We performed a comparison between IBM Datacap and Verint Robotic Process Automation based on real PeerSpot user reviews.
Find out what your peers are saying about UiPath, Microsoft, Automation Anywhere and others in Robotic Process Automation (RPA)."The big thing these days is really the Insight Edition component and being able to build annotators to extract from literally unstructured content: paragraphs and information where there's no start anchor point to define where that data is located. There could be a number of entities in that which you have to draw information from. Being able to extract from them is really the differentiator today between that product and many of the other products..."
"The second thing that I like about Datacap is the fingerprint capture which is easy to configure on Datacap. From the form of the document, if a document is redundant in the same department, we can configure the capture based on the form of the documents"
"The feedback from our clients that this solution has increased their efficiency and their turnaround time on opening any account for end users, thus attracting more customers."
"Datacap is good at processing unstructured data. You can build up some nice data flows, and it is simple to configure. The tool adopts a low-code approach, but you can do a lot of coding if you want to customize and automate your flows. Datacap also has the flexibility to integrate."
"The solution automates manual data entry."
"While we are doing indexing, we tag the document type. It's programmed inside of Datacap to automatically detect the document based on a given template. It auto-indexes that document, which means that it automatically tags the correct document type to the scanned document."
"It's resiliency. There are multiple ways of identifying what you are looking for. There are multiple export formats."
"At the forefront of my thoughts, 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."
"Verint RPA gives our clients greater visibility into what's being done and how. It also lightens the load on the workers by automating tasks."
"It can take some time to implement."
"They have to stop focusing on new development and stabilize the latest release. It is not stable."
"The user interfaces for exception processing can be tweaked. I commonly find that we try to tweak and customize some of those components to more of what the industry standard is. The product is still trying to play catch-up a little bit in those areas."
"Recognition between certain numbers and letters could be improved. Sometimes this solution misreads five with an "S" for Singapore."
"Speed of OCR is one issue. It's a challenge because we have customers that have millions and millions of pages that they want this solution to crank through. In order to do that you have to have a large infrastructure in place, and that directly impacts licensing based on the core count."
"Its weaknesses are primarily tied to the lack of available resources and expertise in the market to effectively support and provide solutions and services to each customer for seamless implementation. Expertise in this specific product is rare throughout the market. One key reason is the product's limited downloads. Additionally, archiving solutions are often perceived as complex and challenging, dissuading many companies from venturing into this domain. Consequently, partners who specialize in archiving solutions are always seeking straightforward, uncomplicated options that are easy to manage and meet customer expectations."
"Its weaknesses are primarily tied to the lack of available resources and expertise in the market to effectively support and provide solutions and services to each customer for seamless implementation."
"I give the scalability of the solution a six out of ten."
"Verint RPA needs a more robust toolset to create complex UIs for workers. It's probably not just this product. Almost all automation solutions have similar limitations."
IBM Datacap is ranked 8th in Intelligent Document Processing (IDP) with 26 reviews while Verint Robotic Process Automation is ranked 41st in Robotic Process Automation (RPA) with 1 review. IBM Datacap is rated 7.6, while Verint Robotic Process Automation is rated 0.0. The top reviewer of IBM Datacap writes "The ability to connect this information with the appropriate database and recognize it irrespective of the format or source is an extremely valuable feature". On the other hand, the top reviewer of Verint Robotic Process Automation writes "It lightens the workload while giving our clients greater visibility into what's being done and how". IBM Datacap is most compared with ABBYY Vantage, Microsoft Power Automate, Tungsten TotalAgility, HyperScience and OpenText Intelligent Capture, whereas Verint Robotic Process Automation is most compared with UiPath.
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