UiPath Reviews

I am an RPA developer and I work with UiPath in that capacity.

Our current use case involves the automation of a process involving healthcare-related data. This is confidential data that is received from the customer and inserted into Oracle forms. Reports are then generated from it and these reports are then used by the organization, which is in the healthcare domain, for their analysis.

The data being analyzed includes medical and treatment history. For example, with the current pandemic going on, there are all sorts of healthcare data that is related to it, including various types of treatments. When somebody walks into any clinic or hospital, all of the treatment is entered into a database and we get an extract of it. The analysis is used to get more details.

Another interesting use case, prior to this one, involved the documenting of invoices. We were working with approximately 250 different samples of purchase invoices, many in different formats. One might be a native PDF file, whereas another could be a scanned PDF, and yet another might be a simple handwritten invoice that was converted into a PDF based on a picture that was taken from a mobile device. We were receiving these invoices from our client and they wanted to extract data from them. It was accomplished by using the Document Understanding features in UiPath.

The other notable use case had to do with issuing refunds for purchases that were made on an e-commerce site. When a customer made an order and there was a problem that resulted in them wanting a refund, there were multiple ways that the client could request one. A refund application could be received by the customer care department in the form of a simple call, which was a verbal request, or as an email written by the customer, or as an automatically-generated email that was created based on filling out a form on the website.

Regardless of which of the three input methods is used, the refund request is gathered and sent to a mainframe application. At that point, the information is extracted from the mainframe and the refund is issued using another application.

The automation of these tasks using features such as artificial intelligence and document understanding has reduced our costs. For example, with the invoice processing use case, there was a team of between 20 and 25 agents who were doing it manually. Obviously, a team of that size has a large cost associated with it. Also, the volume was very high, which meant that the team was not able to deliver on all of the work. There are approximately 250 vendors sending invoices to our customer to process the data, which translates to about 1,000 documents being sent on a daily basis, to be processed by only 25 people. It was a huge task. With this level of volume, people tend to get frustrated. 

We implemented the automation and the team size has now been reduced to only five or six people, and that is only required to monitor the bots. For example, they check to make sure that the data being fetched using document understanding is at par. We have set the minimum confidence of the documents being scanned at 90% and each day, a report is generated and sent to the customer. Overall, it was a very cost-saving implementation.

When it comes to building automations, it's pretty simple. UiPath has a lot of features, starting with Process Mining. For example, when a business person wants to start from scratch, they don't necessarily know which process to automate. They can use the Process Mining feature available in UiPath to get an answer as to whether a particular process is worth automating or not. Features like this are available to shorten the processes. Once a process is identified, we can go ahead and implement and develop the automation. Overall, it is very easy to develop automations because of the inbuilt features.

UiPath provides us with features to implement end-to-end automation, and it begins with the initial steps. They have Process Mining or task mining features to help companies that have an appetite for automation but don't know what they want to automate. Once a process analysis is completed, it can determine whether a process can be automated or not. At that point, we can proceed to the bot development.

Once the bot has been developed, there are different options, including third-party support, for deploying them. After a bot has been deployed, they have the hypercare facility to monitor and maintain bots that are in production. Taken together, all of these features facilitate end-to-end automation. This is very important to our work. 

Consider that UiPath did not always have the Process Mining feature. In those days, in order to do process analysis, companies had to hire Subject Matter Experts (SMEs) for different domains at the beginning of a project to determine which processes could be automated. For example, if there were a requirement for a healthcare process then the company had to hire a healthcare SME. The SME would assist in process analysis and in the determination of whether it was something that could be automated. Nowadays, with the help of the Process Mining features, we no longer have to worry about who is doing the analysis.

From our standpoint, we have to do the recording and supply the inputs. With this, a report will be generated and it will tell us whether the process can be automated. If so, then the developers or an architect will come in and do the development. Following this, the DevOps team will come in for the deployment. Finally, the production support and monitoring are taken care of by the developers.

Using the cloud-based deployment helps reduce our on-premises footprint because we no longer have to take care of servers and local databases. There was a separate team taking care of the networking aspect, and another team taking care of the databases. For on-premises deployments, there are different teams that come into play, whereas with a cloud-based solution, we don't have to worry about anything. UiPath takes care of deployment and the databases, and everything is automatically handled. I can't estimate an exact percentage of how much our on-premises footprint has been reduced, but it has really made a significant impact in terms of substituting or replacing the on-premises facilities.

Attended automation has helped to scale our RPA benefits and in fact, in my almost five years of experience, I have not come across a scenario where the automation could be purely unattended. In the use case with the invoices where we used document understanding, there was still a minimally-sized team of five people in place after the implementation. They monitor the processes and if the criteria of 90% are not met then the invoice will be rejected and sent back to the vendor. In this case, attended automation is really helpful.

