Explore how the GUM-RTDP platform delivers real-time intelligence across industries. Each industry showcases representative Business Events, AI-scored Events, end-to-end Event Flows, and AI Use Cases — illustrating how the platform's three integrated layers work together to detect, predict, and act in real time. Examples are intentionally selective; the platform's composable architecture supports a much broader range of scenarios tailored to your organization.
Event naming is intentional — a well-named event communicates its business intent without ambiguity, eliminating misinterpretation by producers and consumers alike. Where the name alone is insufficient, a precise description in the event registry completes the contract. Naming rooted in the Conceptual Enterprise Data Model (CEDM) ensures events reflect true business concepts rather than technical or system-centric artefacts — a foundational discipline for a governed, trustworthy event fabric.
Airlines
Business Events
- schedule.published
- flight.scheduled
- booking.created
- passenger.checked_in
- baggage.tagged
- boarding.completed
- flight.departed
Event Flows
- On demand.forecast.generated → consumers: schedule planning service (OR), network planning service, capacity planning service
- On schedule.published → consumers: aircraft assignment service, operations planning service
- On booking.created → inference publishes demand.forecast.revised, ancillary.revenue.forecasted, passenger.no_show_risk.scored → consumers: revenue management service, ancillary offer service, overbooking mgmt. service
- On passenger.checked_in → inference publishes passenger.no_show_risk.scored → consumers: overbooking mgmt. service, gate agent alert, standby upgrade service
- On baggage.tagged → inference publishes baggage.misroute_risk.predicted → consumers: manual check service, baggage handler alert
- On boarding.completed → inference publishes flight.delay.predicted → consumers: proactive rebooking service, crew legality checker, gate manager
- On flight.departed → consumers: flight tracking service, connection manager, gate release service, slot usage service
AI Events
- demand.forecast.generated
- demand.forecast.revised
- flight.delay.predicted
- passenger.no_show_risk.scored
- baggage.misroute_risk.predicted
- demand.forecast.generated
- ancillary.revenue.forecasted
AI Use Cases
- O&D and operating segment demand forecasting
- AOG events prediction using flight data, maintenance and sensors
- Delay propagation prediction
- Misconnect risk prediction
- Customer LTV prediction
- Customer churn prediction
- Ancillary revenue optimization (bags, seats, upgrades)
- IROPS prediction
- Passenger no-show risk scoring
Public Transit
Business Events
- vehicle.departed
- stop.arrived
- passenger.boarded
- fare.validated
- service.disrupted
Event Flows
- On vehicle.departed → inference publishes vehicle.failure.predicted → consumers: maintenance alert service, depot coordinator
- On stop.arrived → inference publishes ridership.demand.forecasted → consumers: dispatch service, capacity planner
- On passenger.boarded → inference publishes crowding.level.predicted → consumers: dynamic dispatch service, passenger information system
- On fare.validated → inference publishes fare.evasion_risk.scored → consumers: inspection alert service, enforcement dispatcher
- On service.disrupted → inference publishes service.delay_risk.scored → consumers: transfer protection service, passenger notification, crew reassignment
AI Events
- ridership.demand.forecasted
- crowding.level.predicted
- vehicle.failure.predicted
- service.delay_risk.scored
- fare.evasion_risk.scored
AI Use Cases
- Ridership forecasting by route, stop, and time of day for service planning
- Crowding prediction to adjust headways or dispatch extra vehicles
- Predictive maintenance for buses, trams, and stations (doors, HVAC, batteries)
- Missed connection risk scoring
- Vehicle failure prediction
Railways
Business Events
- carriage.coupled
- track.occupancy.updated
- delay.reported
- train.departed
- train.arrived
- track.blue_flagged
Event Flows
- On carriage.coupled → inference publishes rollingstock.failure.predicted → consumers: maintenance work order service, yard master
