How to integrate Receipt Parsing into your Application using Make?

In this step-by-step tutorial, we'll show you how to build and connect a receipt parser workflow in Make to your app or software. If you're looking to integrate other features into your app, we suggest reading Make's article on 5 ready-to-use AI solutions to build and optimize AI projects.

‍

Build AI on Make with Eden AI

Eden AI was created for no-coders having difficulties with choosing the right AI provider and/or integrating several APIs. Managing multiple accounts for each app can be a tough job, but with Eden AI, you can connect and manage all your APIs on a single account. Since some AI providers can be complex to use, we wanted to simplify the “no code” part and make AI available to as many people as possible. 

‍

Eden AI allows you to solve multiple AI tasks on Make:

• Document parsing : extracting text from images and parsing invoice, receipt or resume to extract data

• Computer vision: detect faces, objects, logos, explicit content, etc.

• Text analysis : sentiment analysis, keyword extraction, summarization, etc.

• Machine Translation

• Speech recognition & Speech generation

‍

Let's practice with Receipt Parsing!

Receipt Parsing or OCR Receipt is a type of Optical Character Recognition (OCR) API that specifically focuses on recognizing and extracting text from receipts. This type of API uses advanced Image Processing and Machine Learning algorithms to extract relevant information from receipts, such as the date, merchant name, total amount, and items purchased.

‍

‍

‍

The extracted information can be returned in a structured format, such as JSON or XML, for further processing and analysis. Receipt Parsing can be used in various applications such as expense management, bookkeeping and accounting. It can also be integrated into mobile apps to automate the process of receipt scanning and tracking expenses.

‍

‍

How to bring receipt parsing to your app using Make?

If you're looking for an easier and faster way to implement receipt parsing to your app, skip the tutorial and watch the video below:

‍

1. Connect your receipt storage

First, you’ll need to connect the source where your receipts are stored. It can be directly from emails you receive (Gmail, outlook, etc.) or it can be from cloud storage (AWS S3, Google Drive, etc.) or any other personal sources.

Let’s take Gmail for instance: you'll need to connect your Gmail account on the Watch Email module. Next, select the folder you want to be watched. Then, set up your criterias which can be:

• read or unread emails (or both)
• email addresses you want to watch
• subject of the email
• email content

‍

2. Connect your receipt parser API key 🔑

Once you're sure that you will fetch all the receipts you may receive, you can connect the Eden AI Receipt Parser module to process your receipts :

‍

‍

Then, you can connect your Eden AI account by simply entering your API key which you will have found on the Eden AI platform beforehand:

‍

‍

‍

3. Set up your receipt module

Once the connection is set, the configuration of the Eden AI Receipt module is very easy. First, you will need to plug the file from Gmail module, then choose the receipt engine you want to use along with the language of your receipts:

‍

‍

As you can see, the Eden AI module allows you to choose the best receipt providers by checking their prices and live testing their performances directly on Eden AI platform. As soon as the Eden AI receipt module is set up, you will be able to process your receipts.

‍

For each receipt parsed in the module, different fields will be extracted such as: receipt number, taxes, amounts, dates, customer and merchant information, line items, etc.

‍

‍

4. Store the extracted data

The structure of the answer is always the same, regardless of the supplier you choose or the receipt you analyse. That way, your scenario remains functional and you can take the information wherever you want (your ERP, Airtable, Google sheet, etc.).

Let's say you want to keep the results stored in a Google Sheet:

‍

You can use the "Google Sheet Add a row" module, and configure it as follows.

‍

Then, you can automatically add the extracted data in your spreadsheet:

Congrats 🥳 You're all set and ready to automate your receipt processing with Make!

‍

If you're interesting in more low-code tools, have a look at our step-by-step tutorials on how to bring AI to your application with Power Apps, Google App Script, Retool, IFTTT, and n8n.

‍

‍