The long tail sits unindexed in your drive logs
Petabytes of drive data hold the construction zones, occlusions, and rare agents your model needs, and no one can find them.
Annotation and scenario evaluation for AV stacks – from 3D point clouds to the rare events that decide a release.
Talk to usThe conditions that separate a durable data operation from a one-off labeling project.
Petabytes of drive data hold the construction zones, occlusions, and rare agents your model needs, and no one can find them.
An object that silently switches identity at frame 400 poisons every prediction and planning model trained downstream.
Release gates need scenario-level evidence, and aggregate mAP curves don’t tell a safety board anything.
Synchronize camera, LiDAR, and radar labels across complete sequences.
Mine drive logs for rare scenarios before annotation spend begins.
Audit tracking, geometry, and 2D–3D links across full clips.
Measure each perception release against a fixed, human-graded scenario suite.
Curate the scenes that matter, label them to sequence-level consistency, and let the evals pick what comes next.
Sensor rig, coordinate frames, object taxonomy, and QA thresholds agreed with your perception team before calibration.
Target scenarios mined from your drive logs, sampled by constraint rather than chance, and queued for annotation.
Camera-LiDAR-radar labeling with sequence-level consistency checks and per-class QA reporting on every batch.
Each release is graded on the same scenario suite. The failures define the next curation target list.
Curation, annotation, QA, and evals run on one platform, auditable at every step.
Bring one scenario classPlatform, experts, and workflows – unified in one secure infrastructure.