Ascend
Unified Environmental risk Intelligence for Asset Portfolios

Environmental risk is no longer a single-peril problem. Insurers, reinsurers, and government agencies need a unified view of wildfire, flood, wind, and other hazards across entire asset portfolios, not fragmented data from dozens of disconnected vendors.

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Understand and Mitigate the Impacts of a Volatile Environment

Ascend is a multi-hazard SaaS platform that brings together EarthDaily's proprietary earth observation intelligence and 61+ curated partner data sources into a single environment built for underwriters, portfolio managers, and risk analysts. Query complex risk data in natural language, assess correlated multi-peril exposure, and make defensible decisions backed by property-level precision.

  • Proprietary Wildfire Intelligence:
    EarthDaily's own satellite data and forestry science deliver wildfire risk scores at 20 to 30m resolution, 15 to 50 times more granular than competing products.

  • 61+ Curated Data Partners in One Platform:
    Flood, hail, cyclone, hurricane, property analytics, and more, selected, validated, and made immediately usable without managing separate vendor relationships.

  • One Geocoding Baseline Across Every Peril: Every data layer references a single, validated property location, eliminating the errors that compound when stitching together inconsistent vendor data.

Why Choose Digital Ag for Field Intelligence

Ascend replaces ZIP-code and county-level risk scores with property-level analytics across all perils. This precision enables insurance providers, forestry & utility companies, and governments to identify insurable risks within broadly high-risk zones that competitors decline.

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Unmatched Wildfire Data:

EarthDaily's Earth observation capabilities provide a fuels-based, forward-looking wildfire exposure risk score. Unlike models built on historical burn scars, Ascend's wildfire intelligence reflects current fuel loads, canopy density, and forest health conditions, updated continuously using satellite imagery from the EarthDaily Constellation.

Operational Consolidation:

Managing separate data pipelines for wildfire, flood, and hail with inconsistent geocoding and conflicting property locations introduces errors and consumes underwriter time. Ascend consolidates environmental risk analytics into one system, reducing vendor complexity and improving data consistency.

LLM-Powered Workflows for Non-Technical Users:

Embedded natural language query capabilities allow frontline underwriters and executive teams to access complex risk data without requiring GIS expertise or data science resources. Ask questions in plain language and receive actionable, data-driven insights.

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From Fragmented Data to Unified Risk Intelligence

Ascend's analytics engine combines EarthDaily's proprietary earth observation data with curated partner sources and AI-powered workflows to deliver comprehensive environmental risk assessment.

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Multi-Source Data Fusion at Scale


Access data from 61+ specialized partners covering aerial imagery, climate models, property attributes, and more. Ascend eliminates the need to manage multiple data vendors or pipelines for end-to-end workflow needs.

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Geocoding Consensus Algorithm


Accurately and scalably enhances asset location data, reducing the propagation of geocoding errors in claims and underwriting decisions. Every peril assessment references a corrected, validated property location.

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Cross-Peril Portfolio Analytics


Assess wildfire, flood, wind, hail, and other hazards across an entire portfolio from a single interface. Identify correlated exposures, compare risk across geographies, and support strategic capital allocation with integrated multi-hazard views.

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AI-Powered Natural Language Queries


Non-technical users query complex risk datasets conversationally. The embedded LLM synthesizes data across perils and assets to surface insights that would otherwise require manual analysis across multiple tools.

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Automated Data Synthesis and Scenario Forecasting


Ascend automates the assembly and reconciliation of multi-peril data, accelerating decision cycles and reducing the manual overhead that limits underwriting throughput at scale.

Learn More
Wildfire Risk Intelligence
Forward-looking wildfire probability and fuel hazard scoring built on current satellite observation of fuel loads, soil moisture, vegetation health, and biomass. Updated monthly from daily satellite capture.
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AI Wildfire Probability Model
Satellite-derived wildfire burn probabilities, fuel hazard scores, and change detection datasets with contributing factor data including soil moisture anomaly, vegetation vigor, fire weather index trends, and terrain.
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Burn Severity Mapping
10m resolution burn severity classification produced during active fires using time-series satellite analysis. Six severity classes, adaptable to customer needs, with optional Percent Conifer Basal Area and canopy height layers for salvage targeting.
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Flood Extent Mapping
Near real-time flood boundary detection from daily satellite capture. Tracks flood progression and recession over time, providing an objective, timestamped record of inundation.
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Seamless Integration with Underwriting Workflows

Single-Platform Experience:

Every peril, every asset, and every portfolio view through one environment built for underwriters, not GIS analysts or data scientists.

Consistent Geocoding Foundation:

All partner data layers are normalized against Ascend's geocoding consensus algorithm, ensuring every risk decision references the same validated property location.

Portfolio-Level Views:

Move between individual property assessment and aggregate portfolio risk analysis without switching tools or reconciling data.

Consistent Geocoding Foundation:

All partner data layers are normalized against Ascend's geocoding consensus algorithm, ensuring every risk decision references the same validated property location.

Natural Language Access:

Query risk data conversationally, reducing time-to-decision and enabling non-technical team members to contribute to risk assessment workflows.

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Coverage and Scope

Wildfire Intelligence

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United States

Coverage Area: 

Major agricultural regions including the Corn Belt, Great Plains, and Cotton Belt

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Canada:

Coverage Area: 

EarthDaily provides the only Canada-wide 20m resolution wildfire map that monitors forest health over time and indicates areas with high wildfire exposure risk.

Who Benefits from Ascend

Property Insurance Carriers

Assess wildfire, flood, and wind exposure at property level across entire books. Identify insurable risks within high-risk zones that coarse, single-peril scoring would reject.

