Surface and component anomalies
Isolate corrosion, cracks, erosion, missing hardware, and other component-level conditions across asset types.
Independent infrastructure for energy inspection robotics
Turn every inspection run into data the next model can learn from.
Connect thermal, RGB, LiDAR, and telemetry data in one traceable loop—from inspection capture to model-ready dataset releases.
One operating record from inspection mission to versioned dataset release.
MCAP + ROS
LiDAR + point clouds
Multi-camera video
Telemetry + trajectories
One operating loop
The inspection mission is only the beginning.
Replace fragmented handoffs with a traceable path from synchronized inspection capture to the next model-ready dataset release.
- 01
Ingest synchronized inspection missions
Bring MCAP, thermal and RGB video, point clouds, GNSS, IMU, and asset events together without stripping away time or source context.
- 02
Curate the evidence that matters
Search and slice by asset, component, anomaly, weather, viewpoint, and sensor condition to assemble the scenarios the next training cycle needs.
- 03
Build defensible ground truth
Combine model assistance with human 2D, 3D, and temporal review, then apply the quality gates each release requires.
- 04
Publish a versioned release
Freeze the manifest contents and source origins, attach declared rights metadata, then publish an immutable revision that the loader resolves for training and evaluation.
Scenario intelligence
Find the evidence that changes model behavior.
Turn long inspection runs into focused training slices while preserving the sensor, asset, and operating context around every event.
Thermal anomalies and hot spots
Compare thermal signatures with aligned RGB, location, asset, and calibration context.
Occlusion, glare, and weather
Curate the viewpoints and environmental conditions where inspection models lose confidence.
Durable dataset identity
Ship a release your inspection stack can reproduce.
Treat every training set as a governed artifact with a stable address—not a folder passed between teams.
- Friendly dataset reference plus an immutable canonical revision
- Manifest digest, object count, total size, and source origins
- Declared rights document and access terms attached to the revision
- Published state and revision identity returned through the loader
Dataset release manifest
Versioned- Dataset
- energy/asset-inspection
- Release
- v12
- Origin records
- primary / avala · calibration / avala
- Declared rights
- Attached
- Revision state
- Published
energy/asset-inspection@v12Built for inspection autonomy
One data system across the energy inspection program.
Keep transmission, wind, solar, and industrial inspection work on the same dataset and quality foundation.
Transmission and distribution
Curate towers, lines, insulators, connectors, and clearance zones from synchronized aerial and ground missions.
Wind energy inspection
Build temporal and multi-view datasets for blade surfaces, towers, nacelles, and changing operating conditions.
Solar asset inspection
Align thermal and RGB evidence for panel, string, tracker, and site-level inspection models.
Industrial and pipeline inspection
Review corrosion, leaks, equipment states, and hard-to-reach asset conditions across rover, drone, and fixed-sensor data.
Start with one model bottleneck
Map the inspection-data release your program needs next.
Bring your sensor stack, current workflow, and target behavior. Leave with a scoped path from inspection missions to a versioned dataset.