Reconstruct every mile, frame by frame.
LiDAR, camera, IMU and brake-by-wire on one timeline — replayable against ground truth, from test track to public road.
Every disengagement, explained.
When the scene, the signals and the stack’s decisions live on one playhead, triage stops being archaeology.
Scrub the whole scene
Point cloud, camera, IMU and actuation snap to the same instant — with detections and masks overlaid on the frame.
Replay the road into sim
Feed the exact recorded scene into simulation and run the new stack against it before it drives again.
Mine the fleet for edge cases
Query every mile for the same scenario signature and turn one incident into a coverage set.
One platform, from first prototype to fleet.
The record built in development carries into validation and operations — nothing starts from scratch.
Develop
- Stream track testing and shadow-mode logs into one timeline.
- Compare stack versions on identical scenes, decision by decision.
- Keep sim runs and road data in the same record.
Validate
- Run scenario suites against every release candidate.
- Codify safety criteria once; every mile is scored against them.
- Build regression libraries from real disengagements.
Operate
- Capture the deployed fleet continuously, within bandwidth budgets.
- Surface off-nominal behaviour as it happens, fleet-wide.
- Trend sensor degradation before it becomes a fault.
What a run looks like in Phloem.
A shadow-mode drive as it lands: point cloud, forward camera, IMU and the vehicle bus, already on one playhead.
The point cloud, the camera frame, and what the stack believed — detections and masks overlaid — scrubbed together at the moment of disengagement.
Native to the AV stack.
First-class ingest for the formats, protocols and buses this work already runs on — and the wider ecosystem behind them.
And anything else with an SDK, a topic, or a recorded log.
What teams get back.
Triage opens on the reconstructed scene, not on a directory of logs from three recorders.
The same recording that explains an incident becomes the scenario that prevents the next one.
Miles that make the stack smarter.
Every mile driven is training signal. Keep all of it, in sync, in one place.