Dataset Factory for Spatial Event AI
Simulation-based infrastructure that auto-generates clip-level training datasets for AI that understands events in personal spaces.
THE PROBLEM
Spatial Event AI Fails
Because of Data, Not Technology
Every home is different. Events like mail arrival or laundry completion are state changes, not single frames. Models break every time the environment changes, and manual data collection does not scale.
Space Understanding
Define zones and regions of interest before generating any data
Event-Centric Data
Clip-level datasets with event start/end timelines, not frame annotations
Simulation-Based
Thousands of event variations through simulation, no manual collection
LEADERSHIP
Steve Hwang
Chief Executive Officer
Hans
Chief Technology Officer
Jin
Chief Operating Officer
HOW IT WORKS
Spatial Event AI Factory Pipeline
Our platform understands the space first, defines events within it, then automatically produces and validates training datasets at scale. Four stages, fully automated.
Personal Space Zoning (DT-lite)
Takes a single camera feed and segments your space into functional zones, creating a lightweight digital twin that defines where events can happen.
Event Scenario Generation
Creates thousands of realistic event scenarios by randomizing lighting, occlusion, layout, and sensor noise for robust AI training.
Event Clip Dataset Production
Automatically cuts clips at the event level with pre/post-roll context, producing timeline-structured datasets with precise start/end markers.
Validation & Benchmarking
Checks spatial alignment, scores dataset difficulty, and packages everything into benchmark-ready formats for fair model comparison.
WHY IT MATTERS
Why This Changes Everything
Personalized AI, Fast
Simulation reproduces environment-specific conditions automatically. Build event AI for any space without manual data collection.
Event-Level Datasets
Clip-level datasets with start/end timelines. Train models to recognize when things happen, not just what is visible.
Reproducible Pipeline
Every run is versioned. Same seed, same config, same result. Iterate on data quality with the same rigor as code.
Perception-Only Labels
Labels based only on what a camera can observe. Models trained on our data work where sensors have noise and occlusion.
USE CASES
Where Spatial Event AI Makes a Difference
From smart homes to research labs -- training data for AI that understands what happens in physical spaces.
Smart Home
Mail arrival, laundry completion, objects left at the door. Everyday events that matter but are hard to train AI for.
Everyday event detection
Home Robotics
Home robots need spatial understanding and event recognition. Our datasets train their perception systems.
Robot spatial perception
Facility Operations
Visitor entry, package delivery, inventory movement. Reliable event detection for offices and small facilities.
Operational monitoring
R&D / Benchmark
Reproducible, difficulty-scored datasets for fair model comparison and event recognition research.
Benchmark datasets
Simulation-based dataset generation that scales to any space, any event, any condition. Powered by a Rust-based reproducible runtime.
GET IN TOUCH
Partner With Nuvreon
Whether you are an investor, enterprise partner, or technology collaborator, we welcome conversations about the future of intelligent systems.
Corporate Structure
Delaware C-Corp
Headquarters
United States