Autonomous Fleet & Logistics Audit AI
Computer vision inspection pipeline replacing manual vehicle assessments with automated, auditable condition scoring.
Challenge
Manual inspections suffered from human variance, slow turnaround times, and fragmented record-keeping, delaying billing cycles and masking chronic vehicle damage.
Architecture
- YOLOv8 and Detectron2 models fine-tuned on proprietary fleet imagery for automated damage segmentation.
- Real-time frame ingestion feeding a GPU-accelerated FastAPI inference cluster.
- Audit telemetry written to an immutable inspection ledger and exposed via authenticated APIs to operator consoles.
- Automated historical diffing comparing current inspection states against baseline vehicle records.
Outcome
- Inspection telemetry generated and logged in under three seconds.
- Audit processing efficiency improved by 45% with a 60ms latency reduction over legacy pipelines.
- Uniform, objective damage scoring across all regional inspection sites.
