Built for the speed of quick-commerce.
Dark-store inventory, hyperlocal demand forecasting, and rider performance — a control tower built around 10–15 minute delivery windows, not next-day shipping.
- Delivery SLA
- 10–15 min
- Forecast
- Hyperlocal
- Inventory view
- Per dark store
What's included
Visibility at the speed you actually sell
Quick-commerce fails or wins on inventory precision and delivery speed — this is built around exactly those two things.
Real-time sales tracking
SKU-level sales tracked across every dark store as it happens, not in a report the next morning.
Demand planning
Plan stock levels per dark store around actual demand patterns, not a single citywide average.
Demand forecasting
Hyperlocal forecasts that react to recent velocity, weather, and local events — not last quarter's trend line.
Minute-level SLA tracking
SLA measured in minutes, not days — built for 10–15 minute delivery promises, not next-day shipping.
Rider & delivery performance
Delivery partner performance tracked per dark store, so slow zones get caught before they become churn.
Stockout & inventory tracking
Live stock visibility per dark store, with early warning before a fast-moving SKU actually runs out.
Possible automations
Automations for quick-commerce
A sample of what gets automated for a dark-store operation — scoped to your store count and SLA targets.
What actually changes
Where this moves your numbers
Not features for the sake of features — here's exactly what each one fixes for a dark-store operation.
Stockout risk flagged before it happens — the store gets a replenishment nudge, not a complaint.
Instead of: A dark store runs out of a fast-mover mid-shift, and you find out from a cancelled order.
Hyperlocal forecasts react to this week's velocity, per store — not a stale trend line.
Instead of: Demand planning uses last quarter's citywide average.
Rider performance scored per dark store, so a slow zone gets fixed before it costs you customers.
Instead of: A slow rider zone gets noticed only after churn shows up in retention numbers.
Every order timed against your 10-15 minute promise, live, store by store.
Instead of: SLA is 'measured' by spot-checking a few late orders after the fact.
Inventory reallocation between nearby stores suggested automatically, before the shelf goes empty.
Instead of: Nobody sees a stockout risk until the app shows 'out of stock'.
Your rules, your thresholds — an email or WhatsApp alert fires the second a store's numbers cross the line you set.
Instead of: Custom alerts don't exist — everyone just checks the dashboard and hopes.
Proof, not slides
Dark-store ops, live
Interactive mini-builds on synthetic sample data — the same mechanics that run a real dark-store network.
Q-commerce dark store wall
~2 minA live operations wall across six dark stores, refreshing every few seconds.
6
dark stores, one wall
Consensus demand plan
~2 minOne editable grid where statistical, sales, marketing, and finance views converge.
4→1
demand views merged
Statistical forecast engine
~2 minFour forecast models, switchable per SKU, with accuracy tracked alongside.
4
models, one switch
Zone-level reconciliation
~2 minAn origin × destination heatmap that shows exactly which lanes are leaking money.
10
leaking lanes, ranked
How the engagement works
Week by week, start to handover
Week 1
Discovery & scoping
Map dark-store operations, SLA targets, and current demand-planning process.
Weeks 2-3
Data & pipeline
Connect dark-store inventory, order, and rider-performance feeds in near real time.
Weeks 3-4
Build
The live ops wall, demand forecast, and SLA alerts built and wired to real stores.
Week 5
UAT & iteration
Run it against a live shift before rolling out network-wide.
Weeks 5-6
Handover
Training for store ops leads, documentation, and a clean handoff.
Get in touch
Still tracking orders in a spreadsheet?
Let's talk about what a control tower would look like for your operation — built around how your team actually works.
Book a free 15-minute session
No pitch — just 15 minutes to understand what you're trying to solve and whether a build like this actually fits. Share two times that work and I'll confirm one.