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Case study

Fleet Management System

A system that tracks vehicles and trips — where staff can simply ask ChatGPT "how many vehicles are on the road today?" and get a straight answer.

  • Frappe
  • Python
  • MCP
  • Claude
  • ChatGPT

The Challenge

All the vehicle information sat inside the software. So every time somebody wanted to know something simple — how many vehicles are running today, who is driving which one — they had to log in, find the right report and read through it. Every single time.

The Solution

We built the system that keeps track of every vehicle, trip and service date. Then we connected it to ChatGPT and Claude, so the team can just type a question in plain English and get the answer straight away. The answer comes from today's live information, not last week's spreadsheet.

The Technology

Built on Frappe (open-source business software) with a secure bridge — a Model Context Protocol server — that lets AI assistants read the data safely.

More work

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What we automated

The manual steps this removed

Described in our own words — what the build actually does today.

  • Staff ask questions in plain English instead of hunting through reports
  • Answers cover which vehicles are running, who is on which trip, and what is due for service
  • Every answer comes from today's live information, never an old export
  • We control exactly what the AI is allowed to see — it cannot wander into anything else
  • Nobody has to log in and read a report just to answer a quick question
Workflows this demonstrates

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