The Automation Cloud saves our IT department time because we don't have to worry about hiring different teams for different tasks. The infrastructure maintenance is handled by the vendor and all we have to do is pay for our licenses, then everything is ready.

Automation Cloud has helped to decrease our time to value. You don't have to worry about how the installation is to be done, you just have to pay the license fees and the team will do everything. They have packages, and you just have to give them the numbers according to what you need. Based on that, they will propose a solution and propose an infrastructure for you. Once that is agreed, they will do the installation within a very short time. After that is complete, your developers can start doing the development and within no time, you will start seeing the ROI.

The Automation Cloud has indeed decreased our overall costs.

It is really helpful for an organization to use the Automation Cloud when they do not have sufficient resources available themselves. In situations like this, the UiPath Automation Cloud plays a very important role. You just have to give them the number and they propose the solution including the infrastructure. You just need a few developers and everything else is taken care of by the Automation Cloud team.

We have a lot of clients who are looking at digital transformation, but they don't know what tool to use. There are a lot of vendors available in the market who provide products that are similar to UiPath, but UiPath has a lot of very strong marketing, a strong sales team, and at the same time, the product is very good. UiPath helps in doing quick installations, quicker deployments, and quicker turnarounds. Ultimately, it really helps with digital transformation for any organization.

Digital transformation requires an upgrade, but it is not very complex and not very costly. A company may have to be 25 to 30 million dollars to upgrade, which is a significant cost, but if it saves 100 million then in the end, the organization is saving money.

UiPath has helped to reduce human error to a great extent. When humans perform the same task over and over again, we tend to get bored and frustrated. Our excitement goes down day by day. However, when it comes to machines or bots, they don't get bored and they don't get frustrated having to do repetitive work. This leads to fewer errors, which has a positive impact on the business. There are fewer escalations and the customer is happier.

Our automations have helped to free up employees' time by reducing how long it takes them to complete their tasks. It leaves them time for learning or performing other jobs, and in general, it helps to reduce work hours. I estimate that percentage-wise, it saves my team between 30% and 35%. The total time saved is approximately 250 hours per month.

One of the ways that our employees benefited from having time freed through the use of automation is upgrading. A lot of people, in particular our technical staff, upgraded by learning new technologies. This ultimately led to helping the organization because they are able to work on different jobs.

Automation also leads to an improvement in employee happiness. If you ask them to do the same thing over and over again, on a daily basis, they get bored. When 30% of the time is saved by using automation, it frees up perhaps two hours a day for them to do different work or even recreational activities. 

We have worked on multiple use cases, but most recently, we have worked on a payroll system. Previously, every month, we had to manually get certain details from HR, and we used to do the pay run for all employees in the organization. Now, we automatically extract the required information from the current system by using UiPath. We then prepare a sheet by using Excel, and the entire Excel sheet is processed by a bot. The final sheet is sent for the payslips for the entire organization, and the entire pay report is sent to the bank for payment details.

Automation reduces dependencies. When I have a process that is done by humans, there are dependencies. For example, I need to make sure that the required number of people are available in different shifts. Any process that is done by a human has to be split into eight to nine hours of work. After every eight hours, I have a replacement happening for the same work. So, multiple people are working in different shifts. In addition, any work through humans can only be done from Monday to Friday, or I have to get the team over the weekend. Making our team work over the weekend requires special permissions or approvals. With automation, I am at ease. I'm not dependent on anybody. UiPath is easily accessible from mobiles for the orchestration part. So, if I have a critical process that I need to execute and get the results, I can do it from my mobile. Even when I'm traveling, I can get real-time statistics. 

Previously, I used to get a request at any time to do the pay run for an employee. If the employee was on a leave on that particular day or was not available, I used to miss my target or deadline. Now, we are not dependent on anybody. We are completely independent. If I get a request, the robot is automatically going to process it automatically. I don't even have to tell the robot to run a process after getting a request. All my rules and validations are taken care of by automation before the deadline. If I'm away from the office, my robot can automatically trigger a process on receiving a request. So, we are able to meet all the deadlines, targets, and standards set by the company within the given timeframe.

It has helped in minimizing our on-premises footprint. We work for multiple zones and across the globe. If I have a UiPath architecture, I can deploy it anywhere. Irrespective of the country or continent or zone, I'm able to use the same deployment or the same architecture at multiple locations. It has reduced my cost of infrastructure and maintenance. The cost of everything has come down. Previously, we used to have servers country-wise and continent-wise, but now, we don't need multiple servers and multiple teams to maintain them. I can do things from a single location with a limited set of resources.

