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Azure AI Document Intelligence vs. Parashift

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure AI Document Intelligence
Score 8.7 out of 10
N/A
Azure AI Document Intelligence (formerly Form Recognizer) learns the structure of forms to intelligently extract text and data. It ingests text from forms, applies machine learning technology to identify keys and tables, and then outputs structured data that includes the relationships within the original file. That way, the user can extract information tailored to specific content, without heavy manual intervention or extensive data science expertise.N/A
Parashift
Score 0.0 out of 10
N/A
Companies - from SMEs to large corporations - can use Parashift to configure, classify and extract their business documents. The platform comes with document types from different industries that can be consumed directly without configuration or training. According to this principle, the Procure to Pay solution offers ten ready-to-use APIs. 30+ more are in preparation. To complement these, new, individual document types can be set up within minutes.N/A
Pricing
Azure AI Document IntelligenceParashift
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure AI Document IntelligenceParashift
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
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Azure AI Document IntelligenceParashift
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User Testimonials
Azure AI Document IntelligenceParashift
Likelihood to Recommend
Microsoft
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.
KR
Kharan Raju
Data Scientist
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Parashift AG
No answers on this topic
Pros
Microsoft
  • 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
KR
Kharan Raju
Data Scientist
Read full review
Parashift AG
No answers on this topic
Cons
Microsoft
  • 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
KR
Kharan Raju
Data Scientist
Read full review
Parashift AG
No answers on this topic
Usability
Microsoft
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.
KR
Kharan Raju
Data Scientist
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Parashift AG
No answers on this topic
Alternatives Considered
Microsoft
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.
KR
Kharan Raju
Data Scientist
Read full review
Parashift AG
No answers on this topic
Return on Investment
Microsoft
  • Significant reduction in manual processing cost by 40-60%
  • Improved data accuracy and reduce work
  • Scalability is good without cost increase
KR
Kharan Raju
Data Scientist
Read full review
Parashift AG
No answers on this topic
ScreenShots