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RPA Developer at a consultancy with 11-50 employees
Real User
Starts ready-to-use, has good tools for developers, facilitates optimization of existing processes for significant time saving
Pros and Cons
  • "The highest benefit of it is that it's just there, ready to use, and you don't need to start from a blank screen."
  • "From a developer's point of view, my biggest struggle with UiPath is debugging."

What is our primary use case?

I started my RPA journey as a developer, and I first heard about UiPath as a low-code, drag-and-drop automation platform. Back then, it was very much in the beginning stages of its development. Ever since then, I've seen it evolve quite fast. I would say even faster than other RPA platforms that I've used, in just a few years.

Thinking back to when I first started using it, there are many new features and updates and it's my preferred platform for RPA.

We primarily used unattended automation, where you deploy the bots to work autonomously. This is unattended, end-to-end automation with no human in the loop, other than providing the inputs or checking the outputs.

We have several use cases, but our main one is reducing manual work. The processes that require a lot of manual input and have a lot of human error are the focus. That could be, for instance, processes that have to do with invoicing, billing, reporting, and coding, which require a lot of man-hours, are very reliant on a human being available, and are time-sensitive. Those are the ones that are on the top list to be automated.

Beyond that, I can't specifically talk about the processes that we've automated.

How has it helped my organization?

UiPath helps to implement end-to-end automation, although the discovery of processes, gathering requirements, and creating the design, all happen outside of UiPath. But the development, which is developing the bots, then testing and then deploying them, does happen end-to-end within UiPath.

The end-to-end development capability is important, but this is because every tool offers this and it is expected. That said, there is definitely room for improvement in that end-to-end should include process discovery. It is end-to-end, but those ends can extend further than what it currently is. In that sense, it's no different than other RPA tools.

Another way that UiPath improves the way our organization functions is that the robots can run 24/7. If you think about a human workforce, they work eight hours a day, they take days off, they get sick, they leave, and they take knowledge with them once they leave the company. But, the robots can be run non-stop 24/7, and each process can be scaled up. The same process can be run by one bot, or it can be run by 10 or 100 bots. This means that there's a lot more flexibility that the bots bring, especially for high-volume processes that perhaps even have some peaks, such as an end-of-month rush to produce invoices or meet a deadline or an end-of-financial-year crunch.

These robots have an easier time addressing and variability when it comes to volume. They really create a lot more scalability to where businesses can grow and know that they can meet the demands of the future. So, they're a lot more future-proof, whereas people are harder to rely on.

Speaking from a business perspective, it's the FTE savings. A company obviously needs to spend money on UiPath licenses and development costs, but those costs are oftentimes lower than the cost of that FTE, the full-time employee, whose work is getting automated. If you purely just think about the financial benefits, it's the lower staffing costs.

There is also the ability to free up people. This means that even if people aren't replaced and their salary isn't saved, what they can do is pivot their focus to, for instance, be a lot more customer-facing or do a lot more strategic or creative tasks that perhaps get pushed to the side because there's not a lot of time allocated towards performing them. Now, FTEs have a lot more capacity to contribute and perform tasks that still to this day cannot be automated, like creative thinking, complex decision-making on the spot, strategy, and just human interaction.

In the beginning, employees meet automation with a critical eye. They're thinking, "Well, what's going on? Why are these robots coming in? Are we going to work alongside them? How is this going to work?" But to be honest, in the end, there are winners and losers. What I mean by that is that some jobs are replaced, and that's just simply because of that FTE saving that is usually the driver to justify the cost of development. But on the flip-side, the employees that do stay and do work alongside the bots are usually a lot happier because they have to juggle a lot fewer things.

The robots are there to make people feel like people and not like robots, where they just do the same thing over and over and don't enjoy their job or don't enjoy what they do. A robot takes that away and helps people enjoy their work a lot more because they can do non-repetitive tasks. They can be a lot more customer-facing and perhaps build stronger relationships with their customers, know them better, and have more time available to work on other projects or work on other things that they may never have had the time to do.

In our organization, the robots work on multiple projects. The amount of employee time that is freed up depends on the project and what you are automating, but a pretty good estimate would be a 20% to 40% savings.

With respect to the reduction of problems related to human error, the fact of the matter is that some employees, whether you like it or not, are more error-prone. By automating a process, we were able to standardize it, and therefore, identify the cause of the human error and remove it by replacing the process with a robot that makes a more reliable judgment in terms of action. It is literally just an if-else statement. It's a lot easier to quantify and therefore it's a lot easier to evaluate, and therefore the result is a lot more reliable. Whereas with an employee, let's say the output of their work is a lot more unreliable simply because they could be working on 10 different things on the same day. There could be a deadline approaching, and the quality of work fluctuates with an employee because of it.

