Vision AI

Coforge Document AI is an accelerator software solution for document content processing and analyzing. It helps in standardizing and structuring large amounts of text data, quickly extracting and converting multiple data formats to a single template determined by you. Advanced text-based software features like Clustering, Topic extraction, Sentiments, Financial, Legal and Contract file handling add value and make data more informative and insightful. All this is underpinned by an intuitive user interface that makes Document AI quick and simple to use. The solution is open source-based with capabilities to add off-the-shelf propriety components. Some examples below: 

• LIBOR Remediation: LIBOR remediation for banks and financial services organizations that are mandated to move to another benchmark rate by 2021. Document AI automatically extract information for LIBOR related documents (any format), creating structured searchable records. These are then used for reconciliation using a workflow engine. 
   
• Financial report summarization & Financial Sentiment analysis: Financial services industry operations involve lengthy financial and legal documents - annual reports, contracts product prospectus, research reports, etc. There is a need to summarize these documents to make them easier to consume. Financial sentiments help us in understanding the industry segment more accurately. Document AI helps to summarize important financial documents and gives a financial sentiment across the spectrum to make decisions easier.  
   
• Intelligent document tagging: Large collection of document feeds from multiple sources makes it difficult to search for relevant information. Automatic tagging of these documents can help in retrieving contextual information for any search. Also, automated intelligent document classification is useful in automating multiple workflows across organizations. Document AI has an inbuilt feature that can cluster and classify documents with high accuracy. Multiple-use cases where integration with email servers for automating the complete process has been done. 
   
• Document Data Extraction: Non-Template-based extraction of data elements from large completely unstructured data. This helps in ingesting complex documents like policy documents, Demat / security documents, legal, contract, appraisal documents, etc. The approach is different from what we have as an offering in the market today