We performed a comparison between IBM Datacap and Jiffy.ai Automate based on real PeerSpot user reviews.
Find out in this report how the two Robotic Process Automation (RPA) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."There's something that's very unique about IBM DataCap. It provides me with a good solution for extracting, reading the QR codes, and scanning them. In this stage, we are working in a UIT phase before implementing this protocol in all our branches. From my initial observation, IBM DataCap is good, it is not working too fast, but in a good manner for us."
"I can have all scanners accessible from my end."
"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 offers many features that are beneficial for customers."
"It is very easy to develop this software. It is low code, and if you can't find the things you need on it, you can develop custom actions with more complex code underneath. They sync well, which is very useful for automating a lot of processes. It is a really valuable feature for the clients because we can ingest information and automate plenty of processes for them. The operators don't have to waste that much time on tasks. With Datacap, they can be automated."
"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."
"I like Datacap's integration with FileNet because financial companies use that export. The second part is web services integration, which is effortless to implement."
"The biggest driver was the cost savings. We wanted to improve productivity and save costs. Therefore, we gave most of the mundane tasks currently being done by a human to a bot. Some of the mundane tasks were reading invoices and keying in the data. We are talking about 15,000 documents every day. That is a huge volume that needs a lot of people. With the bot, it is just a fraction of the cost, because there is a huge savings in terms of manpower."
"Its initial setup process was quite efficient."
"With the customization option, we can write custom expressions using its compatibility with Python or other programming languages."
"The most valuable feature is the computer vision or OCR. That has a lot of use cases in real life. A lot of man hours can be saved, as we've seen in the finance processes... The feedback I have gotten from the team is that the OCR is quite powerful."
"The way Jiffy.ai integrates into existing infrastructure has been great for us. Our company is pretty stringent when it comes to cyber security and integrating with our apps... We've definitely had very strong scrutiny over this platform and this work, and even within that, it's been really successful at being able to integrate."
"It removes the burden of having to do some tasks manually. However, we are just using it in production for a single project. It saves us a lot of time in terms of extracting that information. So far, it has made a big impact."
"I found the invoice data extraction very exciting. It is really good."
"It is a one stop solution for automating process. The modular way that is assigned and works together follows a certain logic, and it encompasses a wide range of processes in a very structured and logical manner."
"Currently, when you are entering invoices, you have to enter multiple rows. In Captiva the multiple rows will be dynamically added. This would be a beneficial feature for IBM to add."
"They have to stop focusing on new development and stabilize the latest release. It is not stable."
"The reading efficiency of the solution needs to be improved."
"Our main language in Egypt is Arabic, and IBM DataCap does not support it perfectly. All our documentation is in Arabic. It's not English or any other language. However, we have overcome this problem by using QR codes in the document to extract the data from it. They should have better support for Arabic."
"Third-party integration could be improved; it's very slow."
"Reporting and analytics seem to often be something of an afterthought. With Datacap, they've started building out some dashboards, but one thing we hear from our clients a lot is, "Well, gee, we really love reports. What Datacap has is not really helpful. We'd like something better. We'd like more dashboards." That's one area where we've seen some feedback that the product could do better."
"The technical support is horrible. They have downsized the support teams too much. They've outsourced some of them along with some of the development, and they're just stretched too thin."
"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."
"The solution's support services need improvement."
"The solution has just not closed the gap of being accessible to non-IT users. If you are a non-IT person, then this all looks like gobbledygook. Maybe that is something that can be improved upon."
"They are still new in the market. Or, at least, they are still a small player. They require a lot of improvement in terms of learning material as well as the community developers. If you compare Jiffy.ai to an established solution, like UiPath, you can go to YouTube and find a lot of learning material posted by UiPath, partners, and other people in the community. However, for Jiffy.ai, you won't find that available in the market. Because of this it is very hard for us to find talent in the market. Most of the developers in the market are used to the bigger players. For Jiffy.ai, if you search a resume because you are trying to find someone who has used Jiffy.ai, you won't be able to find it. So, when we onboard a new person, we want them to learn this new system, but it is a bit hard for them to pick up because there are no external learning materials on the Internet."
"The UI or the UX has room for improvement. The approach for designing the workflow is not that straightforward. It's quite difficult."
"When using UiPath automation, we could just Google issues if we were stuck with something. In the initial days with Jiffy.ai, we could not get that type of information from Google because there wasn't much of a community."
"The setup process could definitely be better."
"I believe this is also being addressed, but a lot of the platform work, as we were putting in new versions or making some updates, was, ironically, very manual. It's improved greatly, but I would imagine that's an area that they're probably still working on, on the backend, to help when it comes to what we need to do for platform support."
"Initially, in version 3, Jiffy.ai did not have support for containerization. In our environment, we are heavy users of containers and container illustrators. So, the initial deployment option was running based on individual hosts that we deployed in the cloud. That created a singularity in the way that we deployed services in our system."
IBM Datacap is ranked 6th in Intelligent Document Processing (IDP) with 26 reviews while Jiffy.ai Automate is ranked 25th in Robotic Process Automation (RPA) with 8 reviews. IBM Datacap is rated 7.6, while Jiffy.ai Automate is rated 8.2. 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 Jiffy.ai Automate writes "The willingness to partner with us and understand our needs was key, as are the time and cost savings from automation". IBM Datacap is most compared with ABBYY Vantage, Microsoft Power Automate, Tungsten TotalAgility, HyperScience and OpenText Intelligent Capture, whereas Jiffy.ai Automate is most compared with Microsoft Power Automate, UiPath, Kryon RPA and Automation Anywhere (AA). See our IBM Datacap vs. Jiffy.ai Automate report.
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