With a robot, you will notice that over time, in fact, the quality improves, and that's just the basic truth of RPA. It doesn't happen automatically, and it does require work. It happens because you see the results of the automation and you see areas for improvement, ultimately leading you to make adjustments. You iterate on the RPA solution and make it better over time.

Although it does not improve automatically, through a conscious effort you can be a lot more confident in the output and then be able to see unbiased results at the end of the day. Part of these results is your exception rates, which can be errors. It can be failures, whether technical in nature or decision-making business rule types of errors. Then, you can adjust your process to where it can positively improve that exception rate, and just iterate on that to where it becomes acceptable. Moreover, it's quite stable, which is not the case with the human workforce.

The automation cloud Orchestrator has its benefits and negative sides. The benefit is the fact that it's web-based. A person who has the login credentials can access it without the necessity to have something installed. The development and the monitoring of the bots are separated in UiPath, where the development happens in the Studio and the monitoring happens in the Orchestrator.

In other tools like Blue Prism, it happens in the same place. I've used both, and the Orchestrator is nice. It has a very nice UI, it's user-friendly, it has a lot of features, and I find it quite easy to use. For example, you can see all of the machines, you can see the robots, and you can schedule them. If the business wants to see a lot more across the output of the Work Queue, they can have that visibility from Orchestrator, which is great.

The downside of Orchestrator is the package deployment, which is perhaps another minus of UiPath in general. The deployment of a new package does not take a long time, but there are a lot of steps. It's not an intuitive process. If you have to release a lot of packages, which does occur, especially in the early stage of deployment, when you are releasing hotfixes, or when something goes wrong and you need to redeploy a fix really quickly to minimize business impact, it does slow you down.

I wish it would be just one or two clicks, rather than the whole importing or exporting and connecting to the desktop application and everything that accompanies it. I wish it were a lot easier. Again, it has its upsides but it's not perfect.

What is most valuable?

The best feature in UiPath is their robotic enterprise framework because that is an inbuilt processing framework for utilizing their work queues. It's plug-and-play, and already pre-built to where you don't have to start from scratch. It's enterprise-grade and ready to be used. All you need to do is populate your dispatcher, create a queue, create a performer, and you're good to go.

The highest benefit of it is that it's just there, ready to use, and you don't need to start from a blank screen. You don't have to figure out, for example, how to create an environment where the robots can check if there's anything in the queue to be worked on. The framework is already there. The other tools that I've used, like Blue Prism, don't have that built-in quite as well.

My perspective and overview are from that of a developer, and I find that the recorder feature is really good. This is because UiPath lets you record your actions on the screen. So, if you want to interact with a web-based interface, for example, then you have UiPath record your actions and then build the activities that you would need in order to replicate those actions through the robot. It makes it a lot better and although it's not perfect and it does need to be reviewed and adjusted, it speeds up development quite a bit. This is especially true when it's basic back development like populating fields and clicking buttons and navigating on a web.

Compared to other RPA tools that I have used, something that stands out to me in UiPath is that it has a very extensive library of activities. Those activities are easy to search for and use.

When you are writing code, there is a feature called IntelliSense, which autocompletes your code. More specifically, when you're typing code, if you're starting to type the name of a variable, it will show you all of the variables available and you can just click them. It's very interactive and it's reminiscent of the Microsoft Visual Studio environment, both from the UI perspective and the coding perspective. This means that developers that are familiar with Visual Studio will probably feel right at home using UiPath. It's very developer-friendly and it's geared towards appealing to existing developers.

The UiPath Academy courses definitely help in the process of bringing employees up to speed. The Academy is the go-to place for UiPath learning and I think that other RPA tools are copying this model of disseminating knowledge, being a lot more open with training, making it freely available, and providing an online classroom. These are things that UiPath has always done, and it certainly helps new developers get upskilled in RPA, and specifically with UiPath.

When it comes to ease of use, UiPath is intuitive insofar as the basic features have a low learning curve. However, if you want to take full advantage of what UiPath can do, and if organizations want to create more sophisticated automation solutions, it is more difficult. For instance, automations involving back-end access, maybe writing directly to databases such as SQL or using API, that's a steep learning curve. In fact, I think the learning curve is exponential.

If you just want to make a robot that sends an email, that's really easy to do. But, if you really want tangible benefits, like if you really want something that solves a business problem, it is a huge learning curve and it takes a while to master. Obviously, it does have that low-code requirement, but I would say that's only for entry automation projects, like proof-of-concept or something along those lines. For something that really solves a business problem, you would need code, because that just makes it a lot more robust and a lot more powerful if you can custom-code certain steps of the process.

