I’ve been deep on this planet of OpenAI for some time — engineering prompts, experimenting with GPT, and rising extra educated of AI ‘s capabilities. In my journey to deepen my experience in Azure AI and cloud applied sciences, I lately explored Azure AI Doc Intelligence — a robust instrument designed to extract structured information from varieties and paperwork. This hands-on lab offered helpful insights into AI-powered doc processing and its potential to streamline enterprise workflows.
On this article, I’ll stroll you thru how I arrange Azure AI Doc Intelligence, analyzed doc information, and what I realized from this expertise. I utilized quite a few receipts however selected to maintain it easy for the sake of this content material.
Consider Doc Intelligence like a supercharged OCR (Optical Character Recognition) instrument.
OCR merely put reads textual content from pictures.
Doc Intelligence understands the construction of the textual content.
Instance: names, dates, and costs in a receipt.
That is helpful for companies that course of a ton of paperwork — as a substitute of manually getting into information, they will automate it utilizing AI.
To get began, I needed to create an Azure AI Doc Intelligence useful resource:
- Logged into the Azure Portal
- Created a brand new useful resource (named it AiDocFun)
- Set pricing tier to Free F0 (so no prices apply)
- Waited for deployment
After organising the AI, I uploaded a pattern receipt into Doc Intelligence Studio. The AI scanned it and extracted necessary particulars:
✅ Retailer Identify: Northwind Merchants
✅ Cellphone Quantity: 555–123–4567
✅ Date & Time: 2/17/2020–13:07
✅ Objects Bought:
- Apple — $0.90
- Orange — $0.80
Then, I hit Run Evaluation, and inside seconds, the AI pulled out all of the structured information from the picture:
The AI didn’t simply learn the receipt — it really broke down the info into structured fields like:
- Service provider Identify (Retailer identify)
- Transaction Particulars (Date, Time, Complete)
- Itemized Purchases (Names, Costs, Taxes)
It additionally gave confidence scores, displaying how positive the AI was about every worth. If the rating was excessive (98–99%), it meant the AI was fairly assured it obtained the best data.
