Matter Intelligence

The insurance industry has always been in the business of understanding the physical world: what is built where, what it is made of, how it is changing, and what risks are emerging before they become losses. Yet much of that understanding still depends on indirect signals: property records, inspections, historical claims, models, and imagery designed primarily for human eyes.

Matter is building a new way for machines to understand the material world directly.

At the core of our innovation is a novel advanced sensor originally designed for scientific missions to other planets. That technology was built to answer a fundamental question: what is something actually made of? By measuring information across the electromagnetic spectrum, rather than relying only on the red, green, and blue channels visible to the human eye and typical aerial imagery, the sensor can reveal material properties that conventional imagery cannot, while simultaneously collecting color, shape, and temperature.

Matter is adapting that capability to generate material intelligence about the Earth at scale, and combining it with AI models that can reason over those measurements.

That distinction matters because many of the things insurers care about are fundamentally material questions. What is this roof made of? How old or degraded does it appear to be? Has it experienced hail or thermal stress? Is vegetation changing in a way that increases wildfire exposure? Has a structure, parcel, or surrounding environment materially changed since it was last evaluated? How do these material properties relate to risk and cost?

Today, answering those questions often requires stitching together incomplete datasets or dispatching people into the field. Matter's goal is to make increasingly sophisticated physical analysis available on demand, at scale.

Our platform is designed around a simple interaction: an analyst specifies what they want to understand about a place or portfolio, and Matter determines how to answer it using sensor measurements, open source data, learned models, and physical reasoning. A request might be straightforward, such as measuring the roof area of every building in a region, or significantly more complex, such as identifying roofing materials, assessing condition, or detecting evidence of damage across thousands of properties.

Underlying that experience is a broader ambition. We believe the next generation of AI systems will need more than language and conventional imagery. To reason reliably about the physical world, models need access to measurements that describe its actual material state.

For insurance, that creates an opportunity to move from periodic and proxy-based understanding toward persistent, measurable intelligence about exposure and change. Better information can improve underwriting, portfolio monitoring, catastrophe response, claims triage, and ultimately the alignment between risk and price.

Matter is building the sensing and intelligence infrastructure to make that possible: bringing technology developed to understand the material composition of other worlds to bear on understanding this one.

We are excited to work with insurers who want to explore what becomes possible when machines can see more of the physical world than what was previously possible.