The majority of our processes are in the unattended mode, but we do have certain processes in the attended mode where certain end-users provide me the real-time information. We have designed a process where we give a specific form to the user. When the form is filled by the user, a process is automatically triggered, and the robot starts processing. It gives real-time statuses and information to the end-user in terms of what we are doing, how are we doing the calculations, and how are they going to get the benefit by opting for certain features within our organization. I can run my processes in the attended and unattended mode. So, I'm able to trigger both modes of automation very easily.

I am able to keep my customer data integrated. With humans, a data leak can happen, but in the case of robotics, my data is very secure.

The way the processing happens is also very smooth. For example, if I'm on leave or on a break, and a customer calls at my help desk, I won't be able to respond. Now, we have chatbots or robots running throughout the day. When the executives are not there and anyone calls the customer support team, customers are able to get a resolution. They don't have to keep calling or wait. Automatically, the bot is able to respond to their queries and concerns. We have been able to reduce the response time. My customers are pretty much satisfied with it, and they don't have any complaints. Previously, the satisfaction level of the customers was not that great.

The best part of automation is that we can easily integrate multiple technologies within a single tool. I can do it at ease with all of my data flow. Automation is happening across the globe, not only in my organization. Every time we do automation, we feel that there is something overlapping in every process. If I automate a process for my organization and your organization, 50% of the things would be the same. I can very easily maintain common things in automation tools through common libraries or common components. For the remaining 50% of things, we use different technologies. We are integrating optical character recognition (OCR) technologies for document processing. We are also using multiple machine learning methodologies to do pattern matching. We are using artificial intelligence to give a response that is comparable to a human response. 

We use its AI functionality in our automation program. We get multiple requests, and they can be through telephone, emails, or documents. When a request comes through the telephone, the robot or automation is designed to convert that to text. When a request comes through a document, we are using AI features. The document might not have a proper structure, and a customer can give any set of data in any format. So, we have built a special template or format, and this AI is helping us to extract the document with the most accurate results possible. We are getting an accuracy of 95%. With this, dependency is also gone. A human has to properly go through a document. Then, we have to convert the data to the file and process it. With AI, irrespective of the size of the document, which can be 100 pages or 500 pages, we are able to exactly locate the data that we're looking for, and we are able to extract and then process it through automation. We are able to smoothly integrate multiple things within a single process.

Its AI functionality has enabled us to automate more processes. It takes a human 23 minutes to process a 500-page document. With AI features, it hardly takes 7 minutes to process the same document. There is a great reduction in the time taken to do the same task, which is a huge benefit. With AI, I can look for, find, and extract specific information in a particular document, and then I'm able to process the information at ease. I can have documents in different formats. For example, each insurance customer or service provider can have different formats. A human would have to scan through multiple pages to reach the conclusion that this is the right data. AI can easily process different formats, whereas a human being has to be trained for different formats. Humans might also understand something and forget something, but that's not the case with AI or automation tools. They always remember the instructions given to them, which has drastically helped us in making our processes more accurate.

It has contributed to end-to-end automation in our organization. End-to-end automation helps us in completing things in a shorter span of time and utilizing resources in a better way. Previously, for every step of a process, we used to have a different team. We had a separate team for the following:

• Requirement gathering
• Answering the queries for the customers
• Responding to the queries by the ticketing system
• Responding to emails
• Processing particular processes at the backend
• Supporting the infrastructure in real-time

Now, all these things are done by robotics. I only need a few people to maintain my infrastructure. 

We use the UiPath Apps feature, and it has definitely helped us. If there is something that is not available within our team, we can directly use all the apps and features given by UiPath. We don't have to dedicatedly set up a team to design that app. If I have to design a new app or a chatbot for my customers, I can easily integrate the UiPath Apps feature instead of recruiting people, training them, and expecting them to give me the output. UiPath provides help and documentation, and if I require any licenses or support, UiPath's team is always available to assist us.

The UiPath Apps feature has increased the number of automations that we can create. It reduces the time to create automations. We can easily create automation. For a small process, we're able to roll out one automated process every 21 days. We are able to roll out an automated and complex end-to-end process every three or five months to our customers. Previously, it used to take us at least six months to one year to roll out the new features or new functionality to customers, but now, the time has drastically come down. 

It speeds up or reduces the cost of digital transformation. Every time we automate, we are able to speed up automation. We are able to do more things, and more people are working on automation. By using new features that UiPath is bringing and the learnings from my past experience, we are able to automate very quickly. Four and a half years ago, a process used to take four months. Now, it only takes 25 days for me. They have added many features, and I don't have to sit and design those features. They are constantly providing new features in their quarterly releases, and I can simply make the best use of them and implement them in my process.

