IBM Datacap Reviews

My client is GM Financial, which is based out of Arlington in the US and is involved in insurance. 

All documents are scanned and extracted, and later, the workflow is initiated inside FileNet, another IBM tool. It is an end-to-end process that they are using, and some processes involve batch files being extracted and directly exported to FileNet.

The OCR extractions are very good, almost 100% accurate now. The integration with other tools is very easy, with inbuilt actions to configure and directly export to multiple depositories.

It is also good at image enhancement, including the removal of lines, which is helpful in processing and automation and ensures very little user intervention, thus saving time.

We mainly use it for our customer who had specific requirements related to Datacap Insight Edition and the machine learning aspect. We needed to integrate Datacap Cloud into our system to meet those needs.

If I don't have extensive experience in this area, there's a gap, and we're working closely with IBM's technical team to ensure we can provide the necessary solution to our customers because our in-house engineers might not have the expertise to handle this aspect on their own.

The standout feature of this intelligent product is its remarkable capability. This project we're currently engaged in revolves around streamlining workflows within both our company and the customer's company. It entails handling information from various documents with diverse formats and types, even when they contain the same data. The ability to connect this information with the appropriate database and recognize it irrespective of the format or source is an extremely valuable feature. Moreover, leveraging machine learning is crucial since our customer deals with an extensive archive of over five million documents. Machine learning can significantly alleviate the backlog by becoming well-versed in various scenarios they might encounter during their work once we've completed our application.

We use IBM Datacap for data compaction on several different document types. Users can scan the documents and they can upload them to the backend repository where they're stored. 

There are a least seven types of applications. For example, one of our clients is the department of human services in Hawaii. They need to know when someone qualifies for financial assistance if they are elderly, pregnant, etc.

Now I handle data capture, and IBM Datacap is part of my current project. They're using Datacap as a scanner portal for connecting and scanning the data capture, setting up indexes, etc.

My product is an online eligibility system. The user can check their eligibility by filling out that application form. They can fill out that application and enter the necessary information, including the supporting documents like adoption documents, degree verification, etc. 

They upload the requirements to show they are eligible for renewal. Datacap helps them select the application type, and there is a barcode index form. Datacap performs a step-by-step classification and verification process. It will go through each classification step and verify the data. In the end, it exports the data to the correct repository. Various types of documents are there, so the user can select one and upload it to the document index. All documents will be stored in that data system. We can use them anywhere.

Datacap's content navigator, which is the UA for end-users, is great. The IBM content navigator is highly developed with many features. We can customize it by adding different features. When someone scans something we can see who scanned it and get notifications. 

Our technical team has access to the serial CRMS so they can check to see if there are any applications. Once they hand it to the Datacap portal, they can continue the application using feedback CRMS to send it. On the Datacap side, multiple people we can view that, and we can set the validation test.

We can scan thousands of documents. Our on-site team has set up a UIT system, and you can scan tons of documents fast. There is also a system that captures whatever data we enter. Datacap automatically scans why we write with pen and paper and captures everything. We also get reports on the scanned and exported data that is loaded into the system. 

Datacap's performance has improved over the years. It's fast even with a hardware printer and scanner. It only takes seconds to capture a document, so we can process thousands of documents quickly. 

I can have all scanners accessible from my end. I can verify whether the scanners are up to them on whether roles have been added to them or not.

We can see the panel for application-type examples. There are input fields where users can enter their input data. The same data will be added to the database easily. That is integrating with the Oracle database to store content, including PDFs. Everything fits.

There are queues and we can get everything from the database. There's a manual maintenance tool that we can use for batch deletion or reporting. We can put them into Excel. I've written automation scripts for this and I can upload them. It's not robot process automation we are using. Rather, it's the framework automation we are using. We work on a source tool, which is based on tech automation technology.

I work for an insurance company, and we use Datacap for document processing.  

Datacap has performance issues when processing large volumes of documents. We're doing 18,000 pages daily. Scanning takes almost 20-30 minutes, but it normally takes one or two minutes. We informed IBM and opened a ticket for that. They forwarded the issue to developers but didn't give a specific timeline for it to be resolved. Version 8.1 is already at the end of support. 

We would like to see Datacap transition to a cloud-based solution with cloud storage. There is a web interface, but it isn't easy to use. 

We have structured documents that need to be scanned. After the scan is completed, it is reviewed by one of our administrators, and then the documents are stored in the repository. 

There haven't been many improvements in the recent versions of the solution; OCR and OMR facilities have been the same. However, the installation of the solution is very simple.

The main use is to scan/import document for capture, capture data based on OCR zones, verify the data captured and export document and data to the ECM platform or other platfoms if needed.

The user can use the client desktop or the plugin of Content Navigator to do all the required tasks.

We're working closely with IBM's technical team to ensure we can provide the necessary solution to our customers.

The solution has improved digitalizing all the document process

We use IBM DataCap for capturing data from banking forms. We use this data that has been extracted from customer documents   for indexing, and classification for a each customer ,  IBM DataCap  under testing for now . I recently did a course related to IBM DataCap one year ago.

In banking we are  working for clients and we have our relationship with them that must be documented that is why We use IBM DataCap in order to identify these documents and extract all mandtory information which we call the metadata. This metadata could be used in the searching analytic phase to read the type of this document. We use IBM DataCap to read the QR code, that will be generated upon the processing of the document from the customer. Then we scan it then we archive these documents according to the extracted metadata  by IBM DataCap

We are using other solutions in conjunction with IBM DataCap to fulfill our use cases, such as IBM FileNet for classification and retrieval. In the warehouse, we use a solution called FileTrail which have a direct integration point with IBM FileNet "our repository ".

IBM DataCap makes it easier for the end-user to retrieve all documents related to our customers in a very simple way by using the defined metadata.

Firstly, we define the required data which will be extracted and included in the QR code, these data called metadata or attributes, these attributes are used for identifying each document. 

Then we define each document with it is name and defining the QR code location to be defined by  DataCap  during the scanning process