QPo Transit Intelligence

Transport Operator
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QPo Transit Intelligence · Prototype build 2026.10

QPo Transit Intelligence

Transport Operator
Starting session…
Corporation View
1 Sep – 30 Sep 2026
SN
Data Integration

Connect Your Existing Systems

Use the data already generated by your existing transport systems. No replacement required — QPo reads the data, standardises it and converts it into actionable transport intelligence.

Your existing infrastructure remains unchanged. QPo only reads the data through a secure, one-way integration.

ETM / Ticketing

Passenger journeys
Fare & revenue
Origin–destination

Not connected

GPS / AVL

Vehicle movement
Trip completion
Travel time

Not connected

Schedules

Routes
Trips
Timetables

Not connected

Fleet & Depot Data

Bus inventory
Depot allocation
Maintenance

Not connected

Financial Data

Revenue
Operating cost
Depot performance

Not synced
Secure Integration
  • REST APIs
  • Direct database connection
  • SFTP / scheduled feeds
  • No write-back to source
QPo Transit Intelligence Layer
APIs · Database integration · Scheduled data feeds
Ingest› Validate› Combine› Analyse› Visualise
Your Data, Your Control
  • Read-only integration
  • Encrypted in transit and at rest
  • Hosted per authority policy
  • No change to existing systems
5 systems connected — all sources are reporting and data is being refreshed on schedule. Last updated 10 Oct 2026, 11:52

Connection Status

Refreshed every 15 minutes Refresh
SystemStatusLast Data UpdateData PeriodRecordsIntegration Method
ETM / TicketingPending10 Oct 2026, 11:351 Sep – 10 Oct 202612,46,352 tripsAPI (REST)View Details
GPS / AVLPending10 Oct 2026, 11:38Live1,842 busesAPI (REST)View Details
SchedulesPending10 Oct 2026, 10:20Sep 202618,420 tripsDatabaseView Details
Fleet & DepotPending10 Oct 2026, 09:10Sep 20262,372 recordsSFTP (daily)View Details
Financial DataPending10 Oct 2026, 08:45Sep 20268,192 recordsDatabaseView Details
Corporation Overview

Transport Operator Network Overview

One view of the entire corporation. Key performance, operations, revenue and service health across all districts and depots.

Ask QPo Copilot

Network Performance Trend

Passengers / dayRevenue (₹ L)

District Performance

DistrictPassengersRevenueActive BusesUtilisationAdherence

Top Performing Routes

View All
RoutePassengers / dayRevenue / dayUtilisation

Lowest Performing Routes

View All
RoutePassengers / dayRevenue / dayUtilisation

Service Alerts

View All
District Intelligence

District / Division Performance

Compare performance across districts and divisions. Identify high performing regions and areas that need attention.

DistrictKalaburagi
DivisionAll Divisions
MetricPassengers
Export Data

Districts in Operator Network

Passengers

District Performance

Export Data
DistrictPassengersRevenueBusesCost / kmRevenue / kmUtilisationAdherenceTrend

Key Insights

View All
Kalaburagi has the highest ridership and revenue
+12% growth this month, driven by the Kalaburagi–Yadgir and Kalaburagi–Sedam corridors.
Yadgir and Vijayapura show lower utilisation
Both districts are 10+ points below the network average and require a service review.
Schedule adherence is above 86% in 5 of 7 districts
Raichur and Yadgir need attention — both are below the 90% corporation target.

Passengers by District

Passengers

Revenue by District

Revenue
Depot Performance

Kalaburagi Depot ▾

Operational and financial health of the depot. Monitor fleet utilisation, service delivery and costs.

Fleet Status

Kilometres and Revenue Trend

Kilometres operatedRevenue (₹ L)

Depot Insights

View All
Passenger revenue increased 8% this month
Driven by higher ridership on KA-01 and KA-07.
Schedule adherence is 92%, above target
Continue current operations.
5 schedules consistently below 40% utilisation
Candidates for retiming or consolidation.
48 buses are under maintenance
Higher than last month (42) — fleet age is the main driver.
Route Intelligence

KA-01  Kalaburagi – Yadgir ▾

Detailed performance and passenger demand for each trip, stop and time period.

KA-01

Route Map

Passenger Demand

Passenger Demand by Time of Day

Passengers

Origin – Destination (Top Flows)

Passengers

Load Factor by Trip

Seats availablePassengersUtilisation

Stop-wise Passenger Activity

Boardings & Alightings
StopBoardingsAlightingsTotal

Trips for KA-01 (Kalaburagi – Yadgir)

View All Trips
Trip No.DepartureArrivalBus No.PassengersRevenueUtilisationStatus

AI Insights

View All
Morning peak demand (8–10 AM)
Above 115% utilisation. Consider an additional morning service.
Excess capacity in the afternoon
Between 2–5 PM utilisation falls below 50%. Schedules can be combined.
High-demand stops
Wadi and Chittapur show heavy boarding activity — consider limited-stop services.
Area & Corridor Planning

Passenger Demand and Service Coverage

Understand where people are travelling, how the network is operating and where service gaps exist.

DistrictKalaburagi
DepotAll Depots
Time of DayAll Day
ViewPassenger Demand
Download Map

Key Insights

View All
High-demand corridor
Kalaburagi – Sedam shows consistently high demand throughout the day. Current services are operating at >95% utilisation during peak hours.
Under-served areas
Chincholi and parts of Afzalpur show significant passenger demand with limited or no direct services.
Route overlap
Multiple routes operate on the Kalaburagi – Yadgir corridor with similar alignment. There may be scope for rationalisation.