Previously, I needed people in different shifts, and every human being might not have the same speed or enthusiasm. Humans also need breaks. A robot works throughout the day, and it has a consistent processing speed, so we are able to process more and more. I can plan a target with my robot, and I am able to achieve that. If I'm adding new customers, I just have to integrate one or two more licenses, which is very easy. I can easily create or configure a new robot and start processing. With humans, I have to train them again and again, whereas with automation, once a process is ready, I can use it in multiple robots. I can use it for 25, 50, or 100 robots very easily. I can scale my process rate very fast.

Previously, we were able to process 5,000 customer requests in a month. By using automation, we are able to do the same amount of work within 10 days or even within a week. If we add more human resources, it increases the cost for my organization, whereas, with robotics, I can configure 10 robots or 100 robots. It doesn't increase the cost a lot for my organization, and I can process everything that I want. I don't have any backlog.

It has freed up the time of our employees. This additional time has enabled employees to focus on higher-value work. I am utilizing resources in a much better way, and I am able to give them the work that is interesting for them or is relevant to their growth. When people in my team started working, they found the job interesting. After working for more than two to three years on the same thing, they don't feel that they're doing something new or learning something new. By using automation for a lot of things, I am able to train my team on the new things or technology that they are interested in or want to work with. I am also able to give the work that they're looking for. It is bringing more satisfaction, not only from the customers' perspective but also from my team's perspective. I am able to keep the same resources in my organization for a longer period of time because they're very happy. They are not dissatisfied with the organization.

It has definitely reduced human error. Our accuracy is 99.2%. With humans, our accuracy was 96%, and by using robotics, we have brought the accuracy to 99.2%.

It has also reduced the costs of our automation operations. In the initial year, we saved 10% of the day-to-day operational cost that we had when we were doing things manually. In the second year, it was 30%, and it has increased in the subsequent years. So far, almost 60% turnaround in the business profit has been reported.

It has saved costs for our organization. Previously, for a process, I had to train, for example, 100 people and keep them in multiple shifts. I also had to give them multiple facilities to be a part of the organization, whereas with robotics, I only have to design the process once, and I can use it in any number of bots, such as 10, 25, or 50. It also helps in scaling at no extra cost.

By using automation, we need fewer people for support operations. If the customer queries are taken care of by chatbots, my data and patterns are being analyzed by using AI and ML, and the scanning of the documents is taken care of by OCR, I need very few people for support operations. I need only 10% of people for providing support around the clock.

We have licenses for 15 robots and they are running internal processes. We develop them using UiPath Studio and we only use unattended automation.

Our primary use case, which is 70% of what we have automated, is related to our booking system. Instead of having 10 agents who handle the booking or creating the reservations, the work is done by the robots. Sometimes, bookings are very simple where you have just airfare or the hotel, but in our case, it's quite complex. We call it dynamic packaging, which will have a flight component, you can have a hotel component, different attractions, meal options, a rental car, and more. Instead of entering all of the options manually, which can take up to 10 minutes or 15 minutes just to create a single booking. It is similar when we perform other tasks, such as making a payment. These things are normally done in our target system. I have created robots and workflows in UiPath that are triggered by the database, and they complete these tasks automatically. We have 15 robots conducting the job.

The second use case replaces the agent when once we get all information from the outside system using a .NET application and store it in the database, it creates parameters for the robots to make a booking or reservation at Universal Studios for attractions.

The third use case covers all of Europe and it is a completely automated car booking system. 

Basically, our use cases are all about travel and booking systems for Universal Studios, general dynamic packaging, and car rentals.

UiPath has definitely improved the way our organization functions. It normally takes one agent approximately six hours to create reservations in the booking system manually, and now the job is left to RPA with UiPath workflows. It saves between 40% and 50% of the agent's time, leaving them time to work on something different.

The accuracy of tasks has been improved because everything is data-driven, and there is no problem that comes from human error. The system is almost bulletproof; if you send garbage in then you get garbage out but definitely, there are no human mistakes. For example, instead of entering the name of the customer, it comes straight from the database. The same is true for options like the times of picking up and dropping off your car. The only problem that we have is not related to RPA; it's the case where the target system is not responsive. For example, if you're moving from one screen to another and the system doesn't respond, then we are notified via an alert. 

The improved accuracy and shorter time to complete tasks, freeing up resources for other jobs, translate to money saved. Given that our processes are complex, the automation of them takes a load off of our end-users. In some cases, they have to perform data entry in several different systems. For example, in order to make a booking, they have to use three different systems with three different interfaces.

