BADAS 2.0 predicts collisions at 99.4% precision trained on real roads,
not simulation.
The same real-world data engine is now open for your models.
Why pure simulation leaves your stack vulnerable
The rare, messy, unstageable moments that break autonomy never appear in synthetic data.
Work zones shift and hazards appear weekly your stack is navigating a world that no longer exists.
Abstract simulation scores don't tell a regulator, or you, whether the stack is actually safe.
Nexar runs a network of 350K+ connected edge cameras that capture real driving as it happens not staged, not simulated.
On-device edge AI filters the noise and surfaces only the critical events, which our data engine structures and enriches into AI-ready datasets.
You can target the exact edge cases you need by geography, weather, or behavior, and get them delivered annotated.
It's the difference between training on a model of the world and training on the world itself.
Outperformed Cosmos on identical dataset parameters with 91x fewer parameters.
Book a call, tell us the scenarios your stack struggles with.
We target real-world data on demand by geography, weather, and behavior.
The data engine structures and AI-enriches it into training-ready datasets.
Validate your stack against 10B+ miles of ground truth with Nexar APEX.
Deploy with confidence and keep a live feed of the road as it changes.
Nexar exists on one conviction: true autonomy will be trained on reality, not simulation. We operate the world's largest open video driving dataset, built from a live network of edge cameras on real roads capturing the long-tail moments other systems never see.
That foundation is why partners like NVIDIA, Waymo, and Motional build on Nexar, and why Yann LeCun joined our board of directors. Nexar is the infrastructure layer turning the real-world edge into deployable intelligence.
Our data is captured from real roads by a live sensor network the unstageable long-tail events simulators can't reproduce. Simulation is a training tool; reality is the proving ground.
Yes. Collection-on-demand lets you define scenarios by geography, weather, and behavior, and we proactively target and deliver that data, annotated and AI-ready.
BADAS 2.0 beat NVIDIA's Cosmos on the same data at 91x fewer parameters, at 99.4% precision. We invite partners to review the methodology and benchmark against their own stack.
Structured, high-fidelity video and metadata, AI-enriched into context-rich annotated datasets usable directly for model training and simulation input.
A technical conversation about your use case and the data or validation you need no pitch deck. You leave knowing exactly how Nexar's data engine or APEX would fit your stack.
Talk data and deployment with the Nexar team.
[placeholder Owen to supply Calendly scheduling link]