Power Automate Invoice Processing Tutorial AI Builder and Azure
ฝัง
- เผยแพร่เมื่อ 2 ส.ค. 2024
- Welcome to today's tutorial where we'll delve into the intricacies of processing invoices within the Power Platform. In this demonstration, we'll explore two approaches: the low-code AI Builder method and the Document Intelligence Service on Azure.
Processing invoices is crucial for many businesses, and understanding these methods can streamline operations and enhance efficiency. Whether you're a seasoned developer or just starting out, this tutorial has something for everyone.
We'll begin by exploring the AI Builder approach, you'll learn how to use AI builder in Power Automate, where we can easily leverage pre-built models to extract vital information from invoices. With just a few clicks, we'll see how AI can identify key data points such as customer details, invoice dates, and itemized lists.
Next, we'll dive into the Document Intelligence Service on Azure, offering a more customizable and cost-effective solution. While slightly more complex to set up, this service provides greater control and flexibility in processing invoices. We'll discuss pricing tiers, integration options, and delve into the technical details of building a flow within Power Automate.
Throughout the tutorial, I'll provide step-by-step guidance, including demonstrations of building flows, analyzing JSON responses, and handling complex data structures. Whether you're interested in AI-powered automation or backend development, this tutorial will equip you with valuable insights and practical skills.
Timestamps:
00:00 Introduction
00:42 Exploring the AI Builder Approach
03:02 Understanding AI Builder Cost
04:52 Testing the AI Builder Flow
06:02 Understanding the Document Intelligence Service on Azure
07:08 Pricing and Integration Options for Azure
08:47 Exploring the Studio
11:00 Building Flow integration with Azure
14:59 How to poll Synchronous Service
18:28 Review the flow history
19:17 Analyzing JSON Responses
21:27 Selecting data from the JSON response
24:42 Create an Invoice from Canvas App
25:52 Testing the Flow
By the end of this tutorial, you'll have a comprehensive understanding of how to process invoices using the Power Platform, empowering you to streamline operations and unlock new possibilities for automation.
Want to generate Invoices from a Canvas App? • Create Word, Excel, HT...
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#PowerAutomate #PowerPlatform #Tutorial #invoice #ocr - วิทยาศาสตร์และเทคโนโลยี
Great demo. Love that pricing comparison for AI builder vs. Azure PAYG services. As always with bigger power comes more responsibility/JSON.
I love a bit of JSON though 🤣 500 free credits a month though - worth it?
Thanks for sharing this method. Useful and cost effective.
Absolutely brilliant! I've been discussing this with colleagues about how the rate is much better and how you can use COE to find the big jobs running and put doc intelligence in place there. Love the precision of delivery.
Very much appreciate your comment - makes this worthwhile, thanks.
great video as always, nicely technically explained. cheers!
Thank you! Cheers!
Great 😃
Thanks for Sharing! Do you have tutorial on Azure Vault?
Not yet… 🤔
Nice Video
It was a sunny weekend and I had lots of gardening 😎 but managed to get this recorded and edited late last night. Very much enjoyed exploring and sharing this one.
Hello Damien,
Very nice video thanks for sharing. I have a question how's your experience with hand written documents or invoices. Earlier this year I was working on project using AI Builder and Flow to process hand written documents, I found AI Builder unable to process hand written documents 100% accurately.
Ex: if in document text is Bagel, AI Builder is predicting text as 'Bogel'.
Ex: if in document text is deport, AI Builder is predicting text as 'depont'.
And AI Builder is not providing any option to modify this prediction text.
Let me know if came across such scenario and how you overcame such issue.
Thanks.
Interesting. What was the confidence score? I’m not sure what your options are but keen to hear if you find a solution.
Great video, thanks for sharing. I just have one question : Is there a reason why you use Power Automate instead of Logic Apps ? Is it because of cost issues ?
I primarily focus on Power Automate but 💯 a lot of my videos, including efficiency can be replicated on Logic Apps.
Hi, thanks for the great video! We are looking to improve our invoice processing using Azure AI Document Intelligence. Do you know if it is possible to build a Power Automate flow that lets u manually check the output data of the AI model and either approve or change some wrong values before the data gets exported into our internal processes? I am looking for such a soolution, but I am unable to find it as of yet.
Thanks! :)
To elaborate a little on that, ideally we would want to set a threshold. For example, if confidence is 0.9 or higher we want to automatically accept the output. But if its lower, we want to manually check and maybe change the output.
Yes, this would be achievable, the output contains the confidence score and so you could factor that into either an app or an automation. For example, if a score is below 0.9 you could send an email or adaptive card, request a human in the loop verifies / updates and then save the changes. I don't have a demo yet though. Interesting use case.
Thanks for the quick reply. Do you have any recommendations on which tooling to use for such an automation? I can imagine power automate might be a suitable tool. And if you ever make a demo about this, I will be sure to check it out :)!
Power Automate could certainly support this 👍 I’ll add it to me list but can’t make any promises
You could run both methods, in parallel, writing to two Dataverse tables recording the associated Confidence scores in those Dataverse tables. Then, later, run a Flow that compares those two Dataverse tables generating a 3rd one with the data that exceeds a value of 90% for the Confidence Score.