With RPA, in general, there is also a fear that jobs will be lost but when you're always swamped at work, including overtime, night shifts, and working on weekends, RPA is a big help. 

UiPath has helped to reduce our hardware footprint by between 20% and 30%. We now have only 15 virtual machines running instead of 15 physical desktops. The amount of hardware required to operate the business is directly correlated to the number of human operators and the software that is running.

UiPath has saved us significantly in terms of costs, primarily because of the manpower we used to have for the booking reservation system. It frees up resources for the agents, IT staff, and people from various departments. For example, we have group reservation systems for car booking, flight booking, and others. UiPath has made an impact in all of these places and the cost saving is very beneficial. In the first year, we saved over $100,000 on the booking systems. After the initial project in the first year, two or three more systems were built, for a savings of $300,000 annually before COVID.

In terms of the time we are saving, it is quite low these days because of the COVID-19 travel restrictions. Pre-COVID, we were saving approximately 80 hours per day. The reclaimed time for our employees is now available for them to work on higher-value work. The savings is not only from the data entry but for troubleshooting errors, which no longer needs to be done.

We have offices in Montreal, Vancouver, and Toronto, and the majority of agents are stationed in Montreal. I am working in the Toronto location, so I cannot comment on the majority in terms of how employee satisfaction has improved. What I have heard from the executive management is that more people are happy because they are able to better focus on what they want to do. This is especially true because they do not have to spend many hours troubleshooting trivial issues. Instead, they are concentrating on higher-value work.

My primary use case is to build automation. We started with building automation for enterprises, then shifted to Intelligent Automation, and currently, we are using it for Agentic Automation.

By implementing UiPath, we wanted to solve different kinds of problems. The major one is where people are taking a lot of time to do mundane and repetitive tasks. Some processes have a lot of repetitive steps and a high business volume. We automated those processes. After that, we shifted to something called Intelligent Automation to process scanned documents such as bank invoices, PDFs, etc.

We are now working on use cases with Generative AI for building intelligent applications on top of automations.

Agentic Automation helps with use cases without fixed input and output. Previously, when we were only restricted to robotic process automation, we had to schedule the processes weekly or monthly. Whenever human intervention was required, it was a long loop. For business use cases where we needed a chat interface, we had to go for a different solution altogether and then integrate it with the automation. Agentic Automation helps with all use cases where a person gives unstructured input, such as a person wants to know where his order is or why his account was debited 300 dollars. To cater to all the use cases where inputs and outputs are not fixed, we use Agentic Automation.

The biggest benefits of Agentic Automation have been customer satisfaction and time to respond to queries. We used it for a use case for the L1 support of a client. Previously, the client's customer would call or message on chat, and a human would respond. The support person will go to the system, look for the query, and then revert on the chat or on the call. With the implementation of Agentic Automation, we have enabled the smart AI assistant for the company, so anybody can type anything onto that AI agent, and it is able to understand the context and the background. It knows who the user is, and it fetches all the details. It reduces the time of the support people. They can now focus on more important things rather than repetitive tasks. The response time to the customer is reduced, and user satisfaction has increased. It is also easy to scale. Tomorrow, if the volume of inquiries increases from 10 to 10,000, they do not have to hire more people. They just have to scale their AI agents.

We have had one or two use cases of UiPath Communications Mining. In one use case, the customer had a huge set of data in its on-prem environment, and they wanted to process a list of emails. They were a big hotel chain in the north of the US. They had a support mailbox where a lot of people sent emails related to the services, inquiries, etc. They wanted to monitor and categorize them into actionable insights to identify which features people liked or did not like. With UiPath Communication Mining, they extracted the information, bucketed the email, and got actionable insights. UiPath Communication Mining also gives you things that you need to prioritize. For example, they found out that a lot of people were complaining about the swimming pool, so they knew that the swimming pool was the first thing they needed to improve upon. UiPath Communications Mining was helpful for such actionable insights. After that, we used other products of UiPath, such as UiPath Studio, Orchestrator, or Action Center to build a complete cycle. UiPath Communications Mining turns every message into actionable data in real time, which means that you get insights within a fraction of a second of receiving emails.

UiPath Communications Mining helps automate actions or responses according to the type of content in the message. If they receive a customer email saying that they have to cancel their visit, they can categorize it into a cancellation request. Most of the time, it is able to identify content on its own. If it requires human input, it shows a pop-up on your screen where you can confirm a hotel cancellation request. As soon as you click on confirm, that date is available for other customers. An email is triggered to the support or the customer confirming the cancellation.