What needs improvement?

Features for process discovery would improve the end-to-end development capabilities.

From a developer's point of view, my biggest struggle with UiPath is debugging. The debug mode in UiPath feels clunky and it is a sore spot. It feels it's hard to control the flow of the process. There are a lot of internal errors and it's not intuitive. In general, debugging is not a good experience and I don't enjoy doing it. In contrast, Blue Prism has better debugging capabilities.

Blue Prism is a little more dynamic; you can adjust variables, you can jump around the flow, and it's easier to control. With UiPath, it's a little bit of a nightmare. It becomes harder to debug the bigger your automation is, because it's quite unpredictable, and it's quite unstable. Definitely, if debugging was improved, I would say UiPath would get 11 out of 10.

Something that I noticed recently is that they have moved to paid certification for developers, whereas it used to have free certification. This is a little bit outside of the platform itself but the pain point here from my perspective is that there is a barrier to entry for new RPA developers, or ones that want to renew their certification. It has become a lot harder and that used to be a differentiator for UiPath. It had a very strong online learning offering and it offered no-charge recertification on top. This is now very similar to what other tools are doing and I see that as a negative.

For how long have I used the solution?

My first introduction to UiPath was in early 2018 or late 2017.

What do I think about the stability of the solution?

The robots could be a lot more stable, which is another area for improvement. The stability issue with UiPath is a prominent one, especially in comparison to other tools like Blue Prism. I feel that there are a lot of errors that are caused by the UiPath framework, as opposed to the robot design. Sometimes it's just very unreliable and crashes unexpectedly, which creates serious issues in terms of reliability. In early deployment, it always happens that it's very late nights, and there's a lot of babysitting processes. The robots need it because you never know what's going to crash.

In comparison with other RPA tools, it is average when it comes to reliability. I would rate other tools a little bit easier to manage expectations as to what you can reasonably expect to go wrong, and what you can reasonably expect to break. With UiPath, our developers, even our experienced ones, oftentimes get errors that we've never seen in our lifetime. This is partly due to the flexibility of UiPath, with it being so easy to adapt to all types of applications and all types of environments and it being so malleable. It is one of the most versatile tools; it's industry agnostic, platform-agnostic, and tool-agnostic, but that flexibility creates a lot more room for error in the code. It means that a lot more things can break or interfere with each other, compared to other platforms that are perhaps more niche and more targeted in what they're actually trying to solve.

What do I think about the scalability of the solution?

UiPath is definitely scalable. It is modular, where you build a workflow and that can be reused across multiple robots or multiple processes. Those processes can then be run by one, two, three, five, and 100 bots, provided that they can work concurrently in the same environment, performing the same process. It's wonderful and the scalability is uncapped. If you have licenses, then you can use them, which is great.

The only limits are how many licenses are you willing to buy, and the inherent limits of your own infrastructure and your own process. It comes down to how many robots can realistically work concurrently in the same infrastructure and in the same network without breaking it.

We have approximately 20 developers who use UiPath. We have business users, but it is difficult for me to say how many there are.

How are customer service and technical support?

I have been in contact with technical support, and I have experienced submitting a support ticket to them. I even got on a call with them and they were very helpful. We had been having issues with automating a platform and we wanted to get their specific insight as to what was going wrong. It had to do with UiPath not being able to extract selectors from that specific interface.

I was really surprised because they spent the time to not only address my ticket and answer my questions, but also to allocate time to schedule a meeting, and really look into the platform via screen share. I was sharing the screen with them and showing them what was happening, and they really looked into it and gave it a lot of attention.

I understand they get a lot of tickets, and I really felt they provided a good answer. They responded really fast, I would say within 24 hours, and we began exchanging details through a back and forth conversation.

They provided me with the outcome that I was happy with. It was a very good experience.

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

In addition to UiPath, we used Blue Prism and Automation Anywhere. UiPath is king here, and I rarely hear anything about the other two. I would estimate that we use UiPath 95% of the time, perhaps even 99%.

The alternative to UiPath that I am more familiar with is Blue Prism. From my perspective, UiPath is geared towards developers. The audience towards which it's skewed is the developer or the technical person. Blue Prism is geared more towards business people. It's geared towards converting business people, including SMEs and subject matter experts that know the process well, into developers. You will find that the language that each program uses is one that's geared towards the target market. Consequently, UiPath uses a lot of developer language and developer concepts.

