What we do
One product, and two services around it. Each starts from the data and the test set you already own, and each ends with a number on that test set.
01 / Product
Rare episodes
We generate the episodes your fleet meets once a year and your training set has never seen: cut-ins, crossings, obstacles, sensor and actuator failures, and the weather that grounds a drone. Each episode is set in a real scene from your captures and rendered photoreal. Geometry and labels stay outside the generative model.
- You hand over
- ROS bags, MCAP logs, video, point clouds, calibration files, maps, and labels.
- You get back
- Rare episodes with lineage, and a measured result on your real test set.
Generate rare episodes
02 / Service
Data quality control at scale
Most training and test sets are checked on samples, if at all. We run quality checks over the whole set: duplicates, label errors, missing and corrupt frames, calibration drift, coverage gaps, and leakage between train and test. We built these checks to gate our own pipeline; we now run them over yours.
- You hand over
- A training set, a test set, or both, in your native formats.
- You get back
- A per-sample audit: what is wrong, where it is, and what to fix, drop, or recollect.
Audit our data
03 / Service
Perception engineering
Our engineers work inside your team on the perception layer: target detection, context extraction (what the target is doing), and prediction (what it is about to do). We start from your model and your data, find where it fails on your test set, and collect or generate the data that closes the gap.
- You hand over
- Your current model, your data, your test set, and an engineer to work with.
- You get back
- A measured improvement on your test set, and the data that produced it.
Improve our perception model
Explore rare-event examples