Use Case Explorer

Generates customised safety reports for employees based on predictive risk scores.

Provides instant, natural language answers to safety protocol queries from vast manuals.

Enables conversational querying of structured and unstructured safety incident data.

Creates engaging audio summaries (e.g., podcasts) of safety information from various sources.

Analyses live data streams to identify hazards and monitor worker compliance.

Explains *why* assets fail, suggests specific repairs, and simulates failure scenarios.

Assists technicians with diagnostics/repairs; optimises infrastructure design via simulation.

Generates optimal schedules based on complex constraints and explains rationale.

Predicts disruptions, generates recovery plans, and communicates updates.

Extracts and structures data from various documents (invoices, forms); generates templates.

Automates payroll, financial oversight, HR administration, and fraud detection.

Automates regulatory checks, streamlines audit prep, provides real-time analytics.

Provides 24/7 human-like support, resolves issues, guides customers.

Creates intelligent wikis, answers policy questions, assists onboarding.

Generates job descriptions, screens resumes, and drafts personalised candidate communications.

Streamlines content creation for marketing, sales, and internal communications.

Assists procurement teams by summarising supplier contracts, analysing performance reports, and drafting negotiation points.

Provides automated responses to common IT support queries, troubleshoots issues, and guides users through solutions.

Generates structured incident reports from unstructured field notes or audio recordings, and analyses them for trends.

Analyses images/videos from track or rolling stock inspections to identify defects and generate textual descriptions and severity assessments.

Creates realistic, dynamic training scenarios for train crews, adapting to their responses in real-time to test decision-making under pressure.

Automatically generates clear, empathetic, and multi-channel communications to customers during service disruptions, providing real-time updates and alternative travel options.

Analyses and summarises cybersecurity threat intelligence feeds, highlighting risks specific to rail operational technology (OT) systems.

Scans supplier and client contracts to identify non-standard clauses, potential risks, and obligations, providing a summary for legal review.

Automatically identifies and redacts sensitive information (PII, commercial-in-confidence) from documents before public release or sharing.

Simulates thousands of train routing and handling scenarios to identify the most fuel-efficient operational strategies under different conditions.

Gathers data from various internal systems (e.g., fuel usage, carbon emissions, employee diversity) to draft the narrative for an annual ESG reports.

Analyses maintenance records and supply chain data to forecast spare parts demand, generating optimised ordering and stocking recommendations.

Analyses anonymised employee feedback from surveys and communication platforms to identify trends in sentiment, burnout risk, and engagement.

Assists IT teams by generating boilerplate code, scripts for data migration, and unit tests for internal software and analytics tools.

Analyzes near-miss reports and operational data to generate hypotheses about underlying root causes and contributing factors.

Rewrites complex engineering specifications and maintenance manuals into simplified language or visual guides for frontline technicians.

Provides a conversational interface for crew members to report fatigue levels and receive guidance based on rostering data and fatigue models.

Simulates passenger movement through new or redesigned stations to identify bottlenecks and optimise layout, signage, and staffing.

Summarises key performance indicators, financial results, and operational highlights from various reports into a concise briefing document for executives.

Monitors new legislation and regulations, analyses their potential impact on operations and policies, and drafts initial action plans.

Tracks social media mentions and news outlets for emerging issues or negative sentiment, generating alerts and summaries for the communications team.

Assists in writing and assembling large tender or bid documents by pulling standard information, customising sections based on requirements, and ensuring consistency.

Generates drafts of internal IT policies (e.g., acceptable use, data handling) based on industry best practices and specific organisational requirements.

Generates a customised onboarding plan and materials for new hires based on their role, department, and existing skill set.

Allows train drivers and staff to ask natural language questions about complex operating rules and receive instant, cited answers.

Creates realistic, synthetic data streams from asset sensors to test and validate predictive maintenance models without needing real-world failure data.

When a disruption occurs, this tool suggests optimal crew re-assignments, considering certifications, fatigue rules, and employee location, then drafts communication to affected staff.

Provides real-time transcription, and if necessary, translation, of voice communications between train controllers, drivers, and emergency services during an incident.

