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AI Data Extraction

AI-Enhanced Feature

Invoice data extraction is powered by Brikly's AI engine. The system continuously improves as it processes more invoices from your suppliers.

When you upload an invoice, Brikly's AI reads the entire document and converts it into structured, editable data. This replaces the manual process of keying in supplier details, line items, and totals by hand.

What the AI extracts

The extraction engine identifies and pulls out the following fields:

Header information

  • Supplier name - the company that issued the invoice.
  • Invoice number - the supplier's reference number.
  • Invoice date - the date printed on the invoice.
  • Delivery date - if different from the invoice date.
  • Invoice total - the grand total including VAT.

Line items

For each product listed on the invoice, the AI extracts:

  • Description - the product name as printed by the supplier.
  • Quantity - number of units ordered.
  • Unit of measure - e.g. kg, litres, cases, each.
  • Unit price - price per unit.
  • Line total - quantity multiplied by unit price.
  • VAT rate - the VAT percentage applied to that item.

Totals and VAT

  • Subtotal (net amount before VAT).
  • VAT breakdown by rate (e.g. 0%, 5%, 20%).
  • Grand total (including VAT).

Confidence scoring

Every extracted field is assigned a confidence score that tells you how certain the AI is about its reading:

ConfidenceIndicatorWhat it means
HighGreenThe AI is very confident. Typically no action needed.
MediumAmberThe AI's best guess - worth a quick check.
LowRedThe AI struggled with this field. Manual review recommended.
tip

Fields with high confidence are usually correct, but it is good practice to glance over the extracted data before confirming - especially for the first few invoices from a new supplier.

Reviewing extracted data

After extraction, you are presented with a review screen showing all the data the AI found. From here you can:

  • Edit any field - click on a value to correct it.
  • Confirm the invoice - accept the extracted data and move to the matching stage.
  • Reject the invoice - discard the extraction and start again if the results are unusable.

Fields that need attention are highlighted with their confidence colour so you can focus your review time where it matters most.

Handling extraction errors

Occasionally the AI may misread a value or miss a line item entirely. Common causes include:

  • Poor image quality - blurry or low-resolution photos.
  • Unusual invoice layouts - heavily designed or non-standard formats.
  • Handwritten annotations - the AI focuses on printed text and may skip handwritten notes.

If extraction results are poor:

  1. Check whether a higher-quality version of the invoice is available (e.g. the original PDF instead of a photo).
  2. Re-upload the better version.
  3. If the same layout consistently causes issues, contact support - the team can investigate and improve handling for that supplier's format.
caution

If you correct an extracted value, make sure to update the related fields as well. For example, if you change a line item's unit price, verify that the line total and invoice total still add up.

Next step: reviewing line items

After extraction, some line items may be missing fields that the AI could not read (e.g. pack size or unit of measure). See Reviewing Line Items for how to quickly fill in missing data before matching.

How corrections improve the system

Every correction you make feeds back into Brikly's learning engine. Over time, the AI becomes more accurate for the suppliers and formats you work with regularly. See The Learning System for more on how this works.