Demand and capacity planning
Forecast order volume and service pressure so operations teams can plan coverage around observable signals.

Marketplace · On-demand delivery
A connected customer, courier and administration platform for multi-category on-demand services.
AI Development opportunities
A modern extension could help teams interpret marketplace activity faster while keeping customer communication, courier treatment and operational decisions under human control.
Forecast order volume and service pressure so operations teams can plan coverage around observable signals.
Summarize delayed, rejected or unusual orders and route consequential cases to an accountable operator.
Retrieve approved order and policy context, draft responses and keep customer or courier escalation with a person.
Surface changes in delivery patterns, integrations and marketplace behavior for investigation—not automatic judgment.
Any AI feature would require location-data privacy, worker-impact review, fairness testing, explainable signals, measurable evaluation, model monitoring and a human escalation path.
Explore AI Development →01
Project context
Lezzoo aggregates food, groceries, pharmacy and cosmetics, flowers, laundry, gas and additional local services.
Its product model connected convenience and choice with a marketplace designed for customers whose routines depended on fast local fulfillment.
02
Problem to be solved
The seven-month engagement used two-week sprints, daily developer meetings, twice-weekly client calls and sprint demos.
03
Customer system
The customer system supported sign-in, ordering, favorites, supplier and product browsing, and customer-service chat. New systems integrated with that established product.



04
Administration system
Configurable roles gave administrators, supervisors and dispatchers permissions aligned with their responsibilities.

Create cities by country, then filter the operating structure by location.
Break cities into subzones with configurable pricing.
Create and edit courier and administration teams with role-based permissions.
Assign cars, bikes and other vehicle categories to couriers and pickup points.
Track regular and courier orders in real time.
Review completed work and app-calculated earning history.
Present courier rankings and ratings to authorized teams.
05
Courier system

Find suitable orders for a courier shift.
Move work through accepted, rejected, pickup, transit and completion states.
Track personal delivery activity and the historical rank view.
Give couriers a direct route to dispatchers when an order needs attention.
Technology
The architecture used microservices, NATS, Bull queues, CQRS, frontend and backend CI/CD, and AWS deployment.
NestJS
TypeScript
MongoDB
Redis
Docker
NATS
Socket.IO
Bull
AWS CloudFormation
React
Next.js
Redux-Saga
CI/CDDelivery snapshot
The PDF states that eight people participated: one project manager, one UI/UX designer and six developers.
The team brought together product management, UI/UX design and six developers.
Project outcome
The revenue model used delivery fees that varied by time, distance and service.
The delivered systems created a smooth, scalable experience for customers, couriers and operations teams.
Building an on-demand platform?
We can help shape the product, systems and AI roadmap around the people and workflows that keep delivery moving.
Discuss your platform