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Buyer's Guide
Robotic Process Automation (RPA)
September 2022
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Digital Project Manager at a aerospace/defense firm with 501-1,000 employees
Real User
Top 10
Saves significantly on manpower, but the UX needs improvement, as designing workflows is not straightforward
Pros and Cons
  • "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 UI or the UX has room for improvement. The approach for designing the workflow is not that straightforward. It's quite difficult."

What is our primary use case?

We mostly use Jiffy.ai in finance, for accounts payable, accounts receivable, for scanning invoices, and fetching invoices from the suppliers' websites. 

The new division I'm in, which is a non-finance division, requires some automation as well. We are an engineering division, and the RPA team is starting to look into the non-finance processes. In our division, the processes are along the lines of document scanning and organization of those documents. We need to scan documents and identify the document types and put them in the right folder. It's a very manual, labor-intensive job that we are doing now.

But so far, it is mostly used in finance processes.

How has it helped my organization?

We have definitely seen savings in terms of manpower, especially in the finance processes, which are very labor-intensive and repetitive. Since the automation was implemented, they have been able to reduce the workforce by quite a number.

On a normal basis, a person has to process, say, 100 pages of invoices, but with automation, all that he or she needs to do is manage the exceptions and the errors. He can use the remaining time to do something else that is more valuable.

It also helps to reduce errors. By taking the human out of the equation, we can definitely increase accuracy. This was one of our goals with automation.

What is most valuable?

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 and also in my future use cases. The feedback I have gotten from the team is that the OCR is quite powerful. I'm really looking forward to that.

For the finance processes, from what I know, Jiffy integrated quite well with the Oracle system. Most of the finance requests have been taken care of. It handled the integration pretty well.

What needs improvement?

The UI or the UX has room for improvement. The approach for designing the workflow is not that straightforward. It's quite difficult.

Also, when it comes to a Knowledge Base or training, there aren't many resources online that developers can refer to, unlike the competitors. There's no forum and there aren't too many YouTube videos or that sort of thing. There is also no free trial.

For how long have I used the solution?

I was involved in the RFP and the PoC stages of looking for the right solution for RPA. The process started more than a year ago. It took us quite a while, more than a year, actually, to make a decision. There were a few factors involved. One of them was because of our budget. We didn't really have a budget at the time, but we do have a requirement to source for a suitable RPA solution.

I was involved a little bit during the initial stage, and then I changed my role and joined another department. Since then, I haven't used Jiffy. When I was involved with Jiffy, I was more a project manager. I wasn't really involved hands-on, but I did go through training that they did during the setup and the onboarding process.

Ultimately, we implemented it about six months ago.

What do I think about the stability of the solution?

There's a trade-off. One of the reasons we ended up with Jiffy is that the cost is really low compared to the rest, but in exchange you get what you pay for. To be fair, the people involved with it are not really familiar with the system, because it's quite new. But I've heard quite a few complaints about the usability and stability of Jiffy. Sometimes the bot will just not run for some unknown reason. In those cases, there's no documentation or forum where we can discuss issues. I wouldn't say it's running smoothly all the time. There have been a few issues along the way.

What do I think about the scalability of the solution?

If they manage to resolve all the nitty-gritty small issues, then the scalability is not an issue. 

Our finance processes are not small, they are quite huge in terms of volume, and Jiffy has handled that quite well.

How are customer service and technical support?

One thing that they are very good at is customer support. I still have a good working relationship with the top management of Jiffy and their sales team, even though I'm no longer part of their project. We still keep in contact every once in a while, just to check on the progress and catch up. In that sense, they are really good.

Which solution did I use previously and why did I switch?

Jiffy is our first RPA solution. That's what we took a while to make a decision, because we are not really familiar with all the concepts.

One of the reasons we chose Jiffy is that they are quite new, so they're easier to work with. That is what we are experiencing now. The customer support is really good. They are willing to adapt to whatever we need. 

Product-wise, I think there are superior products on the market, but that comes with a price as well. We wanted to start small. Also, the promise of it running on Chromebook, which turns out not to be true, was a factor in our choice, so we feel quite disappointed about that.

How was the initial setup?

We deployed Jiffy on a Windows Server, running on Google cloud, because the bots, in some processes, have to be running on a 24-hour basis. That's why we needed it to be installed on a server. But in some cases we are running it locally on the laptop, for some basic automations.

What about the implementation team?