E&S and Specialty Carriers

Capture market share as standard carriers exit climate-exposed geographies. Property-level, multi-peril precision enables faster underwriting on the volume of submissions flowing into E&S desks.

Reinsurance Companies

Evaluate cedant portfolio quality with cross-peril analytics and property-level granularity for treaty pricing and correlated multi-hazard exposure assessment.

Managing General Agents

Access institutional-grade environmental risk analytics without internal GIS, CAT modeling, or data science teams. Demonstrate data-backed risk selection to capacity providers across every peril.

Civil and Federal Government

Support disaster preparedness, infrastructure resilience, and post-event response with multi-hazard intelligence across jurisdictions.

Utilities

Assess wildfire exposure to transmission infrastructure and plan vegetation management using continuously updated fuel load and forest health data.

Ascend Features & Capabilities
Assess. Underwrite. Manage. From One Solution.

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Wildfire Exposure Risk Scoring:

Fuels-based, forward-looking wildfire risk scores derived from EarthDaily's proprietary satellite data. Monitors forest health over time and identifies areas with elevated wildfire exposure using fuel hazard mapping, distance to hazardous fuel, canopy height, forest composition, and fuel type analysis.

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Flood Extent Mapping:

Determines flooded areas in near real time using daily satellite capture from the EarthDaily Constellation. Supports emergency response, damage assessment, and claims validation by detecting inundation levels as flood boundaries evolve.

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Burn Perimeter Mapping:

Visualizes the exact geographical boundary of areas affected by wildfire, mapping the full extent of burned territory for claims assessment and portfolio exposure analysis.

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Burn Severity Classification:

Classifies the intensity of fire damage on a 0 to 1 scale, measuring vegetation removal and charred ground extent. Enables differentiated claims treatment based on actual damage intensity rather than proximity alone.

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Forest Health Monitoring:

Continuously monitors forest and vegetation condition over large areas. Detects health issues driven by invasive insects and biotic stressors before they are visible on the ground. Quantifies plant vigor, tracks phenology to map dead and dying stands, and measures soil moisture patterns that influence ignition potential and fire behavior.

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Wildfire Change Detection:

Identifies areas where wildfire probability or fuel hazard has shifted over time, enabling portfolio managers to track evolving risk exposure and adjust underwriting strategies accordingly.

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Parcel and Building Change Detectio:

Identifies new construction, demolished structures, defensible space modifications, and alterations to existing buildings by comparing high resolution satellite imagery across different time periods. Uses temporal analysis at 5m resolution to flag spectral and spatial differences indicating construction activity, demolition, or significant property changes.

Ascend is EarthDaily's multi-hazard environmental risk SaaS platform. It brings together EarthDaily's proprietary earth observation data and 61+ curated partner data sources into a single environment for assessing wildfire, flood, wind, hail, and other environmental risks across asset portfolios. Built for insurance, reinsurance, government, and utilities users, Ascend consolidates multi-peril analytics, property-level risk scoring, and LLM-powered natural language workflows into one platform.
Traditional CAT models are probabilistic and retrospective, built to estimate aggregate losses based on historical loss patterns. Ascend's proprietary wildfire intelligence uses current satellite imagery to assess actual fuel loads, canopy conditions, and forest health. This provides a forward-looking view of wildfire exposure that reflects today's fire regimes, not historical burn scar data that may no longer represent current risk.
Ascend uses a geocoding consensus algorithm that compares and reconciles location data across multiple sources to produce a validated property position. The platform displays both the original and corrected property locations, along with error distance in meters and a confidence score. This prevents the cascading errors that occur when wildfire, flood, and wind data reference slightly different property locations.
Ascend is designed to complement, not replace, existing CAT models. It fills specific gaps that probabilistic models were not designed to address, particularly on wildfire where current fuel conditions matter more than historical loss patterns. For other perils, Ascend integrates best-in-class partner data into a unified platform, improving the accuracy and usability of your overall data stack without requiring a rip-and-replace of existing tools.
Ascend's embedded LLM allows users to ask questions about risk data in plain language. The system synthesizes data across perils, assets, and portfolio segments to return actionable insights. This enables underwriters and executives to access complex analytics without technical training or GIS expertise. [VERIFY: Provide specific examples of supported query types and output formats.]
Daily satellite capture from the EarthDaily Constellation enables monthly updates to wildfire risk scores and fuel hazard data. This provides a faster refresh cadence than solutions that rely on annual or semi-annual data updates, ensuring risk assessments reflect recent changes in vegetation, fuel loads, and forest conditions.
Ascend covers wildfire, flood, wind, hail, cyclone, and hurricane through a combination of EarthDaily's proprietary satellite data and 61+ curated partner sources. The platform provides an integrated, multi-hazard view of risk exposure at the property and portfolio level. [VERIFY: Provide complete list of available perils and data sources.] Or Leave as is?
Ascend uses daily satellite capture from the EarthDaily Constellation to determine flooded areas in near real time. This supports emergency response, damage assessment, and claims validation by detecting inundation levels as flood boundaries evolve. [VERIFY: Is historical flood risk modeling also available through partner data, or only near-real-time detection?]
Yes. While Ascend is designed primarily for insurance, reinsurance, and government users, the platform's multi-hazard analytics also serve utilities assessing wildfire exposure to infrastructure, financial institutions evaluating environmental risk in lending portfolios, and organizations meeting environmental risk disclosure requirements under TCFD, ISSB, and SEC guidance.

Ready to see Ascend in action?

Discover how Ascend's multi-hazard intelligence can strengthen your underwriting, portfolio management, and risk assessment workflows. EarthDaily offers a 3-month proof-of-value engagement that benchmarks Ascend against your current workflow on speed, accuracy, and risk selection.