Dark store operators and grocery delivery startups hit the same ceiling: dispatch boards run on WhatsApp, pickers burn time retracing routes, inventory counts lag behind actual stock, and every new zone you add makes the problem worse. The 10-minute promise depends on software that moves as fast as your operations. When it doesn't, customers churn before you fix it.
Dark store inventory management with SKU-level tracking, expiry monitoring, and auto-replenishment triggers
Picking route optimization that cuts average fulfillment time to under 3 minutes per order
Rider dispatch with live zone assignment, order batching, and GPS tracking across your full fleet
Real-time order tracking for customers and operations, from confirmed to doorstep
The problem
Riders returning to the store because the app showed stock that wasn't there when picking began?
Dispatch managed manually across group chats while order volume climbs and delivery windows slip?
No way to see, in real time, which dark store has capacity and which zone is bleeding margin?
Short answer
RaftLabs builds custom grocery delivery and q-commerce software for dark store operators, grocery delivery startups, and retail chains launching rapid delivery. Our grocery delivery app development work covers dark store inventory management, picking route optimization, rider dispatch, real-time order tracking, and multi-slot delivery scheduling. Most teams launch a validated v1 in 12 to 20 weeks at a fixed cost, then grow it.
Q-commerce software (quick commerce software) is the operational layer that powers 10-to-30-minute grocery and on-demand delivery. It covers dark store inventory management, digital pick lists with route optimization, rider dispatch with real-time GPS tracking, multi-slot delivery scheduling, and the customer-facing app that ties it all together. Unlike standard e-commerce platforms, grocery delivery app development for q-commerce is built around high-frequency, low-value orders where fulfillment speed and inventory accuracy are the primary constraints.
01 Diagnosis
Pickers burn time retracing routes across the dark store
When pick lists are generated in the order items were added to the cart rather than by shelf location, a picker walks the entire store multiple times per order. At low volume, that's an inconvenience. At 200 orders per hour across multiple concurrent pickers, the collision of walking paths adds minutes to every fulfillment cycle and blows the delivery window you promised customers.According to Grand View Research (2026), the global quick commerce market is projected to reach $1.3 trillion by 2033, growing at 23.5% annually. At that growth rate, the platforms that win will be the ones that can fulfill reliably at volume, not just at launch scale. Optimized pick route generation, shelf-location mapping, and batch picking algorithms that group nearby SKUs across multiple concurrent orders are what separate a 3-minute fulfillment cycle from a 9-minute one.
Inventory counts lag and customers see stock that isn't there
When a customer orders a product, the picker confirms it's not on the shelf, and the app has to issue a substitution or cancellation, you've already lost. The customer experience breaks at that moment, and the recovery rate for a failed first order is low. The root cause is almost always an inventory system that updates counts at receiving and end-of-day rather than at every pick.Dark store inventory accuracy requires SKU-level tracking that adjusts in real time as picks happen. Auto-replenishment triggers fire before a product reaches zero. Expiry date monitoring removes near-expired stock from the available pool before a customer orders it. A well-built inventory system keeps the customer app and the warehouse in sync so every order that confirms is an order that ships.
Rider dispatch runs on WhatsApp and breaks when order volume climbs
Manual dispatch, whether via group chat, a shared spreadsheet, or a dispatcher calling riders directly, has a hard ceiling. It works at low volume. As zones multiply and order density rises, dispatchers can't optimize assignment in real time, riders double back across zones, and delivery windows slip. Customers call or open the app and see "on the way" with no accurate ETA.Automated rider dispatch assigns orders to the nearest available rider in real time, batches multiple orders in the same zone into a single run, and tracks fleet position across the entire delivery area. Dynamic zone management adjusts capacity allocation as order density shifts through the day. The result is fewer idle riders during quiet periods and fewer late deliveries during peaks, without adding a dispatch coordinator for every new zone you open.
