Case Study: American Railroad Company achieves 90% asset maintenance accuracy with Tiger Analytics

American Railroad Company achieves 90% accuracy in asset maintenance with Tiger Analytics

The customer, an American railroad company, faced challenges in automating its asset maintenance and fault detection processes. Vendor Tiger Analytics leveraged its expertise to address this by developing advanced deep learning models using computer vision techniques.

Tiger Analytics implemented a solution that automated asset maintenance and achieved a remarkable 90% accuracy rate in identifying defects. The results included the successful detection of specific faults such as track repair needs, missing bolts, and wheel defects with tremendous accuracy for the railroad company.