- On track.occupancy.updated → inference publishes track_occupancy.level.forecasted, safety_incident.risk.scored → consumers: signal control system, switching service, operations controller, safety monitor
- On delay.reported / train.departed → inference publishes train.arrival.predicted → consumers: pax notification service, crew reassignment, connection manager
- On train.arrived → inference publishes passenger.demand.forecasted → consumers: capacity planner, timetable service
- On track.blue_flagged → consumers: safety halt service, dispatcher alert, maintenance coordinator, safety controller
AI Events
- train.arrival.predicted
- track_occupancy.level.forecasted
- rollingstock.failure.predicted
- passenger.demand.forecasted
- safety_incident.risk.scored
Banking
Business Events
- account.opened
- funds.transferred
- payment.processed
- loan.approved
- fraud.detected
Event Flows
- On account.opened → inference publishes customer.churn_risk.scored, loan.default_risk.scored → consumers: onboarding service, risk assessment service, KYC/AML workflow
- On funds.transferred → inference publishes transaction.fraud_risk.scored → consumers: transaction hold service, compliance system, customer alert
- On payment.processed → inference publishes payment.failure_risk.predicted → consumers: customer notification service, retry manager
- On loan.approved → inference publishes credit_limit.adjustment.recommended, loan.default_risk.scored → consumers: KYC/AML workflow, document generation, disbursement service, credit risk service
- On fraud.detected → consumers: account freeze service, customer notification, compliance reporting
AI Events
- transaction.fraud_risk.scored
- loan.default_risk.scored
- customer.churn_risk.scored
- credit_limit.adjustment.recommended
- payment.failure_risk.predicted
AI Use Cases
- Credit scoring
- Transaction fraud scoring
- Loan default risk prediction
- Credit limit adjustment recommendation
- Customer lifetime value prediction
- Next‑best‑product recommendation
Cities
Business Events
- traffic_flow.updated
- parking_spot.occupied
- waste_level.measured
- air_quality.recorded
- incident.reported
Event Flows
- On traffic_flow.updated → inference publishes traffic_flow.level.predicted → consumers: signal timing service, routing information system
- On parking_spot.occupied → inference publishes parking_demand.forecasted → consumers: dynamic pricing engine, routing information system
- On waste_level.measured → inference publishes waste_level.quantity.forecasted → consumers: collection routing service, dispatch planner
- On air_quality.recorded → inference publishes air.quality.level.forecasted → consumers: public alert service, school notification, event organizer
- On incident.reported → inference publishes incident_risk.scored → consumers: emergency response coordinator, fire dispatch, police dispatch, EMS dispatch
AI Events
- traffic_flow.level.predicted
- parking_demand.forecasted
- waste_level.quantity.forecasted
- air_quality.level.forecasted
- incident_risk.scored
AI Use Cases
- Traffic flow prediction for congestion management and signal optimization
- Parking demand prediction for dynamic pricing and routing
- Waste collection optimization (OR/AI)
- Environmental forecasting (air quality, noise, flood risk)
- Emergency response resource prediction
Entertainment (live)
Business Events
- ticket.scanned
- crowd_flow.updated
- concession.purchased
- merchandise.sold
- event.concluded
Event Flows
- On ticket.scanned / purchased → inference publishes crowd.flow.level.predicted → consumers: staffing reallocation service, security dispatcher
- On crowd_flow.updated → inference publishes safety_incident.risk.scored → consumers: security response service, venue operations
- On concession.purchased → inference publishes concession.demand.forecasted → consumers: restocking service, inventory manager
- On merchandise.sold → inference publishes merchandise.sales.forecasted → consumers: inventory manager, venue operations
- On event.concluded → inference publishes staffing.requirement.predicted → consumers: staffing planner, workforce scheduler
AI Events
- crowdflow.level.predicted
- concession.demand.forecasted
- merchandise.sales.forecasted
- safety_incident.risk.scored
- staffing.requirement.predicted
AI Use Cases
- Crowd flow prediction (ingress, egress, concourse movement)