Automatically reads, categorises, and summarises incoming customer complaints from email and web forms, identifying recurring themes.

Assists project managers in writing business cases for new capital investments by generating sections on market analysis, risk assessment, and financial projections based on prompts.

Intelligently searches and categorises millions of internal documents (emails, reports) to find those relevant to legal cases, flagging them for attorney review.

Acts as a travel-planning assistant on the company website, suggesting train journeys, connections, and local attractions based on user prompts.

Analyses real-time inventory levels, project timelines, and market prices to advise procurement officers on the optimal time to purchase materials and services.

Generates realistic but harmless phishing emails to test employee awareness and provides instant, contextual feedback and an they click.

Simulates the impact of severe weather forecasts (e.g., flooding, high winds) on the network, identifying at-risk locations and generating proactive mitigation plans.

Extracts and structures detailed Bill of Materials information from unstructured engineering drawings or legacy PDF documents into a central database.

Provides an interface for managers and HR to ask natural language questions about complex union agreements and work rules.

Monitors and summarises competitor pricing, timetables, and marketing campaigns from public sources, providing a weekly intelligence briefing.

Generates new, optimised train timetables based on a set of constraints like track availability, crew resources, maintenance schedules, and desired passenger outcomes.

A chatbot that guides customers through reporting lost property, using image recognition to help identify items and matching them against found items.

Analyses financial data to identify significant budget variances, then generates natural language explanations and potential reasons for the deviation.

Analyses employee performance data, skills, and career aspirations (from reviews) to identify high-potential candidates for critical roles.

Reads and analyses supplier responses to RFPs, scoring them against weighted criteria, checking for compliance, and summarising key strengths and weaknesses.

Generates customised incident response playbooks for different types of cyber threats (e.g., ransomware, data breach), aligned with industry frameworks.

Analyzes train logs, controller notes, and sensor data to automatically assign the correct delay attribution code for performance reporting.

Generates pre-shift safety briefings for maintenance teams that are customised to the specific location, tasks, and known hazards for that day.

Analyzes data from wayside detectors (e.g., acoustic, thermal) to identify anomalous patterns that precede component failure, generating plain-language alerts.

Automatically scans crew records and upcoming operational requirements to flag expiring certifications and potential compliance gaps in rosters.

Analyzes ticketing data, station layouts, and inspector reports to identify patterns and hotspots for fare evasion, suggesting targeted mitigation strategies.

Reads supplier contracts and project reports to automatically calculate and generate journal entries for financial accruals and provisions.

Organizes and summarizes evidence (photos, reports, witness statements) for insurance claims or litigation, creating a structured case file.

Generates ideas and draft content for internal newsletters, intranet articles, and executive announcements based on company news and strategic priorities.

A chatbot that guides new suppliers through the onboarding process, helping them complete forms, upload required documents, and understand compliance requirements.

Analyzes system and application logs in real-time to detect anomalous behavior that could indicate a cybersecurity threat or impending system failure, generating alerts in natural language.

Analyses data from various sources (geometry cars, visual inspection, weather) to prioritise a list of track segments that require urgent attention.

Takes a script or procedural document and generates a complete video training module, including a synthetic voiceover, relevant stock footage, and on-screen text.

Analyzes reports and photos of graffiti and vandalism to identify tags and patterns, helping to allocate clean-up crews and support law enforcement.

During a network disruption, this tool advises managers on the most efficient way to re-route crews to cover services, considering taxi costs, hotel needs, and working hours.

A specialised chatbot that provides detailed information about station accessibility, including lift status, ramp availability, and accessible toilet locations.

Monitors leading financial and operational indicators to provide early warnings of a potential financial distress or deviation from fiscal targets.

Takes long, jargon-filled corporate policies and generates easy-to-understand summaries, FAQs, and 'What this means for you' sections.

Generates draft press releases for common events like service changes, executive appointments, or positive performance results, based on key data points.

Analyses market data and geopolitical news to forecast price fluctuations for key commodities (e.g., fuel, steel) and recommend purchasing strategies.

Scans dark web forums and marketplaces for mentions of the company or compromised employee credentials, generating alerts for the security team.

