Live feed Sensing geohazards

Real-time intelligence for a moving planet.

AEI turns modern geophysical data and AI into live insights on the ground beneath critical infrastructure for climate and natural hazard decisions.

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Fiber sensing/Seismic/Geophysical networks/Satellite
01 / What we can do today

Where landscape and big infrastructure meet.

We work with operators whose assets sit on moving ground. Understanding the Earth is central to safety, cost, and climate risk.

Dam and downstream river corridor used to represent tailings risk monitoring
Fiber route
Downstream community
site imagery

Mining

Slope stability, tailings dams, and subsidence monitored from inside the ground, not just from the air.

Aerial view of a hyperscale data center building surrounded by open farmland site imagery Photo: Chad Davis / CC BY 2.0

Data centers

Ground conditions, seismic exposure, and perimeter integrity for the most siting-sensitive builds in the world.

Power transmission infrastructure site imagery

Energy & utilities

Pipelines, transmission, and linear assets watched continuously along their entire length.

Urban skyline representing climate risk planning site imagery

Urban & climate risk

Subsidence, groundwater, and hazard exposure for cities adapting to a changing climate.

02 / The platform

We measure the Earth beneath what you build.

Ground-based sensing is our edge. We leverage dense geophysical networks and satellite data fused with physics-based AI models to provide actionable insight for the people managing critical assets.

01

Geophysical sensing & data fusion

Geophysical networks including seismic and fiber sensing combine with satellite data to build one coherent picture of the landscape over time.

02

Physics-grounded models

Earth physics, not curve-fitting alone. Models that explain observations and hold up under scrutiny.

03

AI-powered analysis

Machine learning resolves messy, high-volume geophysical data into patterns and insight operators can act on.

04

Transparent agentic pipelines

Robust, auditable AI pipelines that show their work from raw signal to action.

03 / The pipeline

From noisy signal to a decision you can defend, powered by GeoAI.

Field data is messy, disaggregated, and incomplete. Our AI pipelines are agentic but never opaque. AEI gets the most out of the data and infrastructure you already have while staying grounded in earth science, robust to noise, and auditable from end to end.

STEP 01

Sense

Continuous data from ground networks and satellites streams in.

STEP 02

Fuse

Sources are aligned in space and time into one coherent record.

STEP 03

Model

Physics and AI-based models infer what's happening beneath the surface.

STEP 04

Analyze

Results render as live analytics and imagery of the ground and its behavior.

STEP 05

Decide

A traceable alert or assessment, with the evidence attached.

Transparent

Every result traces back to the raw signal that produced it.

Uncertainty-quantified

Confidence travels with the answer, never a number without a margin.

Robust to noise

Built for real field conditions with gaps, drift, and bad sensors included.

Continuously evaluated

Evaluations are a core principle, not an afterthought. We measure what we ship.

AI is the instrument, not the decision-maker. We build augmented intelligence that keeps humans centered while providing deep geophysical reasoning in language people can act on. AEI lowers the barrier between science and action, helping teams use complex data instead of black-boxing it.

04 / Capabilities

Many sensing modalities, one model of the ground.

Our data streams include seismic arrays, fiber sensing, and satellite imagery, with room for additional geophysical networks and integration with existing sensors.

Offshore distributed acoustic sensing waveform data from Shi, Ni, Denolle et al.
Seismic

Ground motion & micro-seismicity

Dense arrays catch the tremors, slips, and vibrations that precede failure.

Seattle SoDo coastal industrial waterfront used to represent land subsidence monitoring
Geodeticv2.0 · with partner

Surface deformation & strain

Millimeter-scale movement of the ground surface, including subsidence, uplift, and creep. Joining the platform in v2.0 through a sensing partner.

Fiber optic cable installation for distributed sensing
Distributed acoustic sensing

Every meter of fiber, a sensor

Existing fiber routes become continuous acoustic arrays with kilometers of coverage and no new hardware in the ground.

Satellite-style landscape view
Satellite

Landscape-scale context

Optical and radar imagery ties local sensing to wider terrain with broad coverage and change over time.

05 / The difference

Most tools see half the picture. We model the whole system.

Infrastructure is usually monitored either from the ground or from space. AEI brings both views together, adds physics and machine learning, and turns the combined picture into decision-ready insight. That's why our picture holds together where single-source, data-only tools fall apart.

The status quo
-Ground sensors or satellite, rarely fused
-Purely data-centric, with no physical model of the Earth
-Siloed data streams and siloed analysis
-Insight locked behind deep, scarce expertise
-Black-box outputs that are hard to audit or trust
-Backward-looking snapshots and static reports
The AEI approach
+Ground and satellite, fused into one coherent record
+AI-based models grounded in Earth physics
+Uncertainty quantified on every output
+Transparent, continuously evaluated AI pipelines
+Expertise translated into decision-ready language
+Living models that assimilate new data and project forward
06 / Team

Team

AEI was founded out of the University of Washington's FiberLab, where the novel research behind our platform continues every day.

Stephanie Olinger

Stephanie Olinger, PhD

Cofounder · Operations Lead
PhD, Harvard · UW FiberLab

Cofounded AEI to bring modern geophysical sensing to real-world problems. Leads fundraising, partnerships, and commercialization of AEI's innovative solutions.

Prof. Brad Lipovsky

Prof. Brad Lipovsky

Cofounder · Sensing Guru
PhD, Stanford · Professor, University of Washington

Principal investigator of UW's FiberLab, applying novel fiber sensing techniques to geophysics. Leads geophysical data analysis, physics-based modeling, and technical strategy.

Prof. Marine Denolle

Prof. Marine Denolle

Cofounder · AI Visionary
PhD, Stanford ·Professor, University of Washington Professor, Harvard (Former)

Builds AI-powered big-data pipelines to characterize geophysical systems. Leads AI integration, software and model development, and data-processing strategy.

07 / Contact

Let's look at your ground.

Tell us about your site or network and we'll get back to you to scope a demo. Partners, operators, and investors welcome.