We are still very much depending on Jiffy. The agreement that we have is that they will help us to automate 10 initial processes while we are building up our in-house capabilities among our developers. It's quite difficult to find Jiffy-specific talent out there, because it's new. To hire a new developer, we need to train them.

We have two power users of Jiffy in our company, and we have one or two business analysts, while the rest are normal business users. Our team is very small and that is why we are very much dependent on Jiffy at the moment.

Which other solutions did I evaluate?

We ran a few use cases for the common RPA vendors, like UiPath, Automation Anywhere, and Blue Prism. Jiffy came in at the very last-minute. We did run a trial using the system, but one of the issues that we had was that Jiffy didn't really have a free trial account that we could use. They did manage to give us a few trials in a sandbox environment, but it was not straightforward like the other RPA vendors where you can download a trial version and run it on your PC. After we requested quite a bit that we needed some sort of sandbox environment for us to try it on, the Jiffy team allowed us to use it in a limited way. It was not as straightforward as the other players.

One of the reasons we picked Jiffy was that they promised us that it is completely a SaaS solution. Our company is running 100 percent on Chromebooks. We are a Google G-Suite customer and we don't have any Windows machines running. Most of the top RPA software didn't run on Chromebooks at that time. When we met Jiffy, this was the first thing that we were promised, but during the onboarding process we found that that was not the case and that it still runs on a remote desktop Windows machine. To me, it wasn't really a full SaaS solution. It still had to be installed on a Windows Server, accessible from the remote desktop application.

What other advice do I have?

I haven't seen fully deployed, end-to-end processes, because I wasn't really involved in the automation of the finance processes, but from what I've heard, it can be done. The development part takes a while because of the complexity. The creation of a bot or a process is not that straightforward. The workflow setup is quite complex. The methodology, compared to the other RPAs, is more like a flow chart kind of thing. They have used a different methodology. It's not so much a question of whether Jiffy can do it, but more of a question of whether the developers can do it.

In theory, because Jiffy combines RPA, machine learning, workflow, intelligent document processing, analytics, and human intervention features, you can automate without having to integrate with third-party platforms, but we still have to test that. We still need to test whether Jiffy can solidly integrate. RPA is more for front-end automation. In theory, it can work with any system, as long as the UI is clear. As long as a human can click the buttons it can be done.

As an agent of change, because I'm doing digital transformation now in my role, I'm always looking for end-to-end transformation, not just some of the processes within the larger process. The Jiffy approach is good, although it's not unique to Jiffy. The system is very much capable. It's just a matter of how people design and implement it.

Overall, it's a good application to start your RPA journey with. If cost is of concern, then start with Jiffy. If cost is not your main concern there are a few premium products out there, but they come with a huge price tag. They're easier to learn and to use. There are a lot of resources out there. You can easily find developers out there who have experience with UiPath or Automation Anywhere. But if you want to start small, and you have a very small budget, and you are expecting very good customer support, then Jiffy is the one. Their future is bright. They just need to improve a few things along the way.

Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
Managing Director, Business Transformation at a transportation company with 10,001+ employees
Real User
Top 10
The willingness to partner with us and understand our needs was key, as are the time and cost savings from automation
Pros and Cons
  • "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."
  • "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."

What is our primary use case?

We have a number of use cases. We've intentionally started with a focus in our finance controller organization as well as our supply chain organization. The bulk of our bots that have been deployed are in those two areas, doing a number of different business processes across those areas.

How has it helped my organization?

We've seen really good productivity gains. For the areas where we've chosen to automate, it's not that we have freed up 30 heads in one area with one project. It's more an aggregation of 20 heads across all of the different bots that have been developed. But we've seen tremendous value, especially in the pandemic. As an airline, we have had to cut costs and we were able to go through some pretty strong voluntary separation efforts and redistribute resources and cover things because of the automation work that we've been doing.

It has definitely reduced manual processing efforts in our company. We've automated about 10 percent of the work within particular areas that we're working on. I'm sure, across the company, there's a lot more opportunity. We have chosen to start small and get our bearing before we go too far. It has also reduced errors in our organization although I can't put a specific number on that right now. We haven't had as much focus on that front as we have around how much we've been able to automate.

It has also saved us time with the amount of manual work that has been addressed. The time savings are around 5 to 10 percent in the areas where we've been focused. And the automations have helped to save us money, in the $2 million to $3 million range, in annual savings.

What is most valuable?

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. For every automation that we do, we have our technical architects involved especially since, when we implemented this a few years ago, it was really something of a new technology, knowing that you've got "robots" accessing systems and updating records and altering information. It's a little bit daunting if you're not familiar with it. 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.