Analyzes drone/satellite imagery and weather data to identify areas of vegetation encroachment, prioritizing cutting and spraying schedules to prevent track interference.

Analyzes transcripts from exit interviews to identify common themes and reasons for employee attrition, providing insights for retention strategies.

Generates optimal plans for assembling and disassembling trains in a yard (shunting/marshalling) to minimize movements and conflicts.

Aggregates and analyzes customer feedback from all channels (social media, surveys, complaints) to create a unified view of customer sentiment and key issues.

Generates draft footnotes for quarterly and annual financial statements by analyzing accounting data and previous disclosures.

Provides a secure conversational interface for internal investigators to query and summarize evidence from case files, HR records, and communication logs.

Automatically generates quarterly performance reports for key suppliers, combining quantitative data (e.g., on-time delivery) with qualitative summaries of recent interactions.

Analyzes software usage data across the organization to identify underutilized licenses and suggest opportunities for cost savings or redistribution.

Generates personalized safety briefings for train crews and maintenance teams based on upcoming route conditions, weather, and historical incident data.

Monitors government and regulatory body announcements, generating daily or weekly briefings on policy changes, consultations, and political shifts relevant to the rail sector.

Generates step-by-step maintenance procedures for complex or non-standard repairs, drawing from technical manuals and expert knowledge.

Analyzes historical maintenance costs, asset performance data, and market forecasts to generate a natural language summary of the predicted lifecycle cost for a class of assets.

Generates interactive training modules, simulations, and personalized learning paths for new train operators and maintenance staff.

Generates a draft competency framework for a specific job role by analyzing job descriptions, industry standards, and the skills of high-performing employees in similar roles.

Generates real-time, personalized updates for passengers regarding train status, delays, and alternative routes.

Ingests incident logs, controller notes, and performance data after a service disruption to generate a structured first draft of a Post-Incident Review document.

Generates comprehensive financial reports (e.g., quarterly summaries, budget vs. actuals) from raw financial data, including narrative explanations of key trends and variances.

Generates natural language summaries and analyses of different capital investment scenarios, explaining the potential impact on cash flow, debt covenants, and enterprise value.

Analyzes legal documents for key clauses, identifies risks, and generates draft contracts or amendments.

Simulates the potential revenue and demand impact of different dynamic pricing strategies based on historical booking data, competitor pricing, and demand elasticity models.

Provides a conversational interface for business leaders to self-assess their department's capability maturity, generating a summary report and initial recommendations based on their answers.

When a process is automated, this tool analyzes the impacted roles and generates a draft job redesign plan, including new responsibilities and a reskilling/training roadmap.

Tracks project KPIs against the original business case benefits, generating narrative progress reports that explain variances and forecast the likelihood of achieving targeted benefits.

Analyzes a proposed change and stakeholder map to generate a tailored communication plan and draft messages for different affected groups.

Analyzes AI/ML model code and performance metrics to automatically generate technical documentation, covering architecture, data sources, and validation results, ensuring compliance with model risk management standards.

Provides a conversational interface for employees to ask questions about data governance policies, such as 'Where can I store customer PII?' and receive cited answers.

Analyzes market trends and potential partner capabilities to generate draft strategy documents for new alliances, including joint value propositions and collaboration models.

Analyzes real-time video and sensor data from bridge strikes to automatically generate incident reports, identify the vehicle involved, and assess initial damage.

Combines weather forecasts with historical performance data to predict the specific impact of adverse weather (e.g., heat, wind, floods) on network performance and suggests proactive service alterations.

Provides an interactive, conversational assistant for train drivers to diagnose and potentially resolve minor in-service faults by guiding them through troubleshooting steps based on technical manuals.

Takes a high-level strategic goal (e.g., 'Improve Customer Satisfaction by 10%') and generates a hierarchical tree of contributing Key Performance Indicators (KPIs) across different business functions.

Continuously monitors news, industry reports, and political analysis to generate a weekly 'state of the nation' briefing for senior leadership, highlighting key risks and opportunities.

Acts as a brainstorming partner for service designers, generating novel service concepts, value propositions, and customer journey maps based on market research and customer needs.

