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Six cases showing how agents, orchestration and an AI operating system can take on the repetitive work in the industries leading AI adoption.

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Illustrative cases modelled on the industries investing most in AI: mining, financial services, retail, logistics, agri-export and telecommunications. Targets are set during discovery and are not guarantees.

Mining

Maintenance copilot for field technicians

An iron ore mining operator in Western Australia

Challenge

Technicians lose time searching manuals, work orders and parts catalogues across several systems, often on sites with weak connectivity.

Solution

A set of orchestrated agents for manuals, work orders and parts answers technician questions in their own language, by text and voice, drafts work-order notes and surfaces safety procedures. It runs on-premise and tolerates losing the connection.

−30–40%
target reduction in time to find the right procedure
Same shift
work-order notes drafted before the technician leaves the site
On-premise
sensitive data stays inside the site network
Banking & fintech

Voice and chat agent for collections and enquiries

A mid-size consumer lender in Australia

Challenge

Routine balance, due-date and payment-plan enquiries dominate call volume, under strict compliance and call-recording rules.

Solution

A voice and chat agent with approved compliance wording, identity verification, payment-plan offers within set limits and escalation with the full transcript. A policy gate and an audit log record every action.

−25–35%
target reduction in average handling time for routine calls
24/7
routine enquiries answered outside office hours
Full trail
every action logged with identity and reason
Retail & e-commerce

WhatsApp order support and returns

The e-commerce operation of an Australian department-store group

Challenge

Around sales events, order-status and returns requests flood support, and customers wait for simple answers.

Solution

A WhatsApp agent connected to the order system and carriers that handles status, address changes and return labels within policy, and passes exceptions to a person. Cost per resolution is reported every week.

40–60%
target share of order-status contacts resolved without a person
Event-ready
designed for peak days, with queues that scale
Weekly
cost per resolution tracked and reviewed
Logistics & ports

Exception orchestrator for international shipments

A freight forwarder operating between Australia and Asia

Challenge

Delays, customs documents and carrier updates are handled across email and spreadsheets, so problems surface late.

Solution

A supervisor coordinating a tracking agent, a documents agent and a customer-update agent. Re-booking costs above a set limit wait for a person to approve.

−30%
target reduction in time to detect and communicate a delay
One view
of every open exception across carriers and documents
Approval gate
for spend above a defined limit
Agri-export

Export paperwork automation

A fruit and produce exporter in Victoria

Challenge

Each shipment needs packing lists, phytosanitary and customs documents from several sources, with hard deadlines in season.

Solution

Document intake, extraction and validation against destination rules, an exception queue for people, and status updates to customers. The team is trained to run and adjust it.

−50%
target reduction in manual data entry
Fewer rejects
documents validated before they are submitted
Season-ready
team trained to operate the workflow
Telecommunications

A governed AI layer for customer operations

A regional Australian telecom operator

Challenge

Support, sales and retention each started separate pilots with different vendors, and there is no shared security, cost or measurement.

Solution

An AI operating system with shared identity, a tool registry for billing and CRM, model routing and cost-per-outcome dashboards, with three agents onboarded on the same layer.

3 agents
target launched on one governed layer
Per team
cost per outcome visible to finance and operations
Model freedom
providers can change without rewriting agents
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