Distribution
A couple of hundred invoices on a working day
The problem Orders leave on routes before anyone checks whether the buyer’s NTN is still active. A rejection surfaces days later, by which time the goods are gone and the invoice is wrong.
How it runs Billing staff fill one Excel template rather than re-keying each invoice into a portal. Every row is checked before anything reaches FBR, so a bad buyer NTN is caught at the desk. Each invoice still goes to FBR individually as FBR requires — failed rows are corrected and retried on their own, and the rest of the run posts regardless.
Manufacturing
Invoices that already exist in an ERP
The problem SAP or Dynamics is already the system of record. Nobody wants a second place to type invoices, and rebuilding FBR rules inside the ERP means re-doing it every time the technical specification changes.
How it runs The ERP keeps commercial truth and posts invoice data through the API. Validation, submission and the official FBR number and QR are handled outside the ERP, so an FBR change lands in one place instead of becoming a transport and regression cycle.
CA & tax firms
One firm, many client registrations
The problem Each client is a separate registration with its own FBR credentials and its own month-end. Sharing logins across clients is a professional risk; doing each one manually does not scale past a handful.
How it runs One account holds credentials for many seller NTNs, kept separate per client, and a single submission run can carry invoices belonging to different sellers. The same workflow repeats per client instead of being reinvented each time.
What volume actually looks like here
Businesses running bulk on eInvoicePro submit around 2,600 invoices a month on average — roughly 120 on a
working day — and the highest monthly volume on the platform is about 5,000. Across all customers, 1M+ invoices have been submitted to FBR through the
platform, of which 98% pass FBR validation. If your
numbers are larger, say so on a demo and we will talk through how the run would be shaped.
The patterns above describe typical workflows rather than named customer results. Volume
figures are platform averages, not a single customer’s.
