A.POC.0001 - A.POC.0001 - MLA Virtual Advisor POC (Caitlyn AI Platform)

Summary

Access to research and industry knowledge has long been a challenge for producers and staff across Australia's red meat and livestock industry. Despite decades of investment, MLA's extensive R&D library has remained difficult to navigate for the people who need it most. This project tests whether agentic AI, purpose-built on MLA's own knowledge base, can bridge that gap.

Objectives

To develop and deploy a modular platform in a testing environment that hosts multiple AI use cases. These use cases will eventually be accessed through the myMLA portal and the MLA website.

This platform must be able to handle large scale data whilst meeting MLA’s security and privacy standards. High volume data processing and inference must be supported with minimal latency.

Implementation of the platform including theming of the Caitlyn platform, embedding the platform into the MLA website (using dropcode), ingestion of the data housed on the MLA website, the tuning of the AI agents’ voice, guardrails etc. 
It should also deliver a recommendation on commercial model to MLA for consideration for future investment.

Key findings

To develop and deploy a modular platform in a testing environment that hosts multiple AI use cases. These use cases will eventually be accessed through the myMLA portal and the MLA website.

This platform must be able to handle large scale data whilst meeting MLA’s security and privacy standards. High volume data processing and inference must be supported with minimal latency.

Implementation of the platform including theming of the Caitlyn platform, embedding the platform into the MLA website (using dropcode), ingestion of the data housed on the MLA website, the tuning of the AI agents’ voice, guardrails etc. 
It should also deliver a recommendation on commercial model to MLA for consideration for future investment.

Benefits to industry

The results of this POC demonstrate that agentic AI, purpose-built on a large and complex knowledge base, is technically viable, operationally stable, and capable of generating genuine engagement from both producers and internal staff. For an organisation like MLA, which sits at the centre of Australia's red meat and livestock industry and stewards one of its most comprehensive R&D libraries, that is a meaningful proof point.

MLA action

MLA will share updates on social media and via other newsletter channels when the AI agent is live on the website for public use.

Future research

MLA will continue to develop this AI model in partnership with Custom D so it can be made publicly available on the website. MLA is well positioned to be a leader in this space within the Australian agricultural sector, and this POC provides the evidence base to move forward with confidence.