Brand
Case Study

Office Support — AI‑Optimised Back Office

Stock visibility, order management and AI‑assisted route optimisation for an aggregates company operating time‑critical deliveries.

Miles−12–18%On‑time+9 ppPaperworkdigitised
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Client

Regional aggregates supplier

Sector

Logistics / Manufacturing

Engagement

16 weeks | Fixed scope MVP

Outcomes

  • Real‑time stock and order status across depots
  • AI routing cut average delivery miles by 12–18%
  • On‑time delivery improved by 9 p.p.
  • Digitised paperwork and invoicing, fewer errors

The challenge

Paper‑based processes and siloed spreadsheets made it hard to plan deliveries and keep customers informed. Routes were planned manually without considering traffic or load constraints.

Objectives

  • Centralise stock and order data
  • Automate route planning with constraints (vehicle, weight, time windows)
  • Provide customer‑facing updates and proof‑of‑delivery
  • Deliver an MVP fast with room to scale

How we delivered

Approach

  • Discovery workshops, value stream mapping and data audit
  • Iterative delivery with weekly demos and field feedback
  • Heuristics‑first optimiser backed by ML for ETA predictions
  • APIs to integrate telemetry and e‑invoicing later

Delivery lifecycle

Discovery
2 weeks
MVP design
2 weeks
Build
8 weeks
Pilot and optimise
4 weeks

Solution highlights

  • Dispatcher dashboard with real‑time stock and deliveries
  • Route optimiser respecting depot hours and vehicle constraints
  • Driver app for turn‑by‑turn, POD capture and exceptions
  • Notifications to customers with live ETAs

Tech stack

TypeScriptNode.jsReactPythonPostgreSQLAzureTerraformGitHub Actions

Operations

Monitoring with metrics and traces, blue/green deploys, error budgets tied to service levels.

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