A guide to building custom logistics and supply chain software — fleet management, inventory tracking, route optimization, warehouse management, and the integration challenges unique to this industry.
What is logistics software development? Logistics software development involves building applications that manage the movement of goods from origin to destination — including fleet management, route optimization, warehouse management systems (WMS), inventory tracking, shipment tracking, last-mile delivery, and supply chain visibility platforms. Key technical challenges include real-time GPS tracking, complex routing algorithms, integration with multiple carrier APIs, barcode/QR scanning, and handling high-volume data from IoT sensors.
Logistics companies run on a combination of Excel spreadsheets, WhatsApp groups, phone calls, and sheer willpower.
That's not an exaggeration. We've worked with logistics operators managing 200+ vehicles who tracked deliveries in shared Google Sheets. Warehouse managers who counted inventory by walking the floor. Dispatchers who planned routes in their heads because "the software doesn't know about the construction on NH48."
The software exists — SAP, Oracle TMS, ShipStation, Locus, FarEye. But most logistics companies either can't afford enterprise solutions, find them too rigid for their specific operations, or need something that bridges the gaps between multiple systems and workflows.
This guide covers what it takes to build logistics software that works in the real world — not just on a demo slide.
Tracking and managing vehicles — location, status, driver assignments, fuel consumption, maintenance schedules.
Core features: Real-time GPS tracking on a map dashboard, trip assignment and tracking, driver profiles and performance, fuel management, vehicle maintenance alerts, route history and replay.
The hard part: Real-time tracking at scale. Hundreds of vehicles sending GPS pings every 10–30 seconds. That's a lot of data to ingest, process, and display without the dashboard grinding to a halt.
Managing what's inside the warehouse — receiving, storage, picking, packing, and shipping.
Core features: Inventory receiving and put-away, bin/location management, pick lists and wave planning, packing and shipping, barcode/QR scanning, stock counts and cycle counting, integration with order management.
The hard part: Warehouse workers aren't sitting at desks. They're on their feet, holding scanners, moving fast. The UI needs to work on rugged handheld devices with one hand. Every extra tap costs time and money.
Figuring out the best path for deliveries — considering distance, time windows, vehicle capacity, traffic, and priority.
Core features: Multi-stop route planning, time window constraints, vehicle capacity constraints, real-time traffic integration, driver assignment optimization, route monitoring and deviation alerts.
The hard part: This is a genuine computer science problem (Vehicle Routing Problem — VRP). Solving it optimally is NP-hard. For anything beyond 20–30 stops, you need heuristic algorithms or specialized solvers like Google OR-Tools, OptaPlanner, or commercial APIs like Google Routes API or Routific.
Knowing what you have, where it is, and when you'll run out.
Core features: SKU management, stock levels by location, stock movements (inbound, outbound, transfers), low-stock alerts, batch/lot tracking, expiry date management, reporting and analytics.
The hard part: Data accuracy. Inventory systems are only as good as the data going in. One missed scan, one wrong count, and the whole system lies to you. Design for error correction, not just error prevention.
The final leg — getting packages from a hub to the customer's door.
Core features: Delivery assignment and dispatch, real-time tracking (for both dispatcher and customer), proof of delivery (photo, signature, OTP), delivery attempt management (re-schedule, return to hub), driver app with turn-by-turn navigation, customer notifications (SMS, WhatsApp).
The hard part: Everything happens in real time, and the environment is unpredictable. Addresses are wrong. Customers aren't home. Roads are blocked. The system needs to handle constant exceptions gracefully.
End-to-end view of goods moving through the supply chain — from supplier to warehouse to customer.
Core features: Order tracking across multiple stages, supplier management, shipment milestones and status, exception alerts (delays, damages, customs holds), analytics and reporting, multi-carrier tracking.