- Concession demand forecasting
- Merchandise sales forecasting
- Safety incident risk scoring
- Staffing requirement prediction
- VIP next-best-action recommendation
Governments
Business Events
- application.submitted
- case.updated
- permit.issued
- benefit.approved
- compliance_flag.raised
Event Flows
- On application.submitted → inference publishes application.processing_time.predicted → consumers: priority queue service, SLA monitor, applicant notification
- On benefit.approved → inference publishes fraud.risk.scored → consumers: audit service, compliance reporter, payment processor
- On compliance_flag.raised → consumers: audit workflow, legal notification, case management service
- On case.updated → inference publishes compliance.risk.scored → consumers: case management service, legal notification, compliance reporter
- On permit.issued → inference publishes service.demand.forecasted → consumers: resource planning service, workforce scheduler
- On application.submitted → inference publishes application.processing_time.predicted, benefit.eligibility.scored → consumers: priority queue service, SLA monitor, applicant notification, eligibility service
AI Events
- application.processing_time.predicted
- fraud.risk.scored
- benefit.eligibility.scored
- service.demand.forecasted
- compliance.risk.scored
AI Use Cases
- Application processing time prediction
- Benefit eligibility scoring
- Fraud detection across benefits, taxation and procurement
- Compliance risk scoring
- Service demand forecasting
- Case processing prediction
Healthcare
Business Events
- appointment.scheduled
- patient.checked_in
- diagnosis.recorded
- medication.prescribed
- claim.submitted
Event Flows
- On appointment.scheduled → inference publishes resource.utilization.forecasted → consumers: scheduling service, capacity planner, staffing coordinator
- On patient.checked_in → inference publishes appointment.no_show_risk.scored → consumers: outreach service, scheduling optimizer
- On diagnosis.recorded → inference publishes patient.readmission_risk.scored, diagnosis.proposed → consumers: care coordination service, resource planner, clinical decision support
- On medication.prescribed → inference publishes medication.adherence_risk.predicted → consumers: follow-up workflow, pharmacy notification
- On claim.submitted → consumers: provincial billing service, claims adjudication service, compliance reporter
AI Events
- appointment.no_show_risk.scored
- diagnosis.recommendation.generated
- patient.readmission_risk.scored
- medication.adherence_risk.predicted
- resource.utilization.forecasted
AI Use Cases
- No‑show prediction
- Readmission risk prediction
- Medication adherence risk prediction
- Resource utilization forecasting
- Diagnosis proposal generation
- Predictive triage
Hospitality
Business Events
- room.searched
- booking.created
- booking.modified
- room.check_in.completed
- room.check_out.completed
- payment.captured
Event Flows
- On room.searched → inference publishes room.demand.forecasted, occupancy.rate.forecasted → consumers: dynamic pricing engine, inventory manager, revenue manager
- On booking.created → inference publishes booking.cancellation_risk.scored, guest.spend.predicted → consumers: retention offer service, revenue manager, pre-arrival offer service
- On booking.modified → inference publishes booking.cancellation_risk.scored → consumers: retention offer service, revenue manager
- On room.check_in.completed → inference publishes guest.spend.predicted → consumers: personalized offer service, upsell service, loyalty tracker, housekeeping scheduler
- On room.check_out.completed → inference publishes maintenance.issue.predicted → consumers: housekeeping service, maintenance coordinator
- On payment.captured → consumers: billing service, loyalty points service, finance reporting
AI Events
- room.demand.forecasted
- booking.cancellation_risk.scored
- guest.spend.predicted
- occupancy.rate.forecasted
- maintenance.issue.predicted
AI Use Cases
- Room demand forecasting
- Occupancy rate forecasting
- Booking cancellation risk scoring
- Guest spend prediction
- Predictive maintenance (rooms and facilities)
- Guest churn prediction
- Review sentiment analysis
Insurance
Business Events
- quote.requested
- policy.bound
- claim.filed
- claim.adjusted