Analyzes feedback from all customer channels (surveys, complaints, social media) to create a data-driven map of customer pain points, organised by journey stage.

Generates draft emergency response plans for various scenarios (e.g., derailment, security incident), ensuring they are consistent with regulations and best practices.

Provides real-time, in-cab advice to train drivers on the most energy-efficient driving techniques (e.g., coasting, optimal acceleration) based on the train's load and the track ahead.

When a disruption occurs, this tool generates an optimal service recovery plan, suggesting train re-routes, cancellations, and crew re-assignments to minimize overall passenger delay.

Continuously monitors real-time train performance data to detect subtle anomalies that could indicate emerging mechanical faults or infrastructure issues, generating alerts for control center staff.

When a disruption is predicted or occurs, this system automatically generates and sends personalized, multi-channel communications to affected passengers with clear information and travel alternatives.

Acts as a co-pilot for control center staff during disruptions, taking dictated key facts and instantly drafting clear, structured messages for various internal and external channels.

Acts as a travel planning assistant for customers, generating personalized itineraries and suggesting relevant ancillary services (e.g., seat upgrades, station lounge access) based on their journey.

Uses historical data to predict the likely duration and ripple effects of a current disruption, and generates draft communications that manage passenger expectations with more accurate information.

Generates a complete draft of the monthly financial reporting pack by pulling data from the general ledger and other financial systems and populating pre-defined templates.

When a transaction is flagged as potentially fraudulent by another system, this tool generates a plain-English explanation of *why* it was flagged, helping investigators to triage alerts faster.

Analyzes budget vs. actual data and generates a written narrative for management accounts, explaining key variances and performance trends.

Automatically validates employee timesheets against complex work rules and union agreements, flagging errors and suggesting corrections before they enter the payroll system.

Automatically matches transactions between bank statements and the general ledger, identifies discrepancies, and suggests potential resolutions.

Generates accounting journal entries based on business events (e.g., asset acquisition) and provides a clear, auditable explanation for the accounting treatment.

Automatically audits 100% of employee expense claims by extracting data from receipts and checking it against company policy, flagging exceptions for human review.

Takes a complex cash flow forecast model and generates a plain-English narrative summary, explaining the key drivers, assumptions, and potential risks.

When a regulation changes, this tool identifies the internal policies that are impacted, generates a draft of the updated policy, and creates a communications plan to disseminate the changes.

Analyzes and summarizes vast system audit logs, highlighting anomalous or high-risk activities for review by an internal auditor.

Generates drafts of mandatory regulatory reports by gathering data from various internal systems and formatting it according to the regulator's specifications.

Analyzes HR and recruitment data to identify potential biases in hiring, promotion, and pay, and generates anonymized reports for the D&I committee.

Monitors social media mentions and suggests draft responses for the community management team that are consistent with the brand's voice and policies.

Analyzes customer travel patterns to generate proactive, personalized outreach, such as offering a discount on a frequently traveled route or suggesting a weekend trip.

Generates drafts for internal announcements, newsletter articles, and executive messages, ensuring a consistent tone of voice and clear communication.

A conversational assistant that can answer employee questions about their payslip, leave balance, and other benefits, available 24/7.

A chatbot that guides employees through the process of requesting leave, checking their balance, and understanding the approval workflow.

Takes an employee's pension statement and generates a personalized, plain-English explanation of their current standing, projections, and investment options.

Allows employees to simply forward email receipts or take photos of physical receipts, and the system automatically creates a draft expense report for them.

A chatbot on the careers website that can answer candidate questions about the recruitment process, company culture, and benefits.

A conversational assistant that communicates with candidates to find a suitable interview time that works for both them and the hiring manager(s), then automatically sends calendar invites.

Reads long, detailed background check reports and generates a concise summary, highlighting any potential red flags or areas that require further investigation by HR.

Automatically sends personalized updates and rejection notifications to candidates based on their status in the Applicant Tracking System (ATS).

Analyzes recruitment data from the ATS and generates a narrative report explaining key trends, such as conversion rates, time-to-hire, and source effectiveness.

Automates the employee referral process, from tracking submissions to sending notifications and processing referral bonuses.