---
title: "Case Study: GMCT Enterprise AI Solution for Rights of Internment Transfers"
description: AI transforms cemetery management by streamlining Rights of Internment transfers, enhancing compliance, and improving customer service for GMCT.
---

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# [Case Study: GMCT Enterprise AI Solution for Rights of Internment Transfers](https://digitalfrontierpartners.com.au/news/use-case-gmct-enterprise-ai-solution-for-rights-of-internment-transfers)

 Written by [Digital Frontier Partners](https://digitalfrontierpartners.com.au/news/author/digital-frontier-partners) | 2 February 2025 4:22:05 AM

### **Background**

The Greater Metropolitan Cemeteries Trust (GMCT) manages 19 active cemeteries across Melbourne, covering 1,000 hectares of land and serving diverse communities with historical and contemporary burial sites. A key responsibility under the **Cemeteries and Crematoria Act** is the accurate and perpetual maintenance of records, including the management of **Rights of Internment (ROI) transfers**. This process, which involves intricate legal, regulatory, and procedural requirements, has traditionally been labour-intensive, reliant on a small team, and prone to bottlenecks.

To address these challenges, GMCT partnered with **Digital Frontier Partners (DFP)** to develop an **enterprise AI solution** designed to streamline ROI transfers, enhance compliance, and improve customer service delivery.

### **Objectives**

The AI initiative was designed to:

- **Reduce key person dependencies**.
- **Expedite the processing** of ROI transfers.
- **Improve regulatory compliance**.
- **Enhance customer experience** through consistent and accurate responses.
- **Lay the foundation** for scalable AI use cases within GMCT.

### **Implementation Process**

#### **Data Gathering**

- Key documentation, FAQs, and internal policies were identified and integrated into the AI model.
- Historical contact centre queries were used to provide real-world scenarios for training and validation.

#### **Model Training and Testing**

- A dataset of 40 contact centre questions was used to train the AI on common and complex queries.
- Iterative testing ensured accurate, concise, and contextually relevant responses.

#### **Usability Optimisation**

- Initial responses were refined to provide concise summaries with optional detailed expansions, improving usability for staff and customers.

#### **Regulatory Compliance**

- The AI solution was developed within a secure **Azure environment**, ensuring data sovereignty and compliance with state and federal regulations, including privacy and data protection mandates.

### **Outcomes and Benefits**

#### **Operational Efficiencies**

- **Streamlined Processes:** The AI reduced bottlenecks in ROI transfer workflows, enabling faster resolutions.
- **Scalable Knowledge Repository:** Centralised AI knowledge reduced reliance on specialist staff.

#### **Customer Experience Improvements**

- **Consistent Responses:** Families received accurate and reliable information across all interactions.
- **Self-Service Potential:** Future chatbot integration could allow families to access necessary information independently, reducing back-and-forth communications.

#### **Regulatory Assurance**

- Adherence to stringent regulatory frameworks was ensured through secure data management and alignment with government guidelines.

#### **Foundation for Future Growth**

- The proof of concept validated AI’s potential for additional use cases, including supporting outdoor staff with mobile devices and exploring historical data using natural language queries.

### **Challenges**

- **Data Preparation:** Identifying and structuring relevant documents and FAQs for AI training.
- **Usability Testing:** Ensuring responses were accessible and actionable for staff and customers.
- **Change Management:** Building internal confidence in adopting AI technology for critical workflows.

### **Lessons Learned**

1. **Start Small:** A targeted proof of concept enabled GMCT to validate AI’s feasibility and value incrementally.
2. **Partner Collaboration:** Working with experienced solution partners complemented GMCT’s internal capabilities.
3. **User-Centric Design:** Focusing on usability ensured the AI’s outputs were practical and effective.

### **ROI and Future Projections**

- **Time Savings:** Significant reductions in processing times for ROI transfers, freeing up staff for other critical tasks.
- **Cost Efficiency:** Automating knowledge-intensive processes reduces reliance on manual expertise, minimising training costs and mitigating risks.
- **Customer Satisfaction:** Improved service delivery and reduced response times enhance GMCT’s reputation and customer trust.
- **Scalability:** The AI solution sets the stage for broader applications, including advanced record management, chatbot integration, and mobile support for field staff.

### **Conclusion**

GMCT’s enterprise AI solution showcases the transformative potential of targeted AI applications in public sector organisations. By addressing a complex and essential process, the AI initiative not only enhances operational efficiency but also positions GMCT as a forward-thinking leader in leveraging technology for community service. The ongoing roadmap promises continued innovation and value generation for both the organisation and its stakeholders.

 

 

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