You still have to integrate with, or at least access, the systems that you're automating within. For example, if you're doing something within SAP, you're still going to need to access data or screens or APIs or something to interact with that system. But the fact that the solution incorporates intelligent document processing, among other features, means we don't have to integrate with another document processing capability or technology. That's a big reason we chose Jiffy.

What needs improvement?

It has gotten better over time, but some of the training and product documentation could 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.

For how long have I used the solution?

We've been using Jiffy.ai for two years now. We are on version 3.2. We're in the process of working through the upgrade to the newest version of 4.2. So we're on the prior version to what is current right now.

How are customer service and technical support?

Their support is fantastic. They're a startup, they're a young company, and the product has things that can be improved on and worked on, but they have been nothing but there for us, and ready to help solve, and ready to help fix.

Some of those things, early on, were with security. Our cybersecurity positioning and stance on what we expect and what we allow and don't allow, are pretty advanced. It was a pretty tall order to meet a lot of our cybersecurity constraints, so that's an area where we had to do quite a bit of work. The very first bot we put into production fell into the PCI realm. We actually have two environments, one that has to be PCI-compliant, and a regular environment, and Jiffy has been fantastic from a partnership perspective.

A lot of the challenges that we uncover are really internal to our environment, as opposed to the platform. There's a little bit of both, and that's where it really comes back to the partnership with Jiffy. They are always super-responsive in addressing any challenges with the product or the platform and supporting us as we work through how to integrate or automate a certain homegrown application of ours that is probably an outdated legacy application. We've run into challenges along the way, but we partner with our internal folks and then with Jiffy to work through the challenges.

How was the initial setup?

Our deployment was over a period of about three to six months. That was because we were working through internal challenges in getting it set up.

I can't speak to the actual architecture, but organizationally we have a center of excellence which is my responsibility and under my leadership. We partner with, and act as more of a matrixed team with, our technology organization. They help with the platform and all of the configuration management, the change management, migration, and production through the different environments. 

With every area that we're developing a bot for, the business area that we're working with—whether that's finance or pricing, etc.—we have engagement and involvement and leadership involved from that side. It's really like a three-legged stool with our center of excellence making sure that we're working on the right things with a good RPA fit, making sure that we're developing in the right way, following the standards and all the things that we need to do from a good-hygiene perspective. Then, our technology organization makes sure we're security-compliant, and they oversee the change management and the architecture, and make sure we're not doing any harm to existing systems that we're trying to access. And, of course, the business is driving where the opportunities are and what are the business processes that we're trying to automate.

What about the implementation team?

Jiffy helped us with the implementation. We leveraged their professional services for the implementation support as well as ongoing development and for RPA architecture-type support as well.

Which other solutions did I evaluate?

We looked at Blue Prism and Automation Anywhere. 

When we were looking at the other platforms and tools, Jiffy's willingness to partner and work with us and truly understand our needs stood out.

It is also more user-friendly. The understanding of the business process, and how that translates into what you need to develop and code within the platform, was more intuitive than what we saw in some of the other platforms.

We also liked something that's in the new version, the version we're not using yet, which is the AI, the artificial intelligence capabilities, including document processing and OCR. We knew those features were coming and didn't require getting individual licenses. The strategy of some of the other product platforms was, "Yeah, we can integrate with any other tools," but we liked the idea of having that capability built-in, and part of the actual platform itself.

What other advice do I have?

Lean into Jiffy as a partner for their expertise and knowledge. Be respectful of the partnership and the relationships, and our experience has been that they will really jump in to help and be there for you. You have to be honest and you have to just make sure you've got good communication in place as you're working through things.

We've definitely automated end-to-end business processes, but you have to find the right level of granularity where you can do it all. We haven't explored an end-to-end process for a major value stream within the company. But within large-grain, end-to-end processes, we've definitely identified many sub-processes, and their entire end-to-end workflows, that we have been able to automate.

We haven't used Jiffy's Natural Language Processing yet. It is something that we would like to explore, among many of those capabilities in the next version. We've just got so much on our plate right now, trying to implement in the current version, that we're trying to figure out that time to cut over.

There is definitely some human intervention, but it's really not Human In The Loop. That's another of those things that will be in our next release and that we've got planned for the future. We wanted to crawl-before-we-walk-before-we-run, so we've started with some more basic automations. I'm sure the capability is there. We just haven't taken advantage of it yet.

