Restaurant Delivery Software

Faster deliveries. Smarter dispatch. Happier customers.

Give delivery platforms an AI layer that optimises routing, handles exceptions, and keeps operations running smoothly — even when things go wrong.

When one driver calls in sick, everything falls apart.

Delivery ops are a real-time coordination problem. Routes need rebalancing, order volumes spike unpredictably, drivers call in sick, restaurants run late. Your dispatchers are managing by firefighting — toggling between screens, making phone calls, and hoping the next delivery isn't late. Your platform has all the data needed to handle this intelligently. It just needs an AI layer to connect the dots in real time.

Real-time delivery intelligence.

Sidenet's AI assistants sit inside your delivery platform and handle the coordination your dispatchers shouldn't have to do manually. Route optimisation, volume forecasting, and order management — all through natural language.

Delivery Ops — Live Dispatch
Dashboard
Dispatch
Drivers
Zones
Reports
Zone 3 — Active OrdersDriver 12 sick
#89112:40Reassigned → 7On time
#89412:55Reassigned → 15On time
#8971:10Reassigned → 7On time
Sidenet
Reassign zone 3 — driver 12 called in sick.
Done. 3 orders reassigned to drivers 7 & 15. All ETAs within original windows. Customers notified.
via Dispatch Agent
Routing
Orchestrator
Dispatch
Forecast
Orders

AI assistants built for delivery operations.

Each of these assistants can be built, configured, and shipped using Sidenet — no AI engineering required.

Dispatch Assistant

Optimises driver routes and assignments in real time. Handles reassignments when things go wrong.

Sidenet Assistant
Reassign orders for zone 3 — driver 12 just called in sick.
Zone 3 reassignment complete: • Order #891 (due 12:40) → Driver 7 (2 min detour, already nearby) • Order #894 (due 12:55) → Driver 15 (finishing current delivery at 12:35) • Order #897 (due 1:10) → Driver 7 (picks up after #891) All revised ETAs within original delivery windows. Customers notified of minor timing updates. 2 upcoming orders in zone 3 (1:30, 1:45) have been pre-assigned to Driver 15.
Value

Fewer late deliveries. Faster exception handling. Dispatchers manage by exception, not by micromanagement. A 5-minute disruption is resolved in 30 seconds.

Forecasting Assistant

Predicts order volume by zone, time, and day to optimise driver staffing.

Sidenet Assistant
What's the expected order volume for Saturday evening in zones 1-4?
Saturday evening forecast (5pm-10pm): Zone 1: 45-52 orders / 6 drivers recommended (last Sat: 48) Zone 2: 38-44 orders / 5 drivers recommended (last Sat: 41) Zone 3: 28-35 orders / 4 drivers recommended (last Sat: 31) Zone 4: 18-22 orders / 3 drivers recommended (last Sat: 20) Total: 129-153 orders, 18 drivers recommended. Note: Local football match ends at 7pm — expect a 20-30% spike in zones 1-2 between 7:15-8:00pm. Consider staging 2 extra drivers near those zones.
Value

Right-sized staffing. Lower cost per delivery. Better service levels. Predictable ops instead of reactive ones.

Ordering Assistant

Streamlines order intake and processing through conversational AI.

Sidenet Assistant
Place a reorder of last week's standing order for the King Street location, but swap the tiramisu for panna cotta.
Standing order for King Street (last week: Order #7834): • 24x Margherita Pizza ✓ • 18x Caesar Salad ✓ • 12x Garlic Bread ✓ • 12x Tiramisu → 12x Panna Cotta (swapped) • 8x Sparkling Water ✓ Total: £342.80 (prev: £348.40, panna cotta is £0.47/unit less) Confirm and send to supplier?
Value

Faster order processing. Fewer errors. Restaurant partners spend less time on admin and more time on service.

Go live in your delivery platform in days.

1

Embed the chat

Embed the Sidenet chat in your delivery platform with a single line of code.

2

Configure your agents

Configure dispatch, forecasting, and ordering agents in Studio. Connect to your routing engine, order system, and staffing data.

3

Ship & monitor

Test internally, then ship to your delivery operations customers with full observability.

Delivery ops shouldn't run on phone calls and spreadsheets. Ship AI that fixes that.