The data layer for physical AI
datadoo generates photoreal, physics-accurate synthetic data so computer vision teams can train better models - without the cost, delay, or privacy risk of real-world capture.
NVIDIA Inception memberPresented at GTC 2026Based in Málaga, SpainRemote-first teamPrinciples, not platitudes
We started datadoo because we kept hitting the same wall: great models, not enough data. These are the convictions that drive every decision we make.
A decade of synthetic data expertise
Our team has been generating synthetic training data and training neural networks with it for over a decade. We were building this before the industry had a name for it.
Data is the real bottleneck
Compute doubles every year. Models improve every quarter. But training data is still collected frame by frame, labeled by hand, and gated by privacy law. We fix the denominator.
Physics beats pixels
Photorealism is necessary but not sufficient. If light doesn't scatter correctly, if materials don't respond to force, the sim-to-real gap stays open. We simulate physics first and let fidelity follow.
Synthetic data should be verifiable
Every dataset we generate ships with automated quality scores: realism metrics, distribution coverage, and bias checks. If we can't prove it works, we don't ship it.
Built on the NVIDIA platform
Our synthetic data pipeline is powered by the same simulation stack used by the largest autonomous vehicle and robotics programs in the world.
NVIDIA Omniverse
Our pipeline runs on Omniverse and NVIDIA Replicator, the same simulation platform used by the world's largest robotics and AV teams. Full USD scene composition, RTX-accelerated rendering, domain randomization at scale.
Physics-first rendering
Every synthetic image we generate obeys real-world physics — gravity, light transport, material properties. This isn't just visual realism. It's physical accuracy that ensures reliable sim-to-real transfer.
Cosmos-Transfer for domain control
We use NVIDIA Cosmos-Transfer to bridge the visual gap between synthetic renders and target deployment domains. Style-transfer at generation time means zero post-processing and 40% faster pipeline throughput.
datadoo is a member of the NVIDIA Inception Program, which supports cutting-edge startups building with AI and accelerated computing. This gives us early access to NVIDIA hardware, SDKs, and go-to-market support.
Where you'll find us
We present our work at the industry's top conferences - and publish everything we can. Here's where we've been recently.
NVIDIA GTC 2026
Research poster: Detecting Windshield Damage Using Physically Realistic Synthetic Data
View detailsSIGGRAPH 2025
Demo: Real-time SDG pipeline with Omniverse Replicator
NAB Show 2025
Talk: Synthetic data for broadcast quality control and content analysis
Let's build something real
Whether you need synthetic data for your next model or you want to help us build the platform - we'd love to hear from you.