A lot of the challenges that we uncover are really internal to our environment, as opposed to the platform. There's a little bit of both, and that's where it really comes back to the partnership with Jiffy. They are always super-responsive in addressing any challenges with the product or the platform and supporting us as we work through how to integrate or automate a certain homegrown application of ours that is probably an outdated legacy application. We've run into challenges along the way, but we partner with our internal folks and then with Jiffy to work through the challenges.

In the beginning, I'll admit, I had some concern about Jiffy's stability as a company. They were working through some additional rounds of funding. They were a small startup when we first selected them, but they've gone through some additional rounds of funding. They've done some hiring. They've done some solidifying. I feel really confident about it now. They're in a good spot, and they've made a lot of good progress this year.

Which deployment model are you using for this solution?

On-premises
Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
Head of RPA COE at a transportation company with 10,001+ employees
Real User
Top 5
You don't have to code; it is just drag and drop
Pros and Cons
  • "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."
  • "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."

What is our primary use case?

Our initial use cases are mainly for finance. We are doing account payable, accounts receivable, reconciliation, and those types of things with the automation. In terms of accounts payable, we automate the invoice processing since it is an end-to-end. This means that the vendor will send an invoice to email, which will be picked up by the bot automatically. Then, it will extract the information from the invoices and post it to our SAP.

It is a web-based solution but hosted on our server.

How has it helped my organization?

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.

More for regulatory and audit purposes, we still require a human to approve it. Previously, we had the human to do it, then we had people cross-check it. Then, you have another layer of the approval. With the bot, we don't require two people. We only have the approval because we still have a person who does the approval, which we have to maintain. 

What is most valuable?

The most important part is how easy it is to pair the automation. So, it is a canvas that is just drag and drop. You don't have to code, so it is a no-code to low-code solution.

It is good for simple tasks that we have done in the past, e.g., reading the invoices. A valuable feature is the document processing. Usually when we talk about document processing in the market, you just have OCR. Where once you extract the information, you need to program or do some type of data wrangling to actually get the value of it or process it. For Jiffy.ai, they have the machine learning behind it, so we didn't need to code one by one. For example, if you have 5,000 vendors who are sending you different types of invoices, then we are not talking about 5,000 invoices. We are talking about one vendor who has three types of templates, so that is about 15,000 documents to process. Even if you do OCR, you want to extract the information and code it to read this and that. So, Jiffy.ai has machine learning where we don't have to teach all the documents, instead we just need to teach it a few. Then, the machine will already know if it finds this type of information, then that is what it is. For example, the easiest way is the invoice number. Most vendors usually have similar wording: invoice number, invoice NO, and INV. However, in all 15,000 documents, you see that the vendors just play around with this wording. It won't differ much. Therefore, the machine learning knows because of this, you don't need to teach it all 15,000 documents. After about 10 documents, the bot can pick it up themselves and learn about it.

There are not a lot of vendors in the market who provide built-in machine learning. In the invoice, you have multiple things that you want to extract: invoice number, PO, and some other line items. With machine learning, we expect it to know what to extract from, by looking at different templates of invoices. It should know that this is similar. Even though you use the different wording across multiple templates, the machine should know that it is an invoice number. We expect the machine learning should be able to do this, and the Jiffy.ai machine learning is able to do it with 80 to 90 percent accuracy. So far, we haven't had a big problem in whatever the machine learning reads, doing it correctly. If it didn't read correctly, we would have to correct it, then the bot will learn from that, "Okay, this is actually the better way," so it can do better next time.

What needs improvement?

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.

For training, they provide the foundation and advanced training. If you have other issues, they have a support portal, which shows a brief summary of the features. It's not very extensive, like Google Cloud Platform. Sometimes there are things that may not be available in the portal. While other products will also not have available the information in their portal, other people know it. So, you don't have in the community discussions about solutions to a problem that would not be available in the portal. 

For how long have I used the solution?

We started this project last year in May.

What do I think about the stability of the solution?

In terms of the portal’s stability, the system is quite stable. We almost never have downtime, and if so, it is very minimal. However, in terms of bot stability, it depends on the server. The bot sometimes gets stuck, then you have to restart the bot, which is something for them to improve.

What do I think about the scalability of the solution?

I do not see any issues in terms of scalability. We can automate a process for a certain department and that process can be very similar to a process of another department. We might need to just change it a little, so we can use the existing solution that we have created. For example, if we create a reconciliation, then the same engine can be used for any big reconciliation tasks in other departments not related to finance. It could be done for engineering, operations, etc. It is very scalable in terms of reusing the existing solution.

