Delivery Partner App
Drivers receive jobs, route guidance, pickup handoffs, proof-of-delivery steps, earnings, and support actions.
Logistics / Mobile
Jhatpat Delivery
Jhatpat Delivery connects customers, operations teams, vendors, and delivery partners through a real-time last-mile platform built for fast dispatch, routing, tracking, and scale.
Year
2024
Team Size
9 engineers
Timeline
5 month MVP, 10 months to scale
Technology
React Native, Node.js, Kafka
The Challenge
Jhatpat Delivery needed to scale beyond manual dispatch. Orders were growing across cities, delivery partners were managed through disconnected tools, and operations teams lacked a single control plane for rider location, order exceptions, route quality, customer ETAs, and partner performance.
The product needed two experiences at once: a lightweight customer ordering flow and an operations-grade management platform for last-mile dispatch. Accuracy mattered because bad ETAs, missed handoffs, and weak partner visibility translated directly into support tickets and lost customer trust.
DigiteraX built the platform around real-time logistics: delivery partner apps, dispatch dashboards, location streaming, vendor order handoff, Kafka-backed events, route optimization, proof-of-delivery, and operational analytics.
Client Name
Jhatpat Delivery
Industry
Last-Mile Logistics
Engagement Type
Mobile App + Management Platform
Timeline
5 month MVP, 10 month scale-up
Team Size
9 engineers
Budget Range
$350K-$550K
Status
Live, expanding to 15 cities
Delivery Partners
10,000+ active partners
1M+
Deliveries / Month
10K+
Delivery Partners
4.7/5
App Rating
Product Screens
Live Website Snapshots
Public-facing screens captured from the live project website and included here to ground the case study in the actual product experience.
How We Solved It
The Solution
We built a last-mile operating system with mobile apps for customers and delivery partners, a dispatch console for operations teams, and an event-driven backend for order state, location pings, ETA updates, vendor handoff, and proof-of-delivery.
The architecture uses Kafka to process high-volume delivery events, PostgreSQL for transactional order data, Redis for hot route and partner state, and location services for routing, geofencing, and ETA calculation. The first MVP launched core ordering and dispatch; the scale phase hardened real-time tracking, partner performance, and city expansion controls.
Dispatch Management Console
Operations teams monitor live orders, rider availability, city zones, ETA risk, and exception queues.
Real-Time Event Backbone
Kafka streams normalize location, order, vendor, payment, and delivery-status events for instant visibility.
Months 1-5
MVP Dispatch
Complete
Customer app, partner app, order lifecycle, basic dispatch
First city launch
Months 6-8
Scale Platform
Complete
Kafka events, live tracking, route optimization, exception handling
500K deliveries/month
Months 9-10
City Expansion
Complete
City controls, partner analytics, SLA dashboards, support workflows
15-city rollout plan
Technology
Architecture & Tech Stack
Frontend
React Native
API Gateway
Secure APIs
Backend
Node.js
Data Layer
PostgreSQL
Integrations
Secure APIs
Frontend
- React Native
- TypeScript
- Next.js operations console
- Mobile design system
Backend
- Node.js
- Kafka consumers
- REST APIs
- Dispatch services
Data & Storage
- PostgreSQL
- Redis
- S3
- Geospatial indexes
Infrastructure
- AWS
- Docker
- CDN
- Terraform
Tools & Services
- Location services
- Datadog
- GitHub Actions
- Support analytics
Features
What We Built
Delivery Partner App
Partners accept jobs, navigate routes, upload proof, manage earnings, and request support.
Live Dispatch Dashboard
Ops teams track orders, riders, ETA risk, delays, and city-zone health in one control room.
Route Optimization
Routing services reduce idle time, batch nearby deliveries, and improve delivery predictability.
Real-Time Location Tracking
Customers and support teams see current delivery state, ETA, and exception signals.
Vendor Handoff Workflow
Stores confirm readiness, handoffs, substitutions, and cancellation reasons without phone calls.
SLA Analytics
Dashboards track delivery speed, partner utilization, cancellation reasons, and city performance.
Results
The Impact
Jhatpat Delivery scaled from MVP dispatch to a production last-mile platform supporting 1M+ deliveries per month and 10,000+ delivery partners. The operations console gave city teams real-time visibility into order state, ETA risk, partner utilization, and support hotspots.
The product improved reliability while supporting growth into 15 cities. Customers received clearer tracking, partners received simpler task flows, and operations leaders could manage exceptions before they became escalations.
1M+
Deliveries / Month
production volume
10K+
Delivery Partners
active partner network
4.7/5
App Rating
partner and customer apps
15
Cities
expansion roadmap
Return on Investment
- Reduced manual dispatch load by giving operations teams a real-time command center.
- Improved delivery predictability through live location, routing, and ETA signals.
- Created a scalable delivery partner workflow for onboarding, jobs, proof, and earnings.
- Established a city expansion model that can be reused without rebuilding core systems.
DigiteraX helped us move from manual dispatch to a real-time delivery platform. The system gives our customers, partners, and operations teams the same source of truth.
Product Lead, Jhatpat Delivery
The Team
People Behind the Project
RM
Rohan Menon
Frontend Architect
Next.js, commerce UX
IV
Isha Verma
Backend Engineer
Node.js, catalog and order APIs
KA
Kabir Ali
Data Engineer
Product data, vendor analytics
LF
Leah Fernandes
QA Lead
Mobile commerce testing, accessibility
Challenges & Lessons
Overcoming Obstacles
Location Event Volume
Thousands of partners generated frequent location pings and state changes.
Used Kafka streams and Redis hot state to keep dispatch responsive.
Delivery scale requires event architecture early.
Partner App Simplicity
Delivery partners needed fast, low-friction task flows during active routes.
Reduced screens, prioritized job actions, and kept proof-of-delivery steps explicit.
Operational apps must respect field context.
ETA Trust
Customers lose confidence quickly when ETAs drift without explanation.
Combined route signals, order state, and exception alerts into customer-facing tracking.
Tracking is a trust feature, not a map feature.
Evolution
From Launch to Continuous Improvement
Month 5
MVP
Complete
Customer and partner apps, basic dispatch
First city live
Month 10
Scale
Complete
Kafka events, tracking, SLA analytics
1M+ deliveries/month
Current
Expansion
In Progress
City rollout controls and partner growth
15-city expansion
Future
Optimization
Planned
Predictive batching and incentive optimization
Lower delivery cost per order
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