ABBYY FlexiCapture vs. Azure AI Document Intelligence

It is well suited for unstructured documents and automates the scanning operations where users are scanning thousands of documents on a daily basis and process them in the existing line of business application, or it is well suited for the RPA operations where ABBYY FlexiCapture extracts the output of extracted data in Excel, CSV or XML, and RPA applications parse those data and take it into other applications.

Incentivized

Azure AI Document Intelligence is mainly used in document data filling. If the template is the same, only the inside data content will be different. There, we use a text-based OCR process to fill the data in the same template with different, accurate data means the manual work will be reduced and time saved. And used in an image and text combined bot if the user query through text from the knowledge based document it brings the output which is used in information technology and services.

Incentivized

• Integration with workflow tolls
• Auto data extraction
• Business rule setup

Incentivized

• From the Image the OCR technology use to store embedding properly
• From the images the OCR technology automatically capturing text is brilliant
• Also for creating Azure AI Document Intelligence endpoint and keys it is very easy to do

Incentivized

• Although the back-end of the application is very strong, if it can have a visual workflow for defining tasks like scanning, verification and etc., it will be better.
• Reporting feature should be enhance more on web
• Although the result of Arabic Text extraction is very good in ABBYY, if they can focus more on different types of Arabic Fonts, it will be better

Incentivized

• Azure AI Document Intelligence should have used to store image based embedding for multiple languages
• Images storing part is a different area in our case and only for a few images that part can be increased
• Cost is high which should be reduced so more users will come and more technology through this will come

Incentivized

Azure AI Document Intelligence mainly meets our business requirements. Actually, what we need is image and text-based multimodal, and we store data in pgvector PostgreSQL vector embedding those data. For that, we need text and image combined embedding, which we can get from Azure AI Document Intelligence. Which is working good for us and improved accuracy not 100% but 70% accuracy we are getting at least through Azure AI Document Intelligence.

Incentivized

License is cheap w.r.t to IQ BOT More flexibility in terms of custom development Can be used as independent process

Incentivized

Azure AI Search, we used to bring image and text relevant to the user query, but it did not work properly, and the accuracy was very poor compared to Azure AI Document Intelligence. Azure Blob Storage we used to store images and bring in frontend there also accuracy low, so we went for embedding through Azure AI Document Intelligence. Azure AI Content Safety for text content, but it is very costly, so we went for Azure AI Document Intelligence.

Incentivized

• It has eased the scanning operation and reduced the overall time
• Automatic indexing created the good impacted on ROI
• But it only required the specialized IT Admin to maintain the system

Incentivized

• Significant reduction in manual processing cost by 40-60%
• Improved data accuracy and reduce work
• Scalability is good without cost increase

Incentivized