For example, UiPath works similarly to the Visual Studio Environment. Blue Prism, on the other hand, uses a lot of flowcharting visuals, as well as the language that it uses for the same concept. It's going to use a definition that's more from a business process flowcharting realm. Recently, both platforms are converging onto each other and I feel like they're becoming more and more similar, but they still have a few things that are different.

One thing that stands out for me is that Blue Prism has wonderful debugging. It's a lot better than UiPath, and it's an all-in-one tool where the monitoring and the building of the robots happen in one application. The deployment is also really easy.

Blue Prism also offers online learning, which is great. They didn't use to have that offering, and I think that they got a lot of inspiration from UiPath. Their online courses have been great because previously when I was learning RPA, I had to use YouTube. Now, they have a whole Blue Prism university, which is amazing.

Blue Prism has inbuilt version control and a lot of other great features. They have a heavy emphasis on security and encryption, which UiPath perhaps needs to improve on. Companies such as banks, insurance agencies, and finance agencies are a lot more interested in Blue Prism because of its very strong security protocols. The encryption offering is a key requirement for companies that work with a lot of sensitive personal data.

How was the initial setup?

I have never been involved in the initial setup, although my understanding is that it's quite a journey.

What was our ROI?

The areas of the organization with the most ROI from UiPath are operations, finance, HR, and sales. Those are the key departments, although it's across every organization because those departments have a lot of manual work-intensive processes that are the first contenders for automation.

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

We have a yearly licensing model that gives us access to the development and production environments. The cost of licensing is expensive.

What other advice do I have?

Part of automation is the analysis and optimization of processes because the analysis phase is a by-product of wanting to automate a task. If you want to automate something, you have to break it down into parts and really look at it and think, "How can I reduce this into a series of business rules, a series of decisions, or series of steps?" It's an exercise of process optimization in and of itself because a good practice in automation is to not just take what it is and automate it, but to think, "Does what is currently in place actually work? How can it be improved? How can it be streamlined? How can it be done in fewer steps?" It's a good chance to practice some process review, improvement, and transformation.

The idea is to make it optimal because the current process usually has unquestioned practices that maybe haven't been reviewed for a very long time. A lot of businesses say, "We've always done it this way," and they've never thought to revisit the approach. RPA gives you an opportunity to think about whether what you've always been doing will work when it's being done by a robot. Most often, the processes get streamlined through the requirements gathering phase, understanding the as-is, and then a key part of that is doing the process design, which is the to-be vision.

During that time, processes go through a few design iterations where they are optimized and streamlined because we want the robots to be as efficient as possible. This means performing as few steps as possible without sacrificing value and efficiency. It is important because any inefficiencies in a robot are going to scale with the number of times you're going to run that process. If you run a process a thousand times, and let's say there exists inefficiency that results in an extra minute being used, that could be shed if you were to review and optimize that process.

Ultimately, optimization is an important exercise because the benefits include a further capacity to run more automated processes, and less time is taken up by inefficient steps.

Something to be aware of is that updates to the platform have to be managed because any update could impact the performance of a bot that was built with an earlier version. To avoid having a newer version impact the performance of something that was built previously, all of the updates need to go through a due diligence process.

The biggest lesson that I have learned from UiPath is surprising; not everything needs to be automated. It feels weird to say it because thinking, "Well, I have this platform, I have these bots, why not just automate absolutely everything?", but the truth is that there are things that can be streamlined outside of RPAs. Also, some processes can be automated through other means. Consider the very simple example of sending automated emails, or sorting out your inbox by putting the right email in the right folder, those types of things can be done with email rules rather than RPA.

If a platform already has some sort of inbuilt automation, whether that's a social media platform, email platform, networking platform, or any other type of platform, it's always better to explore that first before looking to solve that problem with RPA. There are times when an Excel Macro or an email rule will be a lot faster and a lot more cost-efficient. RPA should be directed towards big-ticket items, big problems, and large volumes to where no existing solution would provide the same level of value.

My advice for anybody who is considering UiPath is to try it out for themselves. The most beautiful thing is when companies take the leap to have a very small citizen developer team, where they upskill a few technically-minded people with free courses and try to build a small proof of concept to see if RPA is the right path for them. I really encourage that sort of curiosity and experimentation because all of the resources are out there and anybody can learn, as long as they're driven and passionate and curious about automation. I would really encourage people just to give it a try and see what comes out of it.

In our organization, UiPath is the number one RPA tool. Being close to the industry as a developer, and I do feel like it's the preferred tool, at least where I'm based in Australia. It is definitely the preferred RPA solution on the market. Our usage is definitely going to increase in the future. I feel like the future is bright for UiPath. That said, it isn't perfect.

I would rate this solution a nine out of ten.

