Edge AI For The Physical World
Born at the edge. For everyone.
The Company
Who We Are
DEMOS AI LAB designs and builds edge-based and physical AI models — deploying machine learning directly on edge hardware to sense, predict, and act on real-world physical systems. Small, verifiable models — designed and trained from the ground up for continuous sensing — that run entirely on-device: no cloud dependency, no latency, no single point of failure — operating precisely when and where connectivity is most likely to fail..
Our research advances what AI can do at the edge — conducted alongside leading university laboratories and pursued through federal research programs, with results built to be verified, published, and deployed.
Our founders combine this research foundation with decades of large-scale U.S. government operations, backed by veterans of the Intelligence Community and the Pentagon. Across three markets, we are building on the same foundation.
The future of AI is not bigger models concentrated in data centers. It is small, honest models distributed across a billion devices — everywhere the real world happens.
How We Work
Everything we build serves one goal: small models with outsized intelligence. Two capabilities make that possible. Data curation: proprietary, expert-vetted datasets built for the problems that demand edge AI — high-quality data from the physical world, where every label is confirmed by real-world outcomes. It is this ground truth that lets a small model learn what only large models were thought capable of. Model development: original, domain-specific architectures designed and trained from the ground up for resource-constrained edge hardware, each shipped with rigorous test and evaluation against SME-vetted benchmarks. Better data, smaller models, honest performance — that is the equation.
These capabilities serve three markets:
We Serve Three Markets:
Government & Defense
We build and integrate edge AI for U.S. government and defense missions — small, domain-specific models, from MOS-specific assistants to mission-specific sensing, delivering frontier-class performance air-gapped on commodity hardware in disconnected, contested, and bandwidth-denied environments. Where the cloud cannot go, intelligence still must — from the tactical edge to critical federal infrastructure.
Commercial & Critical Infrastructure
Every system the modern world depends on — power, water, transport, communications — fails the same way: quietly, then all at once. We are building small, domain-specific models smart enough to hear it coming — for grid operators, industrial fleets, and the infrastructure between — starting with the electrical grid.
Our first platform in development, Grid Sentinel, will fuse satellite imagery, weather intelligence, vegetation data, infrastructure sensors, and consumer edge devices into a single on-device prediction engine — telling grid operators what will fail, where, and when. Our first models, trained on the U.S. Department of Energy's EAGLE-I dataset, have demonstrated 93.5% grid predictability before a single proprietary sensor is deployed. As deployments grow, every sensor expands the ground truth that makes every model sharper — a compounding data moat no competitor can replicate without replicating the network. What we prove on the grid extends to every infrastructure system that can be sensed..
Consumer
We are extending physical AI directly to consumers: a planned marketplace of small, domain-specific models — available by subscription or individual purchase — that turn the devices people already own — phones, tablets, computers — into diagnostic instruments. Models small enough to live on a phone, smart enough to tell you what is wrong — identifying likely faults ranked by probability, with calibrated confidence, stating uncertainty honestly rather than guessing. No data leaves the device. The first products are in development now.