No single view of which dark store has capacity and which zone is bleeding margin
Operators running multiple dark stores typically pull data from separate systems: inventory from the WMS, orders from the OMS, and delivery performance from the last-mile provider. By the time anyone assembles a picture of which store is running low on a category, which zone has a 20-minute average delivery time, or which shift is consistently over on rider cost, the operational window to act has closed.A unified operations dashboard surfaces dark store stock levels, live order pipeline, rider positions, fulfillment time by zone, and cost per delivery in one screen. That gives an operations manager what they need to reassign riders, trigger a replenishment run, or close a zone before margin deteriorates. That visibility is what enables decisions in real time, not in a Monday morning debrief.
02 What we ship
The customer app covers product browsing with real-time stock availability, one-tap reorder from purchase history, multi-slot and express delivery scheduling, live order tracking from confirmed to doorstep, and in-app substitution management when a product is unavailable. Payment integrations include Stripe, Adyen, Apple Pay, Google Pay, and local payment methods by market.
We build for conversion and retention, not just feature coverage. That means fast load times on low-bandwidth mobile connections, frictionless address management, and a delivery tracking screen that gives customers enough information to stop wondering where their order is without flooding your support queue with "where is my order" tickets.
Built for grocery delivery startups, dark store operators launching a direct-to-consumer channel, and retail chains adding rapid delivery to an existing app.
Inventory management built for dark store operations covers SKU-level stock tracking updated at every inbound receipt, pick confirmation, and stock adjustment, not just at scheduled count cycles. Auto-replenishment triggers fire when a SKU drops below a configured threshold and generate a purchase order or supplier request without manual intervention. Expiry date tracking flags near-expired products and removes them from the customer-visible inventory pool automatically.
Batch management handles products with multiple expiry dates or lot numbers. Integration with WMS platforms and ERP systems including SAP, Oracle, and mid-market alternatives keeps the dark store system of record in sync with the broader supply chain. Waste analytics identify the categories and SKUs generating the most spoilage so buying decisions can reduce it.
Built for dark store operators managing fresh, chilled, and ambient categories, grocery platforms with multiple fulfillment locations, and retail chains migrating from manual stock counting.
The picker app generates digital pick lists ordered by shelf location rather than cart entry sequence, so a picker walks the minimum distance per order. Batch picking algorithms group SKUs from multiple concurrent orders into a single efficient path when order density supports it. Barcode scanning verification confirms the correct product and quantity at each pick, reducing wrong-item errors before the order is packed.
Shelf-location mapping is configured to match the physical dark store layout, and the system updates pick routes when a product is moved to a different slot. Average fulfillment time targets of under 3 minutes per order are achievable with route optimization and a well-mapped store layout. The picker app runs on Android and iOS handheld scanners and standard smartphones.
Built for dark stores aiming to sustain sub-10-minute delivery promises at volume and for platforms managing concurrent pickers across multiple aisles.
Automated dispatch assigns packed orders to the nearest available rider using real-time GPS position, delivery zone boundaries, and current load. Order batching groups multiple orders in the same delivery zone into a single run, reducing the per-delivery cost and idle rider time between assignments. Dynamic zone management reallocates rider capacity across zones as order density shifts through the day.
The rider app provides turn-by-turn delivery navigation via Google Maps or HERE Maps APIs, in-app proof of delivery with photo capture and customer signature, and two-way messaging with the dispatcher without leaving the app. Rider performance dashboards track delivery time, acceptance rate, and kilometers per delivery at the individual and fleet level. Integration with third-party last-mile providers via their APIs is available where a hybrid fleet model is required.
Built for q-commerce operators managing their own rider fleet, platforms using a mix of employed and gig riders, and delivery businesses needing zone-level cost visibility.
Delivery slot management covers express slots for immediate fulfillment, scheduled slots up to 7 days ahead, and dynamic slot availability that closes or limits a time window when rider capacity or dark store throughput approaches its ceiling. Customers see only available slots based on their delivery address and the serving dark store's live capacity, reducing over-commitment and late deliveries.