Top Demand Corridors

View All
CorridorPax / dayUtilisationStatus

Areas Needing Attention

View All
AreaIssueDemandRecommendation
Fleet Planning

Optimal Bus Deployment

Use passenger demand, current fleet, route load and schedule performance to identify where additional buses are needed and how to deploy them.

Deployment Analysis

Add busesIncrease frequencyReallocateNo change

Fleet Planning Scenario

Reset
Additional buses0

AI Recommendation

Recommended deployment plan

Adding 20 buses lifts network utilisation from 67% to 75% and serves about 18,500 more passengers per day.

+18,500
Passengers per day
+8%
Network utilisation (67 → 75%)
₹3.2 L
Additional daily revenue
12% lower
Overcrowded trips

Recommended Deployment by Depot

Export Plan
DepotCurrentChangeRecommendedKey RoutesReason

Network Utilisation Comparison

CurrentAfter deployment
Procurement Intelligence

Fleet Requirement and Replacement Planning

Identify replacement needs, estimate future fleet requirements and plan procurement based on actual demand and network performance.

Next 12 months Export Plan

Fleet Age Distribution

2,372 buses

Projected Replacement Plan

ReplacementDemand growth

Additional Buses by Depot (Next 12 Months)

View All
DepotReplacementDemand GrowthTotal Required

Fleet Requirement Map

HighMediumLow

Route-wise EV Suitability

View All
RouteDaily kmDaily PassengersSuitabilityRecommendation

AI Insights

View All
42 additional buses required in the next 12 months
28 for replacement and 14 for demand growth, based on current ridership trends.
12 buses can be reallocated
Underutilised buses in Koppal and Vijayapura can be redeployed before new procurement.
EV suitable on 6 high-demand routes
These routes have predictable schedules and depot charging feasibility.
428 buses will reach 10+ years within 2 years
Plan procurement early to avoid service disruption.
Finance Intelligence

Finance Intelligence

Understand revenue, cost and financial performance across the corporation, districts, depots and routes.

Revenue and Cost Trend

RevenueOperating costSurplus

Revenue by Ticket Type

All Depots
₹10.2 L
Total revenue

Top Revenue Generating Routes

View All
RouteRevenue (₹)Passengers / dayRevenue / km

Depot-wise Financial Performance

View All
DepotRevenue (₹)Cost (₹)Surplus / DeficitRevenue / kmCost / km

Cost Breakdown

All Depots
₹8.4 L
Total cost

Collection Channels

September 2026
₹10.2 L
Collected

Route Profitability Analysis

View All
RouteRevenue (₹)Cost (₹)Profit / LossRev / kmStatus

Collection Anomaly Detection

View All
DateDepot / RouteObservedExpectedVarianceStatus

Ask Finance Copilot

Transport Intelligence Copilot

Transport Intelligence Copilot

Ask questions in your own language. Get insights from the operator's actual operational data with clear analysis and recommendations.

Management

Overall performance

Planning

Routes & network

Operations

Fleet & schedules

Finance

Revenue & cost

Depot Manager

Depot performance

Procurement

Fleet requirement

Ask your question

Planning
Ask a question about routes, depots, ridership, revenue or operations…
Upload a file Use this analysis Save to project

Route Demand Analysis — KA-01

KA-01
PassengersBus capacityOver capacity

KA-01 Summary

Daily passengers12,480 ▲14%
Current buses12
Peak utilisation138%
Avg utilisation82%
Recommended buses+2
Additional pax / day+4,800

Route Map — KA-01 (Kalaburagi – Yadgir)

High demand stopMediumNormal

Alternative Analysis

OptionBusesPax / dayCost / dayRevenue / day

Suggested Questions

View All
Scenario Planning

Evaluate and Compare Scenarios

Test different network, frequency and fleet options to understand the impact on ridership, coverage, cost and emissions.

Load Saved Scenario
1
Create ScenarioAdjust service parameters
2
Analyse ImpactCompare KPIs and maps
3
Refine and SaveSelect the best option

Scenario Settings

Reset
Scenario name
Increase frequency on KA-01 and KA-04
Adjust parameters
RouteCurrentNew
KA-0120 min20 min
KA-0425 min25 min
KA-1030 min30 min
KA-2235 min35 min
KA-4840 min40 min
Add additional route
Other parameters
Service hours5:30 AM – 11:00 PM
Fleet allocation+ 2 buses

Network Comparison

Route-wise Impact

View All
RouteCurrentScenarioPax / day nowPax / day afterChangeStatus

Key Impact Comparison

CurrentScenario
Current
Scenario

Passenger Demand Heatmap (Scenario)

AI Recommendation

Adding one additional morning service captures most of the expected passenger benefit at significantly lower operating cost than deploying two buses throughout the day.
Network utilisation improves from 67% to 75%, reducing overcrowding during peak hours.
Emissions may increase 5% — consider EV buses for the new allocation.
One Intelligence Layer for Every Department
Existing Transport Data
ETM / Ticketing GPS / AVL Fleet Schedules Finance
QPo Transit Intelligence Layer
Ingest · Validate · Combine · Analyse · Visualise

Management

Network performance & priority issues

Planning

Routes, frequencies, corridors & service gaps

Operations

Fleet deployment & schedule performance

Depot Teams

Daily operations & bus utilisation

Finance

Revenue, cost & collection intelligence

Procurement

Fleet requirement & replacement planning

Policy / Leadership

Scenario comparison & investment decisions

Dashboard tells youWHAT HAPPENED
Copilot explainsWHY IT HAPPENED
Simulation helps decideWHAT TO DO NEXT
One intelligence layer over the transport systems you already use.
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01 · Connect Existing Data