Azure AI Document Intelligence vs. IBM Datacap

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

Once highly customized, IBM Datacap can suit any business unit and scenario. To realize accurate knowledge and insight base on business documents, I would emphasize use of IBM Datacap since it has robust OCR tool that ease document capturing.

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

• Machine learning automates document processing from external applications and sources like scanners.
• Exporting data with just a click to other content repositories.
• Redaction of data based on requester role. Therefore, we are able to block irrelevant or sensitive information based on the specification of users.

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

• Supporting documentation is poor
• UI is old fashioned

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

Generally they are very good and reactive to our requests. if we find an issue our error they are quick to add a fix to the next release if needs be.

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's easier to extract data from documents for analytics, unlike other similar platforms.

Incentivized

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

Incentivized

• We have protected and safeguarded business information by redacting documents to ensure that confidential data doesn’t reach to irrelevant business users or cyber attackers.
• Business procedures automation has been enhanced by IBM Datacap as part of the Cloud pak, which eases workflow and decision management.
• Being based on modern modular, IBM Datacap allows us to pay for what we use, thus no losses are encountered.

Incentivized