Which deployment model are you using for this solution?

Public Cloud
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.
Vijay Moorthy
Senior Business Analyst and Consultant at a computer software company with 5,001-10,000 employees
Consultant
Top 20
A valuable enterprise-level tool with the highest level of security, good scalability, and an option to code separately and write a script
Pros and Cons
  • "The entire tool is valuable because it is an enterprise tool. It is on par with other tools like Automation Anywhere or UiPath with the OCR/ICR facilities, analytics, and the entire package for enterprise-level security. It has the highest level of security as compared to any other tool."
  • "There are a lot of things coming up, such as Discovery Bot and Process Discovery. A lot of other aspects are also maturing. We have definitely started using it for our clients, and it is maturing as a solution, but it is all about how you integrate the enterprise with all the automation projects, such as your chatbot, Conversational AI, and robotics. How they are integrated and talk to each other creates a very good business case with all three aspects. The next level should be about integrating it with other automation tools as well. It can have integration with other tools or automation projects, such as your chatbot, Conversational AI, and robotics."

What is our primary use case?

Our use cases are account receivables and account payable. In insurance, our use cases are for vetting beneficiaries, upgrading client portfolios, and updating customer's policies.

What is most valuable?

The entire tool is valuable because it is an enterprise tool. It is on par with other tools like Automation Anywhere or UiPath with the OCR/ICR facilities, analytics, and the entire package for enterprise-level security. It has the highest level of security as compared to any other tool. 

What needs improvement?

There are a lot of things coming up, such as Discovery Bot and Process Discovery. A lot of other aspects are also maturing. We have definitely started using it for our clients, and it is maturing as a solution, but it is all about how you integrate the enterprise with all the automation projects, such as your chatbot, Conversational AI, and robotics. How they are integrated and talk to each other creates a very good business case with all three aspects. The next level should be about integrating it with other automation tools as well. It can have integration with other tools or automation projects, such as your chatbot, Conversational AI, and robotics.

For how long have I used the solution?

I am in robotics for the last seven to eight years, and I have been using Blue Prism for about three to four years.

What do I think about the stability of the solution?

Stability-wise, it is a good tool. 

What do I think about the scalability of the solution?

It is definitely scalable. The whole market of RPA is definitely scalable, but it again depends on your feasibility and complexity when you study a particular environment and process. It also depends on whether you want to scale in the whole organization or different departments or you want to scale up into different areas. All RPA solutions are on par in terms of scalability. There is no difference between them.

How are customer service and technical support?

I don't have any direct experience with them. My solution architect used to handle that. I haven't seen many technical issues because if you are going to deploy the solution and if you've studied enough about the organization and the architecture, then something major is not going to come up. Anything minor, such as securities, passwords, or anything else, can be easily managed.

It is completely run by the solution architects, which is the support team from the RPA side. All technical issues definitely involve the IT team, which is your internal architecture support team and the application support team. You need the support team from the architecture and the IT perspective to manage the technical follow-ups.

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

I have also used UiPath and Automation Anywhere. All these three solutions stand out because they are at the enterprise level. As compared to UiPath and Automation Anywhere, to use Blue Prism, you need developers who have hardcore development experience. It requires quite a bit on the development side. In Blue Prism, you can also code separately and write a script, which adds more value to it.

Blue Prism came too late into the market with its analytics and process discovery features, whereas Automation Anywhere and UiPath were the first ones in the market. Blue Prism is catching up, and it is in the Gartner quadrant, Forrester, etc. It is not lagging far behind.

In Europe, Blue Prism has captured a lot of markets. In the US and Asia, you will see Automation Anywhere and UiPath in the front race. Microsoft, WorkFusion, and Pega are also catching up now.

How was the initial setup?

It is not that complex. It is about how you study an organization and how an organization's architecture runs through. If it is a big organization or an enterprise, then you have to have solution architects from the customer side and also from our side. Solution architects will go and study the customer's architecture. Based on that, we can select which tools are going to be used and how complex it is going to be. It is very much dependent on how the architecture of an organization is because you are going to place the automation tool into that particular organization. Therefore, the initial feasibility and study play a major role in defining the complexity of your design and the entire format or automation.

Initially, the deployment used to take quite long. Now, it is not client-based; it is web-based, and the installation process has been reduced. You just download, and there is no starting a client and all that kind of stuff. It is much easier now than it was before.

What about the implementation team?

In terms of the staff required for the deployment and maintenance of Blue Prism, it depends on what kind of process you're managing. It is not about the tools; it is about the processes. You need to know:

  • How complex they are?
  • What is the risk factor for these processes?
  • How do they impact the entire automation in terms of cost? That is a very important aspect of support because it is in production, and it is going to have a straight impact on the client's revenue.