- payment.disbursed
Event Flows
- On quote.requested → inference publishes quote.conversion_probability.scored → consumers: personalized offer service, campaign manager
- On policy.bound → inference publishes policy_renewal.risk.scored, customer.lifetime_value.predicted → consumers: underwriting workflow, document generation, billing, retention servic
- On claim.adjusted → inference publishes claim_settlement.amount.predicted → consumers: auto-approval service, payment processor
- On policy.bound → consumers: underwriting workflow, document generation, billing
- On claim.adjusted → inference publishes claim_settlement.amount.predicted → consumers: auto-approval service, payment processor
AI Events
- policy_renewal.risk.scored
- claim_fraud.risk.scored
- claim_settlement.amount.predicted
- customer.lifetime_value.predicted
- quote.conversion_probability.scored
AI Use Cases
- Quote conversion probability scoring
- Claim fraud scoring
- Claim settlement amount prediction
- Policy renewal risk scoring
- Customer lifetime value prediction
- Customer churn prediction
- Risk classification
- Loss ratio forecasting
- Claim severity prediction
Manufacturing
Business Events
- work_order.created
- material.issued
- production.completed
- quality_check.failed
- shipment.dispatched
Event Flows
- On work_order.created → inference publishes equipment.failure.predicted, production.yield.forecasted → consumers: maintenance service, production planner, scheduling service
- On material.issued → inference publishes material.consumption.forecasted → consumers: reorder service, supply chain planner
- On production.completed → consumers: shipment dispatcher, inventory updater, billing service
- On quality_check.failed → inference publishes quality.issue_risk.scored → consumers: production halt service, quality manager, supplier alert
- On shipment.dispatched → inference publishes shipment.delay.predicted → consumers: customer notification service, logistics coordinator
AI Events
- equipment.failure.predicted
- production.yield.forecasted
- quality.issue_risk.scored
- material.consumption.forecasted
- shipment.delay.predicted
AI Use Cases
- Equipment failure prediction
- Production yield forecasting
- Quality issue risk scoring
- Material consumption forecasting
- Shipment delay prediction
- Energy consumption prediction
Media & Streaming
Business Events
- content.viewed
- playback.started
- playback.interrupted
- subscription.renewed
- recommendation.served
Event Flows
- On content.viewed → inference publishes engagement.level.predicted, ad.yield.forecasted → consumers: ad insertion engine, content curator, revenue optimizer
- On playback.started → inference publishes content.recommendation.generated → consumers: content suggestion service, ad insertion engine
- On playback.interrupted → inference publishes playback.failure_risk.predicted → consumers: CDN failover service, QoS monitor
- On subscription.renewed → inference publishes customer.churn_risk.scored → consumers: loyalty offer service, account manager
- On recommendation.served → consumers: engagement tracker, A/B test service, analytics service
AI Events
- content.recommendation.generated
- customer.churn_risk.scored
- engagement.level.predicted
- ad.yield.forecasted
- playback.failure_risk.predicted
AI Use Cases
- Personalized content recommendations (session‑level, real‑time)
- Churn prediction based on engagement, content patterns, and QoS signals
- Ad yield forecasting
- Content engagement prediction
- Quality of experience prediction
- Content performance forecasting
Mining
Business Events
- extraction.started
- equipment.fault.detected
- safety_incident.reported
- ore.processed
- shipment.loaded
Event Flows
- On extraction.started → inference publishes production.output.forecasted → consumers: production planner, logistics coordinator, inventory service
- On equipment.fault.detected → inference publishes equipment.failure.predicted → consumers: maintenance work order service, parts procurement
- On safety_incident.reported → inference publishes safety_incident.risk.scored → consumers: evacuation coordinator, shutdown service, compliance reporter
- On ore.processed → inference publishes ore.grade.predicted → consumers: processing parameter adjuster, production planner
