Case Studies

Real results from real projects. See how we help Australian businesses transform operations with AI.

Intelligent Customer Service Assistant

Major Australian Financial Institution

Financial Services
80% Workload Reduction

The Challenge

A leading Australian bank was struggling to manage thousands of repetitive customer enquiries daily. Support staff spent hours answering the same questions about account policies, loan products, and compliance requirements — leading to slow response times and rising operational costs.

Our Solution

We designed and deployed an enterprise-grade RAG (Retrieval-Augmented Generation) chatbot integrated with the bank's internal knowledge base. The system uses semantic search across policy documents, FAQs, and product guides to deliver accurate, context-aware responses in real time.

Results & Impact

80% reduction in manual enquiry handling
Instant 24/7 responses to customer questions
95% accuracy in policy-related answers
Freed up support staff for complex customer issues

Technologies Used

Claude AILangChainVector DatabasesPythonFastAPI

Automated Document Processing Pipeline

National Insurance Provider

Insurance
65% Faster Claims Processing

The Challenge

An Australian insurance company was drowning in paperwork. Claims agents manually reviewed thousands of documents each week — receipts, medical reports, invoices, and supporting files — leading to processing delays and frustrated customers.

Our Solution

We built an AI-powered document intelligence system that automatically extracts, classifies, and validates data from unstructured documents. The solution integrates with their existing claims management platform, routing processed claims for approval or flagging exceptions for human review.

Results & Impact

65% faster claims processing time
90%+ accuracy in data extraction
40% reduction in manual data entry
Improved customer satisfaction scores

Technologies Used

Azure Document IntelligencePythonOpenAIFastAPISQL Server

Demand Forecasting & Inventory Optimisation

Multi-Location Retail Chain

Retail
$1.2M Annual Savings

The Challenge

A Melbourne-based retail chain with 25+ stores was losing money to overstocking and stockouts. Their legacy forecasting relied on manual spreadsheets and gut feel, leading to missed sales opportunities and excess inventory write-offs.

Our Solution

We developed a machine learning forecasting model that predicts demand at the SKU level across all locations. The system incorporates seasonality, promotions, local events, and historical trends to generate weekly replenishment recommendations.

Results & Impact

30% reduction in overstock
22% fewer stockouts
$1.2M annual savings in inventory costs
Automated weekly forecasting reports

Technologies Used

Pythonscikit-learnProphetPower BIAzure ML

Enterprise Knowledge Search Platform

Professional Services Firm

Professional Services
5x Faster Information Retrieval

The Challenge

A mid-sized consulting firm had years of proposals, case studies, and client deliverables scattered across SharePoint, email, and local drives. Consultants wasted hours searching for relevant past work — or worse, recreated documents that already existed.

Our Solution

We built a semantic search platform that indexes all internal documents and enables natural language queries. Consultants can now ask questions like 'Find examples of digital transformation proposals for retail clients' and get ranked, relevant results in seconds.

Results & Impact

5x faster document retrieval
60% reduction in duplicate work
Improved proposal win rates
Centralised, searchable knowledge base

Technologies Used

Azure Cognitive SearchOpenAI EmbeddingsPythonReactSharePoint API

Real-Time Property Market Analytics

Property Investment Firm

Real Estate
Real-Time Market Insights

The Challenge

A Melbourne property investment firm needed to track rental yields, suburb demographics, school rankings, and transport links across hundreds of suburbs. Data was fragmented across multiple sources, making analysis slow and inconsistent.

Our Solution

We designed a custom Power BI dashboard that integrates live data feeds from property APIs, government datasets, and internal portfolio data. The solution includes automated daily refreshes and interactive drill-downs for suburb-level analysis.

Results & Impact

Unified view of 200+ suburbs
Automated daily data updates
Interactive suburb comparison tools
Faster investment decision-making

Technologies Used

Power BIPythonAzure Data FactorySQL Server

AI-Powered Reception & Booking System

Childcare Centre Group

Childcare & Education
70% Fewer Missed Calls

The Challenge

A group of childcare centres across Melbourne was losing potential enrolments due to missed calls. Reception staff were stretched thin — juggling parent enquiries, tour bookings, and daily operations. After-hours calls went unanswered, and voicemails often piled up for days.

Our Solution

We deployed an AI-powered voice receptionist that handles inbound calls 24/7. The system answers common questions about availability, fees, and centre hours, and seamlessly books centre tours directly into their calendar. Complex enquiries are transcribed and routed to staff with full context for follow-up.

Results & Impact

70% reduction in missed calls
24/7 enquiry handling without additional staff
3x increase in tour bookings
Staff freed up to focus on children and parents on-site

Technologies Used

VAPIElevenLabsAWS LambdaGoogle Calendar APIPython

Intelligent Email & Task Automation

Accounting & Advisory Firm

Professional Services
15 Hours Saved Weekly

The Challenge

Partners at a growing accounting firm were overwhelmed with client emails, document requests, and follow-ups. Administrative tasks were eating into billable hours, and important client requests sometimes slipped through the cracks.

Our Solution

We deployed an agentic AI assistant that monitors incoming emails, extracts key requests, prioritises tasks, and drafts responses for review. The system integrates with their practice management software to log activities and schedule follow-ups automatically.

Results & Impact

15+ hours saved per week on admin tasks
Zero missed client follow-ups
50% faster email response times
Improved client satisfaction

Technologies Used

Claude AIn8nMicrosoft Graph APIPython

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