Azure AI Document Intelligence Backbone for Multimodal building
January 27, 2026

Azure AI Document Intelligence Backbone for Multimodal building

Kharan Raju | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Azure AI Document Intelligence

We use Azure AI Document Intelligence mainly for Multimodal Gen AI building process, we use pdf document to take images embedding and text embedding for text to text and image based output generation model using OCR process. This is our main use case for our customer. Text embedding will be around the image. We easily take text embedding also image embedding also taken but text image embedding only can be taken through Azure AI Document Intelligence Optical Character Recognition and we do that using its api endpoint and key we take from Azure portal. Then we use that in our Python code, integrate, and get text image embedding. Text around image and text in image embedding helps to give accurate answers for the user based queries.

Pros

  • 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

Cons

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

Do you think Azure AI Document Intelligence delivers good value for the price?

Yes

Are you happy with Azure AI Document Intelligence's feature set?

Yes

Did Azure AI Document Intelligence live up to sales and marketing promises?

Yes

Did implementation of Azure AI Document Intelligence go as expected?

Yes

Would you buy Azure AI Document Intelligence again?

Yes

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.

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