VAT invoice

Overview

This guide covers how to extract metadata and vat rates from supplier invoices with examples in Python, Node, Java, and C#.

You will extract the following metadata fields:

• Name of the supplier
• Name of the receiver
• Invoice number
• Purchase order number
• Issue date
• Pay due date
• Total amount
• Net amount

You will extract the following vat rate fields:

• Vat rate percentage
• Vat rate net

This guide shows you how to

1. Create vat-invoice document type
2. Add a supplier to your dataset
3. Execute training
4. Extract data from documents
5. Continuously improve models after extraction

Getting your API Key

The Authorization header for your API key is: <<apiKey>> (Login if you do not see one).
You can also obtain the API key by visiting the Settings page.

1. Create a new document type

Before you start extracting data, you need to define a document type.
Navigate to the Dashboard page and click on the New document type button in the top right corner of the table. Next, select the Vat invoice card. The wizard will already pre-fill all the needed extraction fields along with the document type configuration.
Click on the Create document type.

This will create a new document type with name vat-invoice with the following fields:

• supplier_name
• invoice_number
• purchase_order_number
• receiver_name
• issue_date
• pay_due_date
• total_amount
• net_amount

The document type will have a VAT rate plugin already set-up for your fields.

2. Add suppliers

typless is a tool for automation. That's why you need to fill the data set and train it first. To automate a new supplier you need to first add its invoices to the data set.
Download an example invoice from Best Flowers Inc. - Best Flowers Inc. - download

To add document to the dataset use the add-document endpoint or use training room where you can easily upload a file and fill out necessary infromation.

Dataset is created by uploading an original file with the correct value for each field defined inside the document type.
A thing to note with VAT invoices is that you also have to fill out all the vat rates that are present on the document so the engine will also take these into account the next time it does extraction.

As you can see, to achieve high accuracy typless only needs the values that are on the document. Nevertheless, there are some rules to keep in mind when providing values.

Applying these rules to the provided example you will change some fields:

• total_amount value was converted with number type rules from 735,33 to 735.3300
• net_amount value was converted with number type rules from 644,14 to 644.1400
• issue_date value was converted with date type rules from 16.06.2017 to 2017-06-16
• pay_due_date value was converted with date type rules from the word 30.06.2017 to 2017-06-30

You also applied the same rules to the VAT rates on the document.
VAT rates are structured as a list of lists similarly to line items, so keep that in mind when building the data structure for training.

Need some more information on the VAT rate plugin? Learn more about how it works and what are the limits here.

You will have one supplier added to your document type after you run the code example.

3. Execute training

👍

Training is executed automatically every day at 10 PM CET

For all of your suppliers with new documents in the dataset of all your document types.
Free of charge

To immediately see the results you can trigger the training process on the Dashboard page.
Look for the vat-invoice document type in the list, and click on the .

Need more information about training? Read more about it here.

4. Extract data from documents

After the training is finished, you can start precisely extracting data from documents from trained suppliers. Download a new example from Best flowers Inc:

• Best Flowers Inc. 2 - download

Download it and extract the data using the recipe:

You should successfully extract fields along with all the VAT rates present on the invoice.

Need more in depth explanation of the response?
You can read about it here.

5. Continuously improve models

typless embraces the fact that the world is changing all the time.
That's why you can improve models on the fly by providing correct data after extraction.
Let's say your company has a new partner Best supplier. You don't need to start over with building the dataset. You can simply extract and send the correct data after they are verified by your users.
You can learn more about providing feedback on the building a dataset page.

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Closed workflow loop - improve models live!

Use every action from your users to adapt and improve typless models without any extra costs.

To send feedback use the add-document-feedback with object_id.

Running typless live

The only thing that you need to do to automate your manual data entry is to integrate those simple API calls into your system.

Have any questions or you need some help? Contact us in chat.