Nanonets is an AI-based workflow automation software centred around our revolutionary OCR engine. We have many pre-trained models to extract data from standard customer documents, Purchase Orders being one of them.
We can help extract structured information from Purchase Orders in the form of flat fields or key-value pairs, such as Purchase Order Number, Vendor Name, Buyer Name, Total Amount, etc. as well as tabular fields such as Product Code, Line Item Description, Quantity etc. for the table containing order details.
Alternatively, in case you would want a different set of fields to be extracted, you can use our zero-training OCR model which can be set up to extract custom fields within minutes. Here is more information on how you can use the Zero-Training Model.
The list of tabular fields that we support out-of-the box are as follows:
| Tabular Fields | Description |
|---|---|
| product_code | This is a product Identifier, like, SKU Code, Product Number, etc. |
| description | This details the item briefly |
| line_amount | This is the price unit of the product |
| quantity | The number of units of the product purchased |
| price | The total price per line item = Line Amount * Quantity |
The list of flat fields that we support out-of-the box are as follows:
| Field | Description |
|---|---|
| buyer_name | Extracts the name of the buyer from the Purchase Order. |
| total_amount | Extracts the total amount due to the seller/vendor on the Purchase Order. |
| shipto_name | Extracts the name of the buyer |
| total_amount | Extracts the total amount due to the seller/vendor for the transaction |
| net_d | Extracts the total number of days after which the payment will be made to the seller |
| net_amount | |
| buyer_phone | Extracts the contact number of the buyer |
| delivery_date | Extracts the date of delivery of the purchased goods |
| vendor_id | Denotes an identifier associated with the seller/vendor. Useful when 2-way matching against invoices for organisations with multiple vendors. |
| vendor_vat_number | Extracts the VAT number for the seller/vendor |
| vendor_name | Extracts the name of the seller/vendor |
| currency | Extracts the currency which the Purchase Order is in |
| po_date | Extracts the date on which the Purchase Order was issued on |
| total_tax | Extracts the total tax levied on the purchase of goods |
| shipto_address | Extracts the address to which the goods will be shipped |
| buyer_vat_number | Extracts the VAT number for the buyer in case buyer is a business or an organisation |
| po_number | Unique Identifier for the particular Purchase Order. Useful when 2-way matching against invoices for organisations with multiple purchase orders and corresponding invoices. |
| buyer_address | Extracts the address of the buyer from the Purchase Order |
| vendor_address | Extracts the address of the seller/vendor from the Purchase Order |
| total_tax_% | Extracts the percentage of total tax levied |
| subtotal | Extracts the total of the line items before taking into account taxes, discounts, etc. |
| buyer_email | Extracts the email address of the buyer |
| vendor_email | Extracts the email address of the seller/vendor |
You can always add more fields if you need or refine/retrain the model for better extraction accuracy on your own Purchase Orders. We also keep adding more and more fields every month based on customer requests.