made significant infrastructure upgrades to enhance product speed and reliability.

• Reduced Latency: Infrastructure improvements have cut average response times to under 2.5 seconds per property, making Roof Age a real-time-ready solution for quoting and policy decisions.
• Stricter Quality Controls: We’ve added new safeguards to filter out imagery that’s blurry, outdated, or contains visual artifacts. Only high-resolution, high-confidence inputs are used to power predictions.
• Scalability: These backend improvements also allow us to handle larger portfolios with more concurrent requests. This is ideal for carriers integrating Roof Age into enterprise systems.

Easier Access for Every Workflow

Roof Age is available wherever you need it:

• In Z-VIEW: Easily visualize Roof Age predictions and supporting evidence with property-level insights directly in our web application.
• Via API: Seamlessly score entire portfolios and integrate directly into your quoting, pricing, or inspection strategies.

Ready to See the Results for Yourself?

The feedback from the market has been tremendous, and we’re just getting started. Want to see the results for yourself? We’re inviting carriers to pilot the new Roof Age model and evaluate its performance on their own book of business.

Get in touch to schedule your Roof Age pilot

ZestyAI announced that Brava Roof Tile, a leader in premium synthetic roofing solutions backed by Golden Gate Capital, has selected ZestyAI to validate the real-world performance of its roofing systems during past storms.

How Brava Roof Tile Uses ZestyAI’s Property and Roof Intelligence

Brava Roof Tile is leveraging three of ZestyAI’s proven solutions to bring greater clarity to roof performance and replacement opportunities. Roof Age synthesizes building permit data with 20+ years of high-resolution aerial imagery, applying advanced machine learning to deliver verified roof age estimates with 97% U.S. coverage.

Within Z-PROPERTY™, Digital Roof applies AI to assess roof complexity, materials, and condition, flagging vulnerabilities before they become costly failures, while Location Insights evaluates the broader parcel to surface risk factors such as vegetation overhang, yard debris, and secondary structure.

Together, these insights provide comprehensive coverage, unmatched accuracy, and fast deployment at scale, turning property-level data into actionable guidance on roof vulnerabilities and replacement opportunities.

Validating Real-World Resilience With Property-Level Data

“Brava is committed to helping homeowners protect their most valuable asset with roofs that combine durability, sustainability, and beauty,” said Matt Pronk, Chief Financial Officer of Brava Roof Tile.

“With ZestyAI, we gain a clear, data-driven view of how roofs perform in the real world and use those insights to guide families toward stronger, longer-lasting protection.”

“Brava Roof Tile is showing how ZestyAI's risk analytics can be applied to validate resilience in the real world,” said Attila Toth, Founder and CEO of ZestyAI.

“Our mission is to protect families, communities, and their financial wellbeing, and our unmatched coverage and accuracy make that possible at scale."