# Milliray: Sensor fusion for the small-drone threat

Canonical: https://mudpie.ai/companies/milliray/
Breadcrumb: [Home](https://mudpie.ai/) / [Companies](https://mudpie.ai/companies/) / [Milliray: Sensor fusion for the small-drone threat](https://mudpie.ai/companies/milliray/)
Author: Ali Abouelatta (https://mudpie.ai/authors/ali-abouelatta/)
Published: 2026-09-19
Updated: 2026-09-19
Research type: Company profile
Method: Company and accelerator sources checked 2026-09-19. Product claims are attributed to their sources; this is research, not a hands-on product trial.

Milliray builds millimeter-wave radar and sensor systems to detect and track small drones. It fits airports, critical infrastructure, defense and venue operators where low-signature drones create a security problem and false positives make a conventional alert stream unusable.

## What it does

[Milliray’s current site](https://www.milliray.com/) describes a sensor stack that combines millimeter-wave radar, camera and acoustic inputs to detect, track and classify small UAVs. It can run as a standalone site or as a distributed network, with onboard compute for low-latency detection in all-weather environments. The listed targets range from small quadcopters to autonomous swarms.

The product decision is about the first detection layer. Milliray is not presenting a generic computer-vision model that can be trained on a new camera feed. It is selling hardware and sensor fusion designed around low-signature drones, clutter and perimeter coverage. The current site describes airport, critical-infrastructure and defense deployments with different operating constraints, so a buyer needs a site-specific test rather than a generic “drone detection” demo.

The company’s [YC launch](https://www.ycombinator.com/launches/PUU-dronetector-high-resolution-radars-to-detect-small-drones) describes radar integrated with camera and acoustic arrays and says the system can operate standalone or as part of a network. It also lists support from UK Defence and Security Accelerator, NATO DIANA and the Royal Academy of Engineering. Those are public program and company claims, not an independent detection-rate or false-positive benchmark.

## Founder context and tradeoffs

The YC profile identifies Matthew Moore, Thomas Doherty and Jordina Frances de Mas as founders. Their public backgrounds include millimeter-wave radar, atomic and laser physics, automated reasoning and machine learning. That technical mix is directly relevant to the sensor stack.

Pricing is not public. A buyer should ask about detection range, birds and clutter, weather, maintenance, spectrum, integration with existing command systems, data retention and response policy. Detection is only the first part of counter-UAS operations; it does not by itself authorize or execute a response.

## Editorial take

I would shortlist Milliray for a site with a defined low-altitude drone threat and an existing security operation that can run a controlled evaluation. The proof should be a known perimeter, known clutter and a shared definition of a useful detection. If the problem is only occasional visibility, a full sensor stack may be more than the site needs.

## Quick facts

| Field | Sourced detail |
| --- | --- |
| Product | Millimeter-wave radar, camera and acoustic sensor stack for small drones |
| Buyers | Airports, critical infrastructure, defense, venues and VIP-protection teams |
| Deployment | Standalone sensor or distributed network; all-weather claim on homepage |
| Pricing | Not publicly listed |
| Main gate | Range, clutter, false positives, integration and response policy |

## Sources checked

| Source | Checked |
| --- | --- |
| [YC profile](https://www.ycombinator.com/companies/milliray) | 2026-09-19 |
| [Milliray homepage](https://www.milliray.com/) | 2026-09-19 |
| [DroneTector launch](https://www.ycombinator.com/launches/PUU-dronetector-high-resolution-radars-to-detect-small-drones) | 2026-09-19 |

## Cohort context

Milliray is listed in Winter 2026. In our 2026-09-18 directory snapshot, 28 of 199 listed companies in that cohort have YC’s primary industry label Industrials (14.1%). This is a current-directory comparison, not an original intake count or a performance ranking. [Nine-cohort dataset](https://mudpie.ai/research/yc-cohorts-2026-09-19.json).

## Public website snapshot

Observed 2026-09-19T16:20:18.774Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.

| Signal | Homepage observation |
| --- | --- |
| Product description metadata | Observed |
| Canonical link | Observed |
| H1 or H2 heading | Observed |
| Typed structured data | Observed |
| Docs/developer link | Not observed in this response |
| Pricing link | Not observed in this response |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |

[Public observations](https://mudpie.ai/research/yc-homepage-links-2026-09-19.json) · [Collection method](https://mudpie.ai/research/yc-homepage-methods/README.md). Missing links here do not establish that a capability or file is absent elsewhere.


## Author disclosure

I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.