Generally, one person can easily support around five processes if they fall into the simple category. If the processes fall into the complex category, then you need at least two people managing five processes. By complex, I mean when you have applications that are lengthy and the number of steps of the process are more than 500 or so, and you have to monitor the bots very closely. When the bot or the process breaks, the support team needs to take over and act accordingly. 

The roles and responsibilities and the kind of people needed for maintaining the solution vary based on whether you have agile project management or a lot of projects going on. Typically, you will need a solution architect. You would require an analyst only in the first two or three months or whatever is the period for taking care of the process you want to deploy. After that, you don't require the analysts because it only needs to be overseen from the business side, which will begin with SMEs and the production support team.

Any changes or optimization after 90 days, six months, or a year, due to multiple factors such as legislation changes or anything else, have to be done in the process that is robotized. At this stage, the SMEs and the support team play a very vital role. There should definitely be a very good support function because a lot of follow-ups happen in the process and the production in robotics. To manage them, there should be a very good ticketing system in place. The Agile methodology works perfectly fine, and it adds great value to run your process effectively and having an efficient process, but you definitely need the solution architect, application owner, project management team, and the COE team to manage the entire workflow, work items, or backlog items coming into the support function.

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

It is a bit higher in cost as compared to Automation Anywhere and UiPath. The rate also differs from client to client. Margins are also important when it comes to costing and licensing. There are some additional costs involved besides the standard licensing costs. You have the development team cost, which includes the project manager, development team, analyst, and testers. You also need a team manager. You also have the tools cost, architecture cost, platform cost, and the licensing cost of each bot.

What other advice do I have?

You should suggest a tool only after you study the architecture of an enterprise. Every tool has its own features, upside, and downside. It is not about necessarily going for Blue Prism, Automation Anywhere, or UiPath. For implementing a solution, you definitely need to look in the market to find out what suits you. You can then go for it.  

Blue Prism, Automation Anywhere, or UiPath are on par. There is not much difference in those tools at an enterprise level. The early development cost and the cost of the platform differ in these three tools. There are some clients who say that "We want only Blue Prism. We don't want to look at anything else." In such a scenario, you can definitely go for Blue Prism because it is on par with other competitors. 

The biggest lesson that we have learned from using Blue Prism is that it is important to choose the right processes and the right complexity of the processes. You can't choose highly complex processes where you have around 800,000 steps or very volatile processes where the team is involved in the application layer or at the process level very frequently. These kinds of things could be avoided.

I would rate Blue Prism an eight out of ten because it is a very old tool. It has been around in the market for quite a while, and they have their own learnings. It is a complete package at an enterprise level, where you can have analytics and attended and unattended automation. You can run your scripts, and at an enterprise level, even security aspects are very strong as compared to what is generally required by a client. There is room for improvement. All the new features that are coming up are not being used by many clients, and a lot of learning has to happen.

Which deployment model are you using for this solution?

On-premises
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Head of Intelligent Automation - Africa Regions at a financial services firm with 10,001+ employees
Real User
Top 10
Enables us to serve various automation needs as both tech and business users
Pros and Cons
  • "The Robotic Desktop Automation Express component allows us to do rapid development outside the normal, time-consuming processes."
  • "The product could do more to expand its 'codeless' coding options by adding drag-and-drop assistance in building bots for non-technical users."

What is our primary use case?

We are using WorkFusion as our enterprise RPA solution at this time to help us deploy some automation. It is a hybrid-based installation. Eventually, we are going to try to move everything to the cloud. Some of our customers are dealing with transactions, trader solutions, governance compliance needs, and other special cases so it is not totally possible to go totally on the cloud at this time. There are also clients who deal with things like a KYC (Know Your Customer) type solution, and then a few operational needs like ATM reconciliation and financial revenue reconciliation. The regulations sometimes preclude certain solutions in certain configurations.  

How has it helped my organization?

It helps us to provide some of the bot solutions we need to work with our customers.  

What is most valuable?

I suppose that the most useful feature in WorkFusion has been the desktop solution — also known as a desktop option. It is a type of RDA (Robotic Desktop Automation) express option because it allows us to do very quick developments outside of the normal BI (Business Intelligence) process. Even though the bigger enterprise is obviously more robust, there are a lot of small solutions that can solve pain points in our business at a particular moment that do not require more rigorous development.  

What needs improvement?

