AI Use Cases Maintenance of Fleet & Infrastructure XR-assisted inspections Leverage hands-free extended reality (XR) to guide and document rolling-stock and wayside inspections, improving quality and safety. How the agent works A technician dons smart glasses. The AI agent overlays step-by-step checklists, captures photos/video by voice, timestamps defects, and auto-generates a maintenance report that syncs to the EAM/CMMS. It flags repeat findings and recommends parts and work orders based on historical patterns. AI Vision maintenance for rolling stock Use computer vision and telemetry to detect wear, dents, and component degradation, predicting failures and optimizing shop visits. How the agent works The agent guides standardized image capture in the yard, identifies defect type/severity, estimates refurbishment cost with a rules engine, and schedules the unit into the next available bay—minimizing service disruption. Worker safety & PPE compliance (AI-vision) Use edge AI to enforce PPE and safe behavior for trackside & depot staff—reducing incidents and shutdown risk. How the agent works The agent runs on edge nodes connected to your current CCTV feeds, verifying helmets, hi-vis, gloves, and safety glasses; cross-checking permit-to-work geofences and train movement plans to detect live-track encroachment; recognizing hazardous acts (crossing live rails, walking foul, unsafe climbing, handheld distraction, tools left on track); and pushing instant alerts to radios/Teams while auto-logging timestamped clips to the incident system with privacy safeguards (on-device processing and face masking). AI Use Cases Operation Planning & Scheduling Demand-aware timetable and crew optimization Continuously optimize long-term timetables and crew plans using live ridership, events, and disruption data to balance capacity and cost. For day-of operations, apply advanced heuristic optimization and AI-driven recommendations to automate dispatch decisions. How the agent works The agent ingests APC/AVL, ticketing, events, weather, and disruption feeds to forecast demand and risk. It runs optimization models (timetable/crew blocks for long-term; headways/vehicle swaps for day-of) and simulates scenarios to pick the lowest-cost, on-time plan. Recommendations are pushed to control systems with one-click apply, and the agent learns from outcomes to refine future plans. Disruption response & re-routing Accelerate incident handling across rail and bus networks with decision support. How the agent works The agent detects incidents from CCTV/video analytics, ops data and crowd-source information, predicts knock-on effects, generates alternative routings, short-turns, and bus bridges, and coordinates comms to stations, crew and passengers on dedicated apps. Smart e-Bus Depot Charging Orchestration Use AI to optimize when, where, and how vehicles charge across depots and public hubs—and to predict e-bus availability windows to maximize duty planning and dispatching. How the agent works The agent unifies charger/vehicle telemetry, energy tariffs, depot-readiness targets, and renewable availability into one control layer. It forecasts each bus’s available-forduty window and on-time probability, then orchestrates charging to meet service levels at the lowest cost—reprioritizing sessions in real time and preventing feeder overloads. It proposes duty assignments within range/layover/SOC constraints, writes plans back to dispatch and planning systems, and issues concise alerts with next-best actions for faults, load spikes, or late-ready risk. AI Use Cases Intelligent Enterprise & ERP SAP S/4HANA process acceleration Digitize finance, procurement, and asset processes for rolling-stock manufacturers and operators. How the agent works The agent surfaces ERP insights (“stockouts in depot A next week”), auto-prepares PRs/POs, reconciles materials to work orders, and suggests template-based postings—reducing cycle times across the value chain. GenAI staff co-pilot for back-office Give planners, controllers, and depot staff an AI coworker that answers policy/process questions and drafts documents. How the agent works The agent connects to ERP, EAM, and document stores; retrieves context; drafts SOPs, memos, and training snippets; and logs edits to improve future outputs—all with role-aware permissions. Subscription & account operations automation Streamline B2C account, consent, and subscription management with guided workflows. How the agent works The agent validates identity/consent, proposes next best actions (refund, renewal, plan change), and updates CRM/OMS while enforcing GDPR policies end-to-end. AI Use Cases Data Analytics & Internet of Trains Computer-vision analytics at scale Turn onboard and station video into real-time safety & ops intelligence—automatic passenger counting, incident detection, and early warnings for platform-edge track intrusions/self-harm risk—while optimizing dwell and throughput. How the agent works Analyzes vehicle, platform, and gate feeds to quantify crowding/dwell, detect slipand-falls and risky behavior at the platform edge, auto-count passengers, trigger instant alerts, and log searchable incident clips into dashboards for investigation and compliance. Digital twin & IoT observability Create a live digital representation of trains, stations, and track to simulate scenarios and optimize operations. How the agent works The agent ingests sensor and SCADA data, builds asset twins, runs “what-if” simulations (e.g., door failures, substation load), and recommends mitigations before issues hit service. Executive-ready operational summaries Auto-summarize network KPIs, anomalies, and root causes for daily stand-ups. How the agent works The agent monitors high-volume ops and customer data, detects underperformance, and generates short, role-specific briefs (maintenance hotspots, schedule adherence heatmaps, feedback trends) with drill-downs on request. AI Use Cases Ticketing & Distribution Frictionless and biometric payments Speed up gate throughput and reduce fraud with AI-enabled fare media, including optional biometrics. How the agent works The agent validates tokens/biometrics on-device or at the edge, reconciles with back-office, and adapts risk checks based on patterns—maintaining privacy by design. Smart offers & subscriptions Personalize passes, capping, and bundles to boost conversion and loyalty. How the agent works The agent learns travel habits, proposes best-value products, manages subscription lifecycles, and automates entitlements and refunds with compliant account handling. Agentic Fare Collection (Easy Go) Remove taps and manual validations: detect board/alight events automatically, charge only for distance traveled, and always apply the best fare/cap. Leverage cameras and mobile phones the rest is done automatically. How the agent works The AI detects ride start/stop, calculates optimal pricing across zones/peak times, manages accounts, payments, billing, and analytics, and integrates with external fare systems/wallets for end-to-end journeys—yielding best-fare outcomes (reported 10– 30% lower ticket cost to riders) and reduced hardware maintenance (≈35%) AI Use Cases Passenger Experience & Commercial Systems On-board and station staff companion Equip front-line staff with a voice-enabled co-pilot for SOPs, incidents, and customer FAQs. How the agent works The agent listens hands-free, retrieves context (service status, wheelchair space, connections), drafts responses, and escalates complex cases—speeding assistance while maintaining consistency. Safety, crowding & accessibility intelligence Improve safety and inclusivity with real-time detection and assisted navigation. How the agent works The agent spots overcrowding and hazards via video analytics, guides platform flow, and supports inclusive wayfinding (including assisted-reality indoor navigation) to elevate overall CX. Proactive service communications Deliver timely, personalized travel updates linked to the customer’s journey. How the agent works The agent correlates itineraries to disruptions, crafts multi-lingual notifications, proposes alternatives, and measures sentiment to refine future comms and service design.