Melbourne Business Automation
Automation Use Cases
Case Study 1 — AI Invoice Intake Pipeline
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The problem: Every supplier invoice, bill, and receipt arrived by email and required manual review, approval, data entry, and filing. Time-consuming, error-prone, and easy to lose track of.
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What was built: Forward any invoice to a dedicated mailbox and the system handles everything. The document is extracted using Azure Document Intelligence, the content is classified using Azure OpenAI against a project and expense mapping table, routed for approval if required, and written to the financial record automatically. Filed in SharePoint with full audit trail.
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The outcome: One action - forward the email. The system does the rest. No manual data entry, no chasing approvals, no misfiled documents.
Case Study 2 — Teams-to-Quote Automation
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The problem: Quoting required switching between systems, manually entering client details, building pricing from scratch, formatting a document, and sending it — every time, for every quote.
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What was built: Type a quote request into Microsoft Teams in plain language. AI extracts the client and service details, checks whether the client already exists, creates the quote, builds the pricing using AI against a live services and pricing database, generates a formatted Word quote document, saves it to SharePoint, and sends it to the client.
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The outcome: One message in Teams produces a complete, formatted, accurately priced quote ready to send. The entire process that previously took 20-40 minutes happens automatically.