Cleaner invoice intake
Invoices arrive with extracted fields, source files, and missing details already flagged.
Rebotify builds an AI employee that reads invoices, checks required details, prepares approval packets, and routes exceptions before finance has to chase every thread.
Mia is our AI employee. Email her — she’ll book your 15-minute call. That’s the demo.
The business outcome is fewer month-end surprises, cleaner approval packets, and faster exception handling.
Invoices arrive with extracted fields, source files, and missing details already flagged.
Approvers receive the supplier context, amount, due date, and specific decision needed.
Duplicates, mismatches, changed details, and missing references surface before payment review.
THE ROLE
Invoice processing automation should start with intake and exception prep: read the invoice, match known vendor details, check missing fields, attach source context, and send a clean approval request.
01
The employee reads invoices from email or folders and extracts the fields the finance team actually checks.
02
Supplier, ABN or tax ID, due date, amount, purchase order, bank details, and missing attachments can be checked before review.
03
Approvers receive a clear summary, source file, prior context, and the specific decision needed.
04
Unclear, duplicate, or policy-sensitive invoices go to the right reviewer instead of sitting in a general inbox.
Finance has to check emails, PDFs, supplier portals, drive folders, and chat threads before the real work starts.
The same missing details keep delaying payment decisions and creating back-and-forth.
Simple invoices are easy; mismatched suppliers, unclear purchase orders, and unusual terms need judgment.
The first workflow prepares and checks the work; payment actions can remain gated behind existing finance controls.
The employee can surface suspicious repeats, changed bank details, and conflicting invoice information for review.
Each prepared item includes the source document and the checks applied so finance can verify quickly.
Read new supplier invoices, extract fields, identify missing details, and prepare the approval request.
Compare invoice details against a PO or project record and flag mismatches before approval.
Summarize stale invoices, missing approvals, and exceptions that need action before close.
The employee works in the systems your team already uses — no new dashboard to log into.
Invoice automation needs structured data, exception handling, and finance controls before payment is touched.
Claim boundary
We do not claim fully touchless payment, universal fast payment, ATO visibility into invoice contents, or guaranteed savings.
Reference point
The ATO describes lower processing cost for eInvoices and notes internal checks still apply before payment.
Reference point
ATO guidance describes Peppol eInvoicing as direct structured data exchange between buyer and supplier software.
Reference point
OpenPeppol documents the interoperability framework and invoice specifications that support automated processing.
Invoice processing automation should start with intake and exception prep: read the invoice, match known vendor details, check missing fields, attach source context, and send a clean approval request.
Invoice processing automation is best for finance and operations teams with a repeated workflow, a clear human owner, and enough examples to teach the AI employee what good work looks like.
Rebotify maps the workflow, writes the first operating playbook, connects the minimum tools, and puts useful drafts, checks, or summaries into a human approval queue.
Yes. Rebotify normally starts with human approval for customer-facing, financial, legal, or policy-sensitive actions. The AI employee prepares the work and escalates uncertainty.
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Mia is our AI employee. Email her — she’ll book your 15-minute call. That’s the demo.