The insights from UiPath Communications Mining help the administration people to see what is working and what is not working. In this hotel use case, they can see that out of 1,000 emails, how many were for cancellation and how many were complaints. It provides information about the volume. You can drill into a specific category. It helps prioritize the issues.

The UiPath Communication Mining reduced the time of staff from three hours to fifteen minutes.

The introduction of autopilot into the UiPath products has made work easier. A lot of beginner developers are able to write automation by just giving a prompt. While doing the development and automation, if you are stuck at some point where you need syntax or code, within UiPath Studio, you can request the code. You do not have to search for the solution on the web. With a prompt, you can create an automation to read a PDF and convert it to Excel. It is absolutely low-code. Coding-wise, it is much easier than before.

UiPath provides good support for on-premises environments, which works very well for banks and other businesses that cannot go to the cloud. They have very good enterprise support and a dedicated team supporting on-premises. Their product managers work directly with customers. They continue to add things on the on-prem side. In addition to UiPath Studio, they have added AI Center, Document Understanding, Action Center, etc. They are putting all the things on-prem. They are able to cater to all use cases.

UiPath helps reduce human errors by 70% to 80%. About 20% of human errors are always there because new users are onboarding and systems are changing. You can even reduce them by 90% if your process is extremely streamlined and no human is involved. This reduction varies depending on the use case.

UiPath saves a lot of time and costs for our customers. For one of the use cases, the time taken was reduced from three hours to fifteen minutes. It also helps customers meet compliance.

We are using UiPath for some automations. One of the roles that I have handled over the last two years was related to customer service. In customer service, you tend to have a lot of inquiries and redundant work that can be done through RPA automation. We managed to use it to reduce a lot of recurring tasks. Our experience is very nice when using automation to reduce the workload.

There are a lot of cases related to user inquiries or figuring out how to do things, as well as some tasks related to setting passwords, creating shared folders, and creating virtual machines. These types of workflows are tasks that require only line manager approval, and things can be done without daily human intervention. We have managed to automate staff onboarding and related tasks. 

I have recently changed to a governance role. I am now the governance director at the company. A part of my governance role is taking care of internal and CSR committees. We are considering using automation for good causes.

We are now both a customer and a partner of UiPath. We are using UiPath as a partner because we are selling it to customers and we are also using it internally for the benefit of our employees.

UiPath has helped us a lot to reduce unnecessary load on the agents. In customer service, you tend to do a lot of repetitive tasks. After some time, the employee or agent ends up not being happy because they have been doing the same thing every day. When you take away such reoccurring and redundant tasks, you keep the employee or the agent free to do what matters more. It increases customer satisfaction and employee satisfaction. 

UiPath frees up employee's time for things that matter and need to be done by a human. It has saved 30% to 40% of the time of the customer service staff. We can easily automate tasks that our agent is conducting. The benefits are seen more outside working hours when you have fewer people working.

UiPath helps us be more efficient by freeing staff from doing unnecessary tasks. There is better load balancing and utilization of the agent's or employee's time, so there is going to be more productivity.

UiPath helps speed up digital transformation. Bots can do multiple tasks at the same time. Humans need more interactions for every task.

UiPath helps reduce human error. Bots are more precise than humans. A bot gives the output based on the instructions without making mistakes.

We primarily work with banking clients at a high level, automating solution points, nodes, and bot processes to reduce demand. For example, if a task was previously performed by a hundred people, we have now limited it to around five to ten people by implementing automation to closely monitor the bots in real-time to ensure their effectiveness.

Building automation using UiPath is easy and in most cases can be done with a single click. There is no need to write coding. We can insert and delete columns or remove duplicate frames easily. 

We have already implemented a couple of solutions, one of which is a maintenance automation database. The users of the database want to send emails with attached files and other artifacts, and previously this was done manually. Each day, up to 300-500 items were manually processed by 50-60 people who would navigate to a separate application, search for the file, upload it, and send the email. This was a tedious task and accuracy and reliability were questionable, requiring manual verification. This process was repeated monthly for around 10,000-12,000 items, taking around 25-30 days to complete. We automated this process and provided a high-level solution initially, which was later built, bought, and deployed. The bot we created is capable of processing 900-950 items per day, meaning that all 10,000 items can be processed within eight to ten days. This reduces the processing time by one-third and the cost from 100 to around 12 months, as we only need three to four rotational shifts to monitor the bot. Sometimes the bot may disconnect or encounter issues beyond our control, but we address these promptly to reinstate the process. This is the work we are doing in our organization.

End-to-end automation is a crucial aspect of completing tasks within the specified time frame. Clients do not want to wait for extended periods, such as a month or two, and prefer to see progress at least one-third or one-fourth of the way through. This ensures that clients are not preoccupied with a single task and can focus on improving their business while also increasing accuracy. UiPath aims to provide clients with a high return on investment from both the software build and business development perspectives. This is achieved by delivering effective solutions that meet clients' needs.

