Scorecards
Versioned scorecards and per-storm summaries that partners use to validate and audit engine behavior.
Structural intelligence
Governed structural insight for hurricane risk
PTEM is a structural priming engine paired with a frozen, multi-season dataset. Risk teams use it to benchmark scenarios, evaluate readiness regimes, and add a validated structural view alongside traditional hazard models.
Licensed only to institutional risk owners, reinsurers, and public programs that require governed audit trails.
Validation surface
Frozen dataset, governed delivery
Historical archives, structural snapshots, and audit notes ship with every tier so partners can reproduce PTEM scoring.
- Versioned validation pack with every agreement
- Structural signals at a 6-hour cadence
- SDK integration support for risk workflows
Why PTEM?
PTEM offers a rigorously validated structural view of storm evolution, drawn from a frozen, multi-year dataset and a governed analytical engine. Risk teams use PTEM to benchmark scenarios, evaluate structural regimes, and integrate a trusted second perspective into existing models.
Under the hood, PTEM tracks structural coherence, phase alignment, and priming indices over time and looks for sustained tightening patterns that have historically preceded major regime shifts.
The result is an orthogonal signal: a structural engine that can flag when a storm is entering a high-readiness regime before intensity-based thresholds are met.
Snapshot
A compact view of the PTEM hurricane engine
A frozen structural dataset, a reproducible engine, and a narrow surface area for integration.
Structural snapshots
Compact structural snapshots at a 6-hour cadence so teams can integrate PTEM signals without exposing internal model fits.
Governed access
Access tiers that separate evaluation/research from production-grade enterprise integrations with governance and audit support.
How PTEM works
A structural engine on a frozen, auditable dataset
PTEM runs on a frozen, multi-season tropical cyclone dataset. The engine produces governed structural signals that can be audited, compared against baselines, and blended into existing risk workflows.
Step 1
Frozen dataset
PTEM is anchored to a multi-season dataset so partners can reproduce scoring and compare model snapshots fairly.
Step 2
Structural engine & governance
PTEM extracts structural signals, applies governance layers, and delivers versioned outputs for audit and integration.
Step 3
Integration & validation
Partners start with evaluation materials and can progress to enterprise integrations supported by validation packs and governance processes.
SDK & API integration
PTEM is delivered as a cloud-hosted engine with a simple SDK and API. Risk teams can pull structural metrics for active storms and integrate them into existing hazard workflows, internal tools, or research environments.
{
"storm_id": "al152025",
"dtg": "2025-09-29T18:00:00Z",
"hc_struct": 0.81,
"fme_struct": 0.72,
"pl_struct": 0.67,
"dc_struct": 0.03,
"ppi_live_norm": 0.92
}This example shows a single structural snapshot for a hypothetical storm: a normalized structural coherence score, energy-like change metrics, phase alignment, structural trend, and an aggregate readiness measure. The actual schema is versioned and documented in the SDK.
PTEM is delivered as a cloud service with versioned models and a governed SDK. We do not provide on-prem or source-code deployments — the engine is operated as a managed, trade-secret-protected system.
Key features
Structural Coherence Engine
Captures changes in a storm’s internal organization using a governed set of structural metrics. Designed to complement—not replace—existing hazard models.
PPI (Priming Index)
A structural priming signal derived from storm organization, symmetry, and burst patterns. Highlights periods where storms may be structurally receptive to rapid changes.
Enterprise SDK
Lightweight Python and REST clients for seamless integration into insurance, reinsurance, or research modeling workflows.
Frozen Validation Harness
A 10-season, 6-hour aligned validation dataset enabling rigorous, repeatable scoring and auditability for all PTEM model snapshots.
Who uses PTEM
Built for institutional risk owners
PTEM is designed for reinsurers, carriers, public programs, and modeling teams that need structural visibility into storm evolution.
Reinsurers & carriers
Use structural signals to stress-test portfolios, examine alternative scenarios, and compare PTEM behaviour against existing cat models.
Public agencies & programs
Support planning and communications with a structural view on storm organisation, without replacing official forecasts.
Research & modeling teams
Use the frozen dataset and structural outputs as a benchmark for new models, or as a complementary signal inside broader risk experiments.