Obviously, the WorkFusion Enterprise product is very technical. You have got to be Java proficient and otherwise technically oriented. I guess what could be an improvement in the product is moving towards more "codeless" coding. That would be using things like a drag-and-drop interface to build solutions with premade components. These components would have set functions to simplify using the coding portion of the product for the business user. Instead of keeping the product in use with only the more technically inclined users, they might create a way for the business user to assemble what they need and enhance development opportunities.  

I think a move towards that sort of codeless coding would be a great step in creating more utility for more end users. Maybe API calls or other creative components could be worked in. The express version does not do API calls and the Enterprise version does not do codeless coding. It would be nice to have a solution somewhere in the middle. WorkFusion has got the very easy, light version covered and the very technical, heavy one covered. There seems to me to be a gray area or gap in the middle where a whole set of potential users is not addressed.  

For how long have I used the solution?

I think our organization has been using WorkFusion for three or maybe four years overall. With my group in the Africa regions, we have been using it for about two years.  

What do I think about the stability of the solution?

I do not think we have ever had issues with stability. It seems to be very good from my personal experience. It is more likely that something in the solution will be affected by the environment changing than it just breaking down. The question becomes can an RPA solution adapt to changing architecture through various upgrades and version changes and remain compatible with the environment.  

The stability of the product itself is something we have not had issues with.  

What do I think about the scalability of the solution?

I would say there are probably just less than 100 users currently working with WorkFusion at our company. I am not sure what the total number is, but probably less than 100. Within the African group, we have probably got about 15 to 20 total users.  

Most of the people using the product are using it on a daily basis. The processes created as bots are obviously running in real-time all the time. The developers are either busy with deployments or they get involved from an analysis and design perspective. But working directly with the product consumes a high percentage of the users' time.  

Our scaling is simply replication across countries and geography. There are always new projects and configurations that need to take place to augment the system, but it is pretty easy to scale usage of completed bots.  

How are customer service and technical support?

I do not ever have the need to contact the WorkFusion tech support directly. We have got a Center of Excellence that supports us from a group perspective. We deal with them and they deal with the vendor if anything needs to be resolved.  

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

This solution is actually the first RPA I have used. Maybe it is not so surprising considering the technology is not very old.  

I joined the team after all of the internal architectural decisions, choices, and implementations were completed. Because of that, I can not really comment on the evaluation process. I have just been making use of the system that was in place after its adoption, and I can not really complain.  

How was the initial setup?

I was not involved in the initial installation as it happened before I arrived. I can only say that I have not heard anything about the issues that may have occurred.  

It does require maintenance and there is ongoing support from a technical training standpoint. Then the bots themselves require maintenance and updates. That is, if there is anything that changes in the environment or any process changes, the bots may need to be reconfigured — or even replaced — to work with the changes.  

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

WorkFusion is cheaper than quite a few of the potential solutions, but we have also heard some complaints that it is a more expensive solution than others. It is certainly not the cheapest solution. I think Help Automate came in as quite a bit less expensive. Obviously, we have to have an enterprise solution with a company of our size and there is an opportunity to negotiate to potentially work out a volume discount. That would make the cost less significant in the choice of what we continue to use.  

As far as I know, all other services are included in the license as a single point of pay without any additional fees.  

Which other solutions did I evaluate?

While we have got WorkFusion as a solution at the moment, we continue going through due diligence. We actively check and evaluate the alternatives that are available. We consider it an ongoing or proactive review of our current toolkit. We currently use mostly WorkFusion, but we also use Python for some of the other automation. We are looking at other important products like UiPath, Blue Prism, Automation Anywhere, and Help Automate. Those are the tools that we are pulling in to use for our comparisons. One of them may solve potential pain points the current solutions do not.  

What other advice do I have?

Overall, I would recommend this solution to other users. I have got nothing against UiPath or Blue Prism or any of those other products, and I think there are other options like Python people can make use of. But from my experience with this product, I certainly recommend it.  

On a scale from one to ten where one is the worst and ten is the best, I would rate WorkFusion about an eight. Between a seven and an eight but on the high end of that range.  

Which deployment model are you using for this solution?

Hybrid Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
AshishTyagi
Solutions Architect at PureSoftware Ltd
Real User
Top 5
Good customer support but some technical issues need to be addressed
Pros and Cons
  • "Automation Anywhere provides a very flexible UI."
  • "Sometimes I feel like it doesn't work properly and we are not able to provide the dexterity needed."

What is our primary use case?

I have used BotFarm to automate web applications and Microsoft products. I have also automated mainframe applications for a healthcare product. I automated around five to six processes for them. All together I have automated more than fifteen processes with this solution that we have deployed in-house.

What is most valuable?