We are satisfied with UiPath's community. Occasionally, we encounter some queries or doubts, such as whether we should use a particular feature or MAC code, or whether we can use a certain file. While we cannot always rely on direct support for such minor issues, we found that the UiPath community can be a helpful resource. We search for similar issues that other users may have faced and posted about, and we often find solutions to our questions in a timely manner. Overall, we find the UiPath community to be effective and useful.

UiPath has helped our client reduce their on-premises footprint. This decision is purely based on the client's interests and has nothing to do with our personal or company interests. Generally, clients prefer cloud integration as they want their systems to be up and running 99.9 percent of the time. However, sometimes they may opt for on-premises solutions based on the CDRT of a particular application, which refers to the sensitivity of the data involved. We have some limited automation that deals with sensitive information, such as credit-related automation, which the client cannot access. In such cases, clients may prefer an on-premises solution, but overall, cloud integration is becoming more important.

With the implementation of AI, we can utilize UiPath for automation, which is more dependable.

UiPath reduces the cost of digital transformation.

Our clients are highly satisfied with the nearly 99 percent reduction in human error achieved through the use of UiPath. This includes both individual and team errors. However, during the development phase, some human input was necessary to create rules for the bot to follow. Any potential issues were identified and resolved during testing by our IT and testing teams. Overall, our clients are pleased with the system's reliability and performance.

I have worked on Adi FlexiCapture, and my reviews are good about it because the automation that I had to end up using is still running fine, the document is in proper format, and it works fine. For Microsoft, I have tried using Form Recognizer for some passport extraction, and at that point in time, the extraction was not good. 

The solution speeds up digital transformation, but the cost is on the higher side.

The biggest benefits I have seen from the UiPath Academy include getting familiarized with whatever products they have, as whenever they release a product, they also release a course in the academy along with it. This helps users get familiarized with the tool and understand the capabilities of that particular solution they are putting forward.

We use it for handling processes that involve human effort savings. We are currently focusing on processes and problems that our users are facing in their day-to-day activities. It is used for the automation of business problems that are repetitive and error-oriented with a huge number of users working on them. We list down a set of processes where users are spending a lot of time, then we verify whether the use case is valid for automation using RPA. Once that is complete, we start programming the bot based on the requirements given by the user. We try to mimic each and every action performed by a human being by using UiPath Studio. It replicates what a human being does.

In terms of setup, the development happens in Studio that's on-premise, but the deployment of the robots is done on the cloud. They have their own cloud service called Orchestrator. UiPath hosts that, and it is available at cloud.uipath.com. It is basically the UiPath Cloud. The interface is completely handled by UiPath.

The biggest benefit is that before implementing automation, the users were spending a lot of time doing mundane and manual activities. Implementing the robotic process automation for processes that they were involved in helped them to avoid doing these manual activities and focus on more value-added processes. On the whole, it has helped the users to spend their time more wisely and also get more benefits for the same time spent. It helps us to improve user satisfaction by improving their working methodology because they are only doing things that are value-adding.

We are automating all the manual activities that can be successfully handled by the robots. So, the users are really happy, and we are getting good feedback from the users in terms of time savings. We are also achieving 100% accuracy in the output, which was not the case when the users were performing these actions. When they were performing the actions, the users had to validate the outputs, and the outputs were not as per the requirement. There used to be an error rate of at least 10% to 15%, but with automation, the error rate has been reduced to zero. So, the removal of manual activity and the reduction of the error rate to zero are two of the main benefits.

We are using it in our finance operations for our accounts payable process to process invoices. For this process, we were receiving invoices at a rate of more than 50 per day, and having humans perform those actions was not sustainable in the long run. So, we developed a robot that would automatically process invoices that we received through email. It extracts and updates the data into our ERP, and then, it sends an email to the users telling them that the invoice has been received, verified, and uploaded into our ERP. Now, we have a process that saves approximately two hours for five or more users on a daily basis. At an annual rate, we can save approximately 10,000 hours. We develop the bot in UiPath Studio and then deploy it in cloud Orchestrator via an unattended bot, which is a bot that runs on a predefined schedule. We have a particular time when invoices arrive in our inboxes. We set the robot to run at that particular time, and then the robot is able to process those invoices and proceed to the next action.