How are customer service and technical support?

They are still quite a small player. Because of that, they can focus on the customer a lot more. If I am comparing them to a bigger player or other players that we have worked with in the past as well, they are a lot more responsive, passionate, and focused on us. They help the customer. 

Which solution did I use previously and why did I switch?

We can create almost any type of solution in a very inexpensive way. In the past, we bought software to do certain processes. However, with Jiffy.ai, we can build the same software at a fraction of the cost. We no longer had to buy this other vendor's software anymore, which we licensed every year. With Jiffy.ai, we just have to pay the setup costs in the beginning and have them do it for us. We wouldn't have to pay them if we are doing it by ourselves. If you just use their service and do the setup ourselves, then we don't have to pay for the service, we would just need to pay for the service to use the Jiffy.ai platform to build our software. So, in this example, we are actually saving 97 percent of the costs.

How was the initial setup?

The deployment process is quite fast. Because they are small, they could focus on us. With the development, there are not a lot of processes to do it. We just have to set up the server. We can use their cloud, as cloud hosting or hosted in our on-premises. Even if it is hosted on-premises, the setup is quite fast. Training our staff was also quite fast. I didn't have any issues. I was quite happy with the setup.

The initial setup could take about a month or less, but we also had the incremental setup for our sister company. So, we have multiple entities in our company. The first time that we set up, we set up from scratch so there were a lot of other things that we needed to set up, but setting up another tenant for our sister company took a few days.

What was our ROI?

The reduction of work on a manually basis by project is between 50 to 90 percent. There are some processes where we almost automate the whole thing, and we just need manual handling by a person in certain rare situations. In that case, the reduction could be 90 to 99 percent. However, for certain processes, we can only automate 30 to 50 percent because the rest of the process still needs to be done by a human because of regulatory purposes, etc. So, it's a huge range: 30 percent to 99 percent.

What's my experience with pricing, setup cost, and licensing?

The pricing is quite competitive. As a small player in the market, they are quite aggressive in their pricing. With the features that they offer, it is quite worth the value.

Which other solutions did I evaluate?

Before we chose Jiffy.ai, we looked into other solutions, especially bigger, more established solution providers, like UiPath, Blue Prism, and Automation Anywhere. In terms of simplicity of usage, Jiffy.ai is easier to use since they are on a webpage. We put a portal on it and everything is available there. The UI is a bit more user-friendly and intuitive. 

In terms of trying to do end-to-end process automation and how easy it is to do it, these are big pros and cons when compared to UiPath. In some ways, they are easier, and in some ways, they are not. I like with Jiffy.ai that we can use Python, but with UiPath, we can't use Python and need to use .NET. I'm unsure if they have enabled Python now. We also have a lot more flexibility with Jiffy.ai, e.g., we can connect to Google or any kind of system without having to do integration. We can just go from the front-end and record it. UiPath has this as well. You need to install Orchestrator on your PC. Then, you can install the design anywhere, because it is web-based, which is an advantage.

In other solutions, you have to install and set it up. If I have a new developer come in, then I have to install the system on their laptop before they are able to do their work. With Jiffy.ai, you can do it anywhere, on any laptop, as long as the laptop has access to the webpage. You just need access to the webpage, then you are able to do it. We control it from the portal as well. So, if I want to shut down or restart the bot, then I just have to go to the portal. I don't have to go to somewhere else, log into the server, or remote desktop to several laptops to do it. Everything is centralized on one laptop in one portal: the user access, the bot management, the task management, and the user interface for the human to manually handle certain stuff. Everything is on one page. This is an advantage over other solutions.

What other advice do I have?

You have to be open to trying new things. There are certain things that if you are already used to other bigger players in the market, then there are things that you like and things that you don't like. However, even the things that you don't like, it is mostly because you are already used to the way the service player is doing it. Therefore, if someone is doing it differently, it could be actually better, though it may not feel like it. I think you will find it exceeds your expectations.

Even with using humans, we have multiple redundancies to ensure there are no errors. The end results are not a lot of errors, though using the bot reduces the redundancy in having people check each other's work.

We are still reducing the full-time employees doing the work, but not up to 100 percent. We still need to maintain certain people for handling tasks that can't be handled by the bot, like manual exception and manual handling. Therefore, we cannot 100 percent automate everything. There are certain scenarios that require human judgment, preventing us from using the bot to do them.

I would rate this solution as an eight (out of 10).

Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
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Robotic Process Automation (RPA)
September 2022
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