Smart scheduling algorithms distribute order load across the day to avoid fulfillment peaks, fill low-demand windows with incentivized pricing, and batch geographically close orders into the same delivery run. The slot management system connects directly to the rider dispatch engine so scheduled orders enter the dispatch queue at the right time without manual coordination. Integration with Google Calendar and Apple Calendar for customer delivery reminders is included.
Built for grocery operators offering both express and scheduled delivery, platforms managing demand smoothing across a constrained rider pool, and retail chains with strict last-mile SLAs.
A unified operations dashboard brings dark store stock levels, live order pipeline, rider positions, fulfillment time by zone, and cost per delivery into one screen. Store managers see inbound receiving queues, low-stock alerts, and daily waste totals without switching between systems. Operations leads see delivery performance by zone, slot utilization, and rider productivity across the full network.
Demand forecasting uses historical order data, day-of-week patterns, local events, and seasonal trends to generate category-level buying recommendations that reduce both stockouts and over-buying. Margin analytics break down cost per order by store, zone, and time slot so pricing and zone decisions are grounded in real numbers. Integration with BI tools including Metabase, Tableau, and Google Looker Studio is available for teams with existing reporting infrastructure.
Built for dark store operators with multiple locations, grocery delivery platforms needing real-time network visibility, and operations teams replacing manual reporting with automated dashboards.
03 How we work
Trusted by
04 Track record
A pure dark-store q-commerce platform is adjacent to, not identical to, some of what we have built. We are direct about that. We built a food-order-management platform that consolidated GrabFood, GoFood, and ShopeeFood into one system with zero order errors since launch. We built a multi-carrier shipping platform that routes thousands of shipments across 70+ countries from a single dashboard. Both share the hard parts of q-commerce: real-time inventory, dispatch, and last-mile tracking under load. Ask for a walkthrough of either during scoping.
07 Why us
08 Questions
Yes. We build the full platform: customer app with real-time tracking, picker app with optimized route lists and barcode scanning, rider app with live dispatch and zone assignment, and an operations dashboard with inventory, order, and delivery visibility in one place. The systems share a single data layer so stock counts, order status, and rider positions are consistent across all surfaces.
Dark store inventory accuracy depends on SKU-level tracking updated at every pick, not just at receiving and end-of-day. We build inventory systems where each pick confirms or flags the count, auto-replenishment triggers fire when threshold levels are hit, and the customer app never shows a product as available unless the warehouse system confirms stock. This cuts the substitution and cancellation rate that erodes customer trust.
We ship the smallest useful slice first. A v1 you launch to validate demand, covering the customer ordering app, one dark store's inventory, and rider dispatch, starts around $60,000 and goes live in about 12 to 20 weeks. From there the platform grows. Multi-dark-store management, demand forecasting from historical order data, and dynamic pricing push a full build toward $120,000 and up over another 20 to 32 weeks. Enterprise-grade platforms with deep POS and ERP integrations reach $200,000 and beyond. Cost is fixed and agreed before each phase begins.
Yes. We integrate with POS systems, warehouse management systems, and ERP platforms including SAP, Oracle, and mid-market options. For delivery, we connect with third-party last-mile providers via their APIs or build native rider management directly into the platform. Payment integrations with Stripe, Adyen, and local payment methods are standard. We scope all integration points during discovery so there are no hidden costs later.
White-label platforms are the right choice if your business model is standard and you need to launch in weeks, not months. Custom software earns its cost when your operations have a specific dark store layout, a delivery zone model, or a customer experience requirement that the platform's configuration layer can't accommodate without significant workarounds. Custom also makes sense when you need to own the data and the margin, not pay a per-order license fee as you scale. We scope the decision during discovery and tell you honestly which path fits your situation.
Tell us what you are building and we will scope it out together.
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