
Max Duursma
Leads Cornu's company strategy, partnerships and business development.
Cornu builds world models that help autonomous systems perceive, understand and navigate the environments around them.
A visualisation of how vessels, bridges and waterways become a shared spatial model.
Cornu brings sensor data, charts and past observations into one world model. Updated as conditions change. Built for decisions on the water.
Detect and track vessels, infrastructure and the shoreline across sensor streams.
Resolve positions, clearances and navigable space in a common frame.
Keep a persistent view of what is here, what has changed and what came before.
Anticipate vessel motion, potential conflicts and conditions along the route.
Support the crew today. Build towards automated control on the same foundation.
Camera, radar & AIS Position & telemetry Environment, charts & history
Cornu's first platform gives inland vessels a continuously updated understanding of the environment around them — bridges, locks, traffic, channel and shoreline, in daylight and at night.
Bridge Watch measures the opening ahead, compares it with your vessel’s air draft, and gives the crew a clear margin before the approach.
Mast-mounted sensing and onboard compute, calibrated to your vessel.
VESSELS ONLINE · 001
Every Cornu deployment can improve the intelligence available to the wider network. A bridge is not observed once. Over a year of traffic it is observed thousands of times, in every light and water level.
A chart describes where things were. Cornu is built to describe what exists now, how it has changed, and what is likely to happen next.
A concept view of vessels, infrastructure and movement connected in one spatial model.
Step onto the bridge of a simulated 100-metre inland vessel. Explore how Cornu turns imperfect camera, radar, LiDAR and AIS observations into a persistent model of the waterway.
Launch simulation ↗︎Explore six simulated scenarios
Marine-grade enclosures and an onboard compute unit sized for continuous operation. Installed per vessel, calibrated per hull.
Models trained on inland waterway conditions rather than road scenes — reflection, glare, fog, night operation, low-contrast water surfaces.
A shared representation that persists between passages and between vessels, updated as observations arrive and reconciled against charts, water levels and notices.
Warnings, clearance and timing support, route intelligence and fleet-level analytics — delivered onboard and to shore.
Maritime products sit on top of a general architecture. Other domains reuse the layers beneath rather than starting again.
Waterways are the beginning. The problem underneath is the same everywhere: a machine has to build and keep an accurate understanding of the space it operates in.
Perception, navigation intelligence and pilot deployments with commercial operators.
Fixed observation points and change detection along quays, locks and bridges.
The same spatial layer applied to machines operating in structured industrial space.
Shared world-model infrastructure for vehicles and autonomous platforms.
Consent-based human observation networks contributing to compatible representations.
Labels are literal. Only work marked in deployment is available to customers today.
Based in Groningen, the Netherlands, Cornu is built by a founding team working across technology, business and marketing. We test on working vessels, in the conditions the system has to survive.

Leads Cornu's company strategy, partnerships and business development.

Leads Cornu's technology, engineering and product architecture.

Leads Cornu's marketing, communications and brand development.

Supports Cornu's growth as an investor and strategic co-founder.
University of Groningen
AutoMooring SolutionsFrom perception to the systems that connect it all. Find your place in the team building intelligence for the physical world.
View vacanciesHave a question, an idea or something you would like to discuss? Get in touch about our products, a collaboration, or anything else. We would like to hear from you.