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Courtesy of Nividous Alan Hester, below is a transcript of the webinar session on 'Demystifying Intelligent Automation (IA) Learn about IA and how it can deliver great ROI' to Build a Thriving Enterprise.
Demystifying Intelligent Automation (IA) Learn about IA and how it can deliver great ROI
Intelligent Automation (IA) is the path forward for those looking for strategic value that fuels business transformation. Many organizations have seen early success with robotic process automation (RPA) however, they have also realized that siloed automation fails to deliver long-term value. IA provides a roadmap to embracing a more holistic approach towards automation for achieving a greater return on investment (ROI).
Intelligent Automation combines RPA and other technologies—various forms of artificial intelligence (AI) and business process management (BPM) tools to enable a new level of end-to-end automation of complex processes. It essentially orchestrates and automates the entire workflow of a process, bridging across various systems, and includes automated tasks in addition to manual tasks completed by humans.
In this session, gather insights on:
Nividous President, ...
Alan, welcome to the webinar, and Over to you.
Excuse me, and welcome everyone.
Appreciate you attending today.
Hopefully, we will be able to give you some useful information about intelligent automation and just to rear iterate, what Shelley said.
If you have any extra them into the question window, and we will reserve some time at the end to address those.
And then obviously, anything that we can't get to, we will follow up with you separately afterwards, so don't feel badly.
If we don't get to answer your question as part of the webinar, we will still provide you with, with an answer separately, later.
So let's start off by looking at some of the business challenges that I'm sure you're all facing to various extents.
And I think this is just to kind of ground us in the topic.
I don't think that there's going to be anything earth shattering here.
Many of you to different extents will see these challenges amplified because of what we're going through with the Global, the Global Pandemic.
Maybe you're coming up with different ways to address them.
But, but one of the things that we're going to talk about today is how intelligent automation can be used to address some of these challenges.
So you can see up there on the screen a number of things, business disruption, lack of innovation.
And when we say lack of innovation, it's not that companies don't have the desire to innovate.
It's just that often innovation gets pushed to the back burner, right.
You spend so much of your time doing the tasks that just keep the light on.
Often you don't have that extra time to spend working on those things that are more forward, looking, strategy and innovation, things like that.
Also, low employee morale and collaboration definitely amplified in our current distributed work environment.
Key things, changing customer expectations, that's also something that I think many companies are finding to be different during the pandemic.
I think customer expectations remain high.
And maybe in some ways aren't even getting higher as they adjust to this new life.
Procuring things differently. Interacting with people differently, interacting with technology differently.
And so that has a lot of impact to many of your companies.
Regulatory and compliance changes, this may or may not apply to your specific company within your industry.
But if that is something that's important to you, then we'll talk about how this technology can help you to address that kind of challenge, inconsistent business growth and as always, competitive pressures.
So what are these specific things that come out of those challenges that pause, potentially, problems on a day-to-day basis within your company?
Many of these you will recognize instantly, and if you don't, it's not necessarily because you don't have them within your company. It could be that you're just not exposed to it from where you sit.
But I'd say that there are very few companies that could say they don't have any of these challenges within there are company somewhere.
So repetitive manual tasks, the kinds of things that waste your people's time, but are necessary in order to keep your business moving forward.
This is getting back to that statement I made earlier about the tasks that are necessary to keep the lights on, Right?
What are those minimum tasks that you need to keep the business up and going and thriving?
And sometimes that relies on people doing things that are outside of their core job.
And sometimes those things are just manual, repetitive tasks that really can be done in better ways or different ways.
Outdated and inflexible systems.
Often, you're dealing with systems that are built many years ago, and you don't have the ability to update them, Maybe the resources aren't available.
Maybe there's no good replacement technology available.
Whatever your situation might be, you could find yourself saddled with dealing with those kinds of outdated inflexible systems and that can be a challenge for you.
Manual on paper based processes, being able to deal with physical paper coming in or maybe PDFs coming in, or things coming in via e-mail, and then having to come up with some kind of process to take that.
unstructured information that exists in those pieces of papers or those documents and