Prometheus Physical risk intelligence for insurance and reinsurance
Newsroom / Blog

Field notes from the Earth Intelligence Layer.

Stories, technical deep-dives, and customer perspectives on turning planetary and asset-level data into decisions.

The Next Moat Isn't Data. It's What You Do With It.

Ask any underwriter if they have enough data and the answer is yes. Ask if they trust it enough to make a fast decision, and it gets complicated. The real moat in P&C isn't a data shortage—it's a single source of truth that holds up under pressure.

Of Pixels and Sheep

Discover how Minecraft's open-world environment is transforming visual AI development by providing researchers and developers with an accessible, highly customizable sandbox for training and testing computer vision models at scale.

How Neural Earth Helped SIGMA Actuarial Build a Defensible Captive Insurance Program

When a regulator asks how you're projecting future losses from five claims in 10 years, you need an answer backed by more than your client's own data. Here's how SIGMA Actuarial built a defensible captive insurance feasibility study with Neural Earth.

Why We Built Prometheus: Decision Clarity and Adaptive Response

There is no shortage of data or tools in risk intelligence. What's missing is cohesion. A founder's note on why we built Prometheus to work the way a high-performing risk professional actually thinks.

El Niño 2026 — Part 3: What To Do About It

If NOAA's forecast holds, you have roughly six months before El Niño arrives—more lead time than most carriers get before a major loss year. Here are the five actions to take now, from ENSO-sensitive accumulation views to cat model inputs.

El Niño 2026 — Part 2: Your Regional Risk Map

El Niño is no longer a probability to monitor—it's a developing event at 98% odds. Here's the territory-by-territory peril breakdown for a 2026 El Niño, from California debris flows to Gulf Coast river flooding.

El Niño 2026 — Part 1: The Signal You Cannot Ignore

NOAA issued an El Niño Watch in March 2026. This isn't a weather post—it's an exposure management post. Here's what the signal means for your peril map.

How Neural Earth Turns Unknowns Into Decision-Ready Insight

In the property insurance market, the most dangerous risk is the one an underwriter doesn't know exists. Here's how Roosevelt Road Specialty solved the SOV Problem with Neural Earth.

GeoAI-Powered Platforms

Transforming situational awareness with data fusion. How GeoAI turns fragmented environmental, asset, and infrastructure data into unified, near-real-time, explainable intelligence for critical decision-making.

We Raised $9M+. Here's Why It Matters.

We closed over $9M in an oversubscribed Seed round to accelerate our GeoAI decision intelligence platform. A founder's perspective on what we're building, why it matters, and what comes next.

Decision evidence

An illustrative record for the pre-bind exposure check. This is a proposed interface, not a live model output.

EVD · EXAMPLE-P0418Review
Decision record
EXAMPLE-P0418 / Referral required
Input basis
Synthetic location TIV: $18.0M. Synthetic current-area gross TIV: $185.0M.
Geographic scope
5-mile radius around the proposed location. The map screenshot is shown separately; no spatial computation was performed for this example.
Method
Illustrative deterministic arithmetic: 185 + 18 = 203; 203 / 250 = 81.2%; 250 − 203 = 47. Values in USD millions.
Configured rule
Review at utilization ≥ 80%. Breach above 100%. Example cap: $250M. Not a reinsurance treaty provision.
Source status
Illustrative values, not verified source data. No measured model-confidence score is asserted.
Decision authority
Designated exposure reviewer. No automated quote, bind, or external-system write.
Production requirements
Source IDs, observation times, method versions, spatial methodology, deduplication rules, and authorized reviewer records.
Illustrative dataHuman approval retained

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