Trades & Field Services 3.5 months

AI Integration Into Existing Business Software (Perth Case Study)

Adding AI to a working system — smarter data entry, faster quoting, no disruption. A Perth trade services company had solid software but staff were buried in manual data entry and repetitive quoting. We plugged AI directly into their existing platform to automate the grunt work. Results delivered: - 70% less time spent on data entry - Quoting time reduced from hours to minutes - 95% accuracy on AI-generated quotes - Zero disruption to existing workflows

Perth Trade Services Company

AI DevelopmentAPI DevelopmentCustom Software DevelopmentSoftware IntegrationProcess Automation

70%Reduction in manual data entry time

90%Faster quoting — minutes instead of hours

95%Accuracy on AI-generated quotes

$0Spent on replacing existing software

Understanding the Problem

The Challenge

A growing Perth trade services company had a reliable job management system — but their team was spending hours every day on manual data entry and building quotes from scratch. Every new job meant copying details between systems, looking up pricing, and assembling documents by hand. They didn't want a new system. They wanted their current one to be smarter. The question was: can you add AI without breaking what already works?

Strategic Implementation

The Solution

We integrated AI capabilities directly into their existing software using clean API connections. No rebuild, no disruption — just new intelligence layered on top. For data entry, we built an AI module that reads incoming job requests (emails, forms, even photos from site) and pre-fills job records automatically. Staff just review and approve instead of typing everything from scratch. For quoting, we trained a model on three years of historical quotes to generate accurate estimates based on job type, scope, and location. The system drafts a quote in under a minute — complete with line items, margins, and terms — ready for a quick review and send.

Technologies Used

PythonOpenAI APINode.jsReactPostgreSQLAWS Lambda

How We Did It

Our Approach

Process Mapping & Data Audit

2 weeks

Sat with the team to understand exactly where time was being wasted. Audited three years of job and quoting data to train the AI models.

AI Model Development

5 weeks

Built and fine-tuned models for automated data extraction and quote generation using real business data. Tested accuracy against manual outputs.

Integration & API Build

4 weeks

Connected the AI modules to the existing system via APIs. Built a clean interface for staff to review AI suggestions before they go live.

Training & Rollout

2 weeks

Trained the team, ran both manual and AI processes side by side for two weeks, then switched over once confidence was high.

We didn't want to throw out our system — we just wanted it to do more. Hello People added AI that actually fits how we work. Our guys save hours every day and the quotes are spot on.
Managing DirectorPerth Trade Services Company

Measurable Outcomes