Union Pacific moves America forward, serving 23 western states across 32,000 miles of track. With Claude AI, transform rail operations through intelligent automation, predictive insights, and operational excellence at scale.
Maintain 32,000 miles of track with predictive maintenance and real-time monitoring. AI agents process millions of wayside detector readings to predict failures before they impact operations.
Optimize network velocity, reduce dwell time, and improve asset utilization. Claude analyzes historical patterns and real-time data to recommend operational improvements.
Maintain industry-leading safety standards with automated inspection systems, hazmat monitoring, and compliance verification. Achieve 99.99% derailment-free operations.
Maximize efficiency from your $10M daily infrastructure investment. AI-driven insights identify opportunities to reduce fuel consumption, optimize crew scheduling, and minimize equipment downtime.
Reduce carbon emissions through route optimization, fuel efficiency improvements, and strategic locomotive deployment. Meet sustainability commitments while maintaining service excellence.
Provide real-time shipment visibility, proactive delay notifications, and intelligent customer support. Serve 7,300 communities with transparent, responsive communication.
Claude excels at processing complex operational data, regulatory requirements, and multi-system integration—perfect for the demands of Class I freight operations.
Deploy specialized AI agents to automate critical rail operations, from predictive maintenance to customer service. Each agent operates autonomously while integrating seamlessly with your existing systems.
Challenge: Manual inspection of thousands of railcars and locomotives leads to unexpected failures and costly downtime.
Solution: Claude analyzes 35M+ daily wayside detector readings, vibration sensors, thermal imaging, and maintenance logs to predict component failures 2-4 weeks in advance.
Impact: 45% reduction in unplanned maintenance, 30% decrease in equipment downtime, $50M+ annual savings.
Challenge: Track inspections require significant manual effort, with potential for human error in identifying defects.
Solution: AI agents process track geometry data, ultrasonic testing results, and visual inspection images to automatically identify and prioritize track defects.
Impact: 99.99% defect detection accuracy, 60% faster inspection cycles, improved safety compliance.
Challenge: Complex network with competing priorities—balancing speed, fuel efficiency, track capacity, and customer commitments.
Solution: Claude analyzes historical traffic patterns, weather forecasts, track conditions, and customer schedules to recommend optimal routing and prioritization.
Impact: 12% improvement in network velocity, 8% reduction in fuel consumption, improved on-time performance.
Challenge: Equipment failures, weather events, and track obstructions require rapid coordination across multiple teams and systems.
Solution: AI agents automatically detect incidents, assess impact, coordinate response teams, and provide real-time updates to affected customers.
Impact: 40% faster incident resolution, improved customer satisfaction, reduced operational disruption.
Challenge: Complex crew scheduling across 23 states with Hours of Service regulations, qualification requirements, and dynamic operational needs.
Solution: Claude optimizes crew assignments considering regulatory compliance, skill requirements, location, and operational priorities in real-time.
Impact: 25% reduction in crew deadhead, improved compliance, enhanced crew satisfaction through better work-life balance.
Challenge: 7,300 communities expect real-time shipment visibility, proactive communication, and rapid issue resolution.
Solution: AI-powered customer service agents provide instant shipment tracking, delay predictions, and automated issue resolution 24/7.
Impact: 70% reduction in customer service inquiries, improved customer satisfaction scores, 24/7 support availability.
Click each step to see how Claude processes real-time sensor data to prevent equipment failures:
Claude continuously ingests data from wayside detectors (hot bearing, dragging equipment, wheel impact), onboard locomotive sensors, maintenance records, and weather conditions across your 32,000-mile network.
AI models analyze 35M+ daily sensor readings to identify subtle patterns indicating bearing wear, wheel defects, brake issues, or structural fatigue—often weeks before human-detectable symptoms appear.
When anomalies are detected, Claude assesses severity, failure probability, and operational impact to generate prioritized maintenance alerts with specific component recommendations and urgency levels.
High-priority issues automatically generate work orders in your maintenance system, including equipment location, failure prediction timeline, recommended parts, and suggested maintenance windows.
Claude learns from maintenance outcomes to improve prediction accuracy over time. Each repair validates or refines the model, creating a continuously improving system tailored to your fleet characteristics.
Claude connects seamlessly to your existing infrastructure:
Accelerate software development for internal tools, integrations, and automation systems. Claude Code helps your engineering teams build faster, maintain better, and innovate more.
Build connectors and APIs to integrate decades-old mainframe systems with modern cloud platforms. Claude understands COBOL, legacy protocols, and modern REST APIs equally well.
Create ETL pipelines to process sensor data, maintenance logs, and operational metrics. Transform raw data into actionable insights for decision-making.
Automated security scanning, compliance verification, and code quality checks. Ensure all software meets FRA cybersecurity requirements and internal standards.
Rapidly prototype and build custom dashboards, mobile apps for field operations, and automation tools for dispatchers and maintenance crews.
Automatically generate technical documentation, API references, and maintenance guides. Keep documentation current as systems evolve.
Quickly diagnose production issues, analyze log files, and recommend fixes. Claude understands complex system architectures and failure modes.
Challenge: Integration of 1,000+ wayside detectors generating data in different formats across multiple vendors.
Solution with Claude Code:
Result: Delivered in 3 weeks vs. 6 months estimated with traditional development. 100% test coverage, zero production issues.
"Create a Python service to parse hot bearing detector alerts and update our maintenance system"
Scaffolds project structure, writes parsing logic, adds error handling, creates tests, generates documentation
Request changes: "Add retry logic for API calls" or "Handle this edge case"—Claude updates instantly
Claude generates comprehensive tests, creates CI/CD pipeline, and prepares deployment documentation