- On shipment.loaded → consumers: logistics coordinator, inventory updater, billing service
AI Events
- equipment.failure.predicted
- safety_incident.risk.scored
- ore.grade.predicted
- production.output.forecasted
AI Use Cases
- Ore grade prediction
- Equipment failure prediction
- Production output forecasting
- Environmental risk modeling
- Worker safety risk scoring
Public Utilities
Business Events
- meter_reading.captured
- outage.reported
- service.restored
- work_order.dispatched
Event Flows
- On meter_reading.captured → inference publishes consumption.anomaly.scored, load.demand.forecasted → consumers: grid balancer, capacity planner, demand response service
- On outage.reported → consumers: crew dispatch service, customer notification, grid balancer
- On work_order.dispatched → inference publishes asset.failure.predicted, leak.risk.scored, outage.risk.predicted → consumers: preventive maintenance service, parts procurement, field crew dispatcher, grid balancer
- On service.restored → inference publishes consumption.level.forecasted → consumers: grid balancer, capacity planner, customer notification
AI Events
- outage.risk.predicted
- load.demand.forecasted
- leak.risk.scored
- asset.failure.predicted
- consumption.anomaly.scored
- consumption.level.forecasted
AI Use Cases
- Load demand forecasting (short‑term and long‑term)
- Consumption anomaly scoring
- Asset failure prediction
- Leak risk scoring
- Outage risk prediction
- Consumption level forecasting
Retail
Business Events
- product.created
- cart.updated
- order.placed
- inventory.level.adjusted
- payment.authorized
- shipment.delivered
Event Flows
- On product.created → inference publishes product.demand.forecasted, inventory.level.predicted → consumers: inventory planner, pricing service, merchandising service
- On cart.updated → inference publishes order.cancellation_risk.scored → consumers: cart recovery service, promotions engine
- On order.placed → inference publishes transaction.fraud_risk.scored → consumers: hold or place order based on threshold
- On inventory.level.adjusted → inference publishes inventory.level.predicted → consumers: replenishment service, supplier notification, demand planner
- On payment.authorized → consumers: shipment workflow, warehouse picker, customer notification
- On shipment.delivered → consumers: loyalty points service, customer notification, satisfaction survey service
AI Events
- product.demand.forecasted
- inventory.level.predicted
- transaction.fraud_risk.scored
- order.cancellation_risk.scored
- customer.churn_risk.scored
AI Use Cases
- Product demand forecasting
- Inventory level prediction
- Order cancellation risk scoring
- Transaction fraud scoring
- Customer churn prediction
- Customer lifetime value prediction
- Price elasticity modeling
Telecom
Business Events
- service.activated
- plan.changed
- usage.recorded
- outage.detected
- invoice.produced
- ticket.updated
- ticket.resolved
Event Flows
- On service.activated → consumers: provisioning service, billing service, welcome notification
- On plan.changed → inference publishes customer.churn_risk.scored → consumers: retention offer service, account manager
- On usage.recorded → inference publishes network.outage_risk.predicted, usage.demand.forecasted, fraud.risk.scored → consumers: network operations center, capacity planner, network planning service
- On outage.detected → consumers: customer notification service, field crew dispatcher, network operations center
- On invoice.produced→ inference publishes plan.change.recommended, customer.churn_risk.scored → consumers: retention offer service, account manager, upsell service, customer success manager
- On ticket.updated → inference publishes ticket.escalation_risk.scored, customer.churn_risk.scored → consumers: priority queue service, supervisor alert, customer notification
- On ticket.resolved → consumers: satisfaction survey service, churn risk re-scorer, loyalty tracker
AI Events
- customer.churn_risk.scored
- network.outage_risk.predicted
- usage.demand.forecasted
- plan.change.recommended
- ticket.escalation_risk.scored
- fraud.risk.scored
AI Use Cases
- Churn prediction
- Network outage risk prediction
- Usage demand forecasting
- Plan change recommendation
- Ticket escalation risk scoring
- Fraud detection