The task bots are good features. I also like enabling the IQ bots to read PDF documents and automate PDF projects and invoices. Because we employ so many people, it is very useful to automate any processes compatible with Automation Anywhere.

What needs improvement?

We are not permitted to use web applications, so we find ourselves using Object Cloning and web control commands instead. Sometimes I feel like it doesn't work properly and we are not able to provide the dexterity needed. Also, on multiple occasions, the service bot deactivates without reason and Automation Anywhere will not function properly until it is reactivated.

In general, everything is fine but they should remove the unattended or attended bot feature. This can be confusing to customers because an unattended bot license costs around $5,000, whereas an attended bot license costs roughly $1,500, which can cause customers to think: “why should I purchase an expensive unattended bot license when I can purchase an attend bot license for much cheaper?” Also, if I want to install my runner license on another machine, for example: if you install your license on a specific machine and a second vendor (like we did), you’re now installed on machine B but you can’t log in on machine B with your credentials from machine A. This is meant to be a security feature, but it makes things very difficult for customers and clients.

For how long have I used the solution?

I've been working with BotFarm for the last four years. I started with version 10.10 and currently, I am exploring A2019 which was just launched by Automation Anywhere.

What do I think about the stability of the solution?

Scheduling bots has been an issue. For example, if you want to schedule automation and it’s set for 5:00 pm, it means that you would need to execute it on the client’s machine every day at 5:00 pm. The issue though, is that it fails a lot because I could have it scheduled but sometimes the bots don’t get involved. That’s an issue that has been a struggle.

What do I think about the scalability of the solution?

The scalability is good. We have a team that uses Automation Anywhere on a daily basis, automating processes.

How are customer service and technical support?

In terms of customer support, they are very good. I am an Automation Anywhere vendor and if I have a problem, I can create a ticket on their portal, they will call or set up a Zoom or WebEx meeting within half an hour, and they always provide a solution. 

They give very active support and will definitely help you and provide the solution to the issue you are experiencing. They are very, very good.

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

I used to use UiPath, Kofax and Blue Prism. Automation Anywhere is great for people who are not very "techie". For example, the code can easily be read and understood, line by line, by anyone with or without a technical background.

Automation Anywhere provides and facilitates cloud service, which means you can access your license from anywhere, easily executing and developing your bots from anywhere in the world.  

Any RPA tool provides the commands to automate any process, but what is the difference between them? How can you understand a new product? Automation Anywhere provides a very flexible UI. It allows you to easily read and build code.

How was the initial setup?

Depending on the system that you are installing, the setup can be complex. Installation time is not predictable and you may have to pay customer support for help with the installation procedure.

If I am installing on five machines but one is taking too long, then they all will take a long time, but if all five machines are installing at the same time, then the procedure can be done within five minutes. These ongoing issues make it very complicated to predict how long the installation will take. Someone has to create a ticket with Automation Anywhere customer support and pay for service personnel to help. Installing Automation Anywhere is complex.

In regards to deployment, it's quite simple. Anyone can deploy a bot on a client's machine after one or two days of training.

Also, Automation Anywhere now provides the facility for cloud service, because of this, you can access your license from anywhere. For example, if you are in London and you are heading to another country, you can easily access your license and execute and develop your bots from anywhere. In 2011, this was a desktop application and the client’s version was based on a desktop, but right now it’s not based on a desktop, which is a good thing. The main reason to choose Automation Anywhere is because no one else is providing cloud service.

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

I purchased a package from Automation Anywhere that included one control room, two developer licenses, and two bot-runner licenses. I think payment can vary but it's a re-occurring fee that needs to be paid every year. 

Which other solutions did I evaluate?

In RPA, we have so many products available to choose from which we can use to automate any applications. I have used Blue Prism, UiPath and other third-party applications. I have used all of these tools to automate various processes under RPA technology.

What other advice do I have?

It’s hard to give any advice without seeing the project you are working with. If you want to purchase any RPA tool, then I’d have to check the project or your process so that I can identify the requirement and I can see which product will completely fulfill your requirement. Make sure to choose your solution based completely on the project you wish to automate. In other words, I can’t give you any direct answer. If you’re automating a web application, then I would use UiPath. If you’re also automating their applications but you have to automate PDFs as well, then I would definitely choose Automation Anywhere, but the selection of the tool is completely based on the project you wish to automate.

I am rating Automation Anywhere 7.5 out of 10 in terms of their activity. Sometimes, when I am in the middle of something, I experience issues or my work gets stuck. This rating is based on my three years of experience with Automation Anywhere. Although they give very good support, I still wasted a lot of time because of the above mentioned issues. So, for this reason, I am giving Automation Anywhere a rating of 7.5 out of 10.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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