We focus only on processes that can be automated end-to-end, completely eliminating human activity. UiPath is flexible, and it allows us to build robots that prevent human intervention right from the start and all the way to the end. Then, we are able to deploy it on the cloud by using the Orchestrator solution. From start to finish, we have completely eliminated human effort, supporting our mission of end-to-end automation. For process analysis, we use a UiPath tool called Task Capture to understand the business case and draw a flow diagram for the steps involved in a process. UiPath has all the solutions required to implement end-to-end automation, and we are successfully using them for all our business problems.

This end-to-end coverage is important. Basically, we select processes where we can avoid human intervention. End-to-end automation is one of the key KPIs that we check before we even start automating a process. It is the first thing that we look for because we prefer no human intervention at all, be it for any kind of input, validating the output, or checking the logs of a process. All of these are predetermined and handled by the robot.

It is cloud-based. So, we do not have any infrastructure costs for maintaining the servers, etc. That is a big advantage. Also, Studio updates for development are pushed automatically. We receive the updates and just click on them, and Studio is updated. Overall, it saves a lot of time for the IT team because there isn't any involvement from IT resources after we deploy or install Studio on our system. From there on, there is literally no involvement of the IT department. That is how beautifully they have designed the tool for the updates as well as overall maintenance.

We went for the cloud to avoid any on-premises server costs that we might need to take care of on a recurring basis. The cloud was a big advantage for us. We are able to save approximately 15 lakh Indian Rupees, which would be $10,000 to $15,000, by not going for the on-premises setup. We were able to save that sort of investment in server costs by going for a cloud-based tool.

We were able to synthesize the value of this solution right from the inception. As soon as we deployed the bots, we were getting actual analytics for the run rate of the process and the total time of bot execution. Indirectly, the time during which the bot executes is literally the time that is saved from human effort. We get proper metrics of the time being saved by using Orchestrator. The other important thing is logs. In case a process fails, from the logs, we are able to derive insights about when exactly a process is failing. We are then able to develop a solution to handle these failures and re-implement them. So, overall the cloud solution gives us insights. It adds value to even developers' time by giving us an overall metric of the time saved as well as utilizing the logs for insights about the process runtime, et cetera. Overall, the cloud functionality is a great value addition.

It affects our ability to scale up automation. When we develop and deploy a process, other users in different departments take a look at the processes, and they are getting confident about the fact that this can solve their problems. We have been receiving requirements, and in that way, we are able to scale up the automation. On top of that, we develop the robots in a way that is modular in nature so that when we implement a process, we have reusable components that can be plugged and played into the new process. This improves the speed at which we can automate processes.

It has indirectly brought innovation from the users' perspective and developers' perspective. The users are saving time, and they are getting innovative in their day-to-day activities. In terms of development, we are on a constant learning path. When the vendor releases new software updates, we are able to effectively utilize those and implement them into our processes on an immediate basis, which improves the speed of delivering a process and the quality of output.

We can scale automation without having to pay attention to the infrastructure for doing so. We don't have to be worried about the cost involved with the on-premises setup. It is a cloud-based solution. So, when a requirement comes up and a bot is developed, only then we need to apply for the license and procure a bot. It has been beneficial because we don't need to pay any upfront cost until the bot is developed and ready to be deployed, and because the bots are delivered completely through the software service, that also indirectly proved very beneficial for global deployments and scaling of processes.

Its AI functionality is helpful to learn from the existing use cases and then implement the learnings on the new and upcoming test cases. As a developer, we need not spend any time developing templates for the extraction, etc. The AI module in itself has the capability to understand new forms of data. It can then accordingly extract and plug in the data to our templates without much effort. So, AI functionality has saved a lot of our time in developing a solution as compared to doing it the manual way.

We had one process where we had to use AI functionality, and we were able to eliminate any manual efforts. Previously, we had somebody who was verifying the output of the bot and after that only processing went to the next step, but with AI, we got the confidence that the bot has the ability to complete the action without manual intervention. That is one great example where AI helped to eliminate manual effort and improve the quality of the output.

It has significantly reduced human errors. Bots have quite a high performance rate with minimal or zero errors. The errors only occur because we haven't updated the business case in the bot. Once the business cases are updated in the robot, we do not see any errors. The bots follow all the steps as programmed and do not deviate from the set of rules defined while developing them. This reduction in human error has had a positive impact on users. The users had been feeling more comfortable using the robot output rather than relying on their own output, which sometimes had errors. So, overall the confidence level has improved and the lead time in delivering the output has also improved. The time they were earlier spending on the validation of their output has reduced. 

It has freed a lot of time. We only automate processes where we find huge time savings. We count it as full-time (FT) employee benefits. We only pick processes that have three or four cumulated FT benefits. With automation, we are saving at least three or four hours on a daily basis. This time is being utilized by business users in completing any other backlog work, focusing on other important things, improving their own work skills, etc.