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You can automate document processing in your flows using AI Builder's document processing model.
For detailed instructions and examples, check out the full documentation: https://learn.microsoft.com/en-us/ai-builder/form-processing-model-in-flow
Just wanted to check in and see if everything is working now. If you still need any help, feel free to let me know.
Also, if the issue is resolved, it would be great if you could mark the answer as solved so others with the same question can find it easily.
Thanks and have a great day!
You will need to use the “Recognize text in image or document” action for OCR. However, when I tested this using your sample file, the extracted text included output such as “täglich im Umgang in d. Gemeinschaftsbräumen”, which indicates that the results may not be fully accurate.
As with most OCR solutions, the quality of the extracted text is highly dependent on the quality of the input document. Factors such as scan resolution, image clarity, contrast, and language can significantly impact the accuracy of the output.
Hi @CFernandes @Valantis ,
I am currently using a similar approach to address the invoice processing requirements. However, I am facing challenges with extraction accuracy, which is currently around 55% for the overall process in production.
The primary challenge is that we receive multiple types of documents and a large variety of invoice formats (approximately 100+ different formats). Due to these layout variations, OCR extraction quality and field mapping consistency are significantly impacted.
I would appreciate your suggestions or recommendations regarding:
Improving extraction accuracy in “Get text from document” or any similiar approach
Best practices for handling multiple document formats
Any available documentation, benchmarks, or references related to AI Builder OCR accuracy
Recommended approaches for scalable invoice-to-JSON extraction
Any guidance or production learnings would be very helpful.
Thanks in advance.
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