The hard part: Integration. You're aggregating data from multiple carriers, warehouses, customs brokers, and internal systems — each with different data formats, update frequencies, and reliability levels.
| Scenario | Recommendation |
|---|---|
| Standard 3PL operations, fewer than 50 shipments/day | Off-the-shelf (ShipStation, Shiprocket, Delhivery API) |
| Single warehouse, standard pick-pack-ship | Off-the-shelf WMS (Zoho Inventory, Unicommerce) |
| Enterprise with complex, multi-location operations | Enterprise solutions (SAP TMS, Oracle, Blue Yonder) if budget allows |
| Unique workflows that no tool supports | Custom build |
| Need to integrate 4+ systems that don't talk to each other | Custom build (often as a middleware/orchestration layer) |
| Building a logistics product/startup | Custom build (this is your product) |
| Fleet of 100+ vehicles with specific dispatch logic | Custom build with off-the-shelf GPS hardware |
The honest take: most logistics companies don't need to build everything custom. The smart approach is to use off-the-shelf tools where they work and build custom software to fill the gaps — usually the integration layer, the dispatch logic, or the customer-facing tracking experience.
Logistics is inherently real-time. Vehicles are moving. Inventory is changing. Deliveries are happening. The technical architecture needs to handle:
Warehouse workers in areas with poor connectivity. Drivers in underground parking. Rural delivery routes with no signal.
A typical logistics operation touches:
Each integration has its own API format, authentication method, rate limits, and reliability characteristics. Build an integration layer that abstracts these differences — don't scatter API calls throughout your application code.
For more on integration architecture, see our guide on API development services.
Similar to real estate software, logistics software is map-heavy.
| Component | Recommendation | Why |
|---|---|---|
| Frontend | React or Next.js | Complex dashboards with real-time updates. |
| Mobile (drivers/warehouse) | React Native or Flutter | Need offline support, camera (scanning), GPS. |
| Backend | Node.js or Go | High concurrency for real-time data. Go if you need maximum throughput. |
| Database | PostgreSQL + TimescaleDB | Relational data + time-series GPS/sensor data. |
| Message queue | RabbitMQ or AWS SQS | Decoupling event processing from API requests. |
| Real-time | WebSockets (Socket.io) or SSE | Live dashboard updates, tracking. |
| Maps | Mapbox or Google Maps | Mapbox for cost at scale. Google for routing API quality. |
| Search | Elasticsearch | For shipment search, tracking number lookup across millions of records. |
Logistics projects tend to be larger than average because of the integration complexity and real-time requirements.
| Project type | Timeline | Cost range |
|---|---|---|
| Shipment tracking portal | 4–6 weeks | ₹5L–₹10L |
| Fleet management dashboard | 6–10 weeks | ₹10L–₹20L |
| Warehouse management system | 8–14 weeks | ₹15L–₹30L |
| Route optimization engine | 6–10 weeks | ₹12L–₹25L |
| Last-mile delivery platform | 10–16 weeks | ₹20L–₹40L |
| Full logistics platform (multi-module) | 16–28 weeks | ₹35L–₹60L+ |
The integration work alone — connecting to carrier APIs, ERP, payment systems, and IoT devices — can account for 30–40% of the total development time. Don't underestimate it.
For a broader view of development costs, read our guide on what it costs to build a web app.
1. Building before mapping the operation. Logistics software is only as good as your understanding of the actual operation. Spend time on the warehouse floor. Ride along with drivers. Watch dispatchers work. The gap between how management thinks the operation works and how it actually works is always larger than expected.
2. Ignoring the human element. Drivers, warehouse workers, and dispatchers are your primary users — and they're often not tech-savvy. If the app is slower than making a phone call, they'll make the phone call. Design for speed, simplicity, and forgiveness (easy undo, confirmation on destructive actions).
3. Underestimating integration work. "We just need to connect to FedEx and Delhivery" — famous last words. Each carrier API has its own quirks, rate limits, error handling patterns, and update frequencies. Budget serious time for integration, testing, and handling edge cases.
4. No offline strategy. If your warehouse app stops working when the WiFi drops, you've failed. Logistics happens in environments where connectivity is unreliable. Offline-first isn't a nice-to-have; it's a requirement.
5. Over-engineering route optimization. Unless routing is your core product, don't build a custom routing engine. Use Google Routes API, Routific, or OR-Tools. The cost of these services is a fraction of the cost of building and maintaining your own optimizer.
If you're building logistics or supply chain software:
Or talk to us. We've built fleet management dashboards, delivery tracking platforms, and warehouse tools for logistics companies. We'll help you identify where custom software will actually move the needle — and where existing tools are good enough.
If this guide resonated with your situation, let's talk. We offer a free 30-minute discovery call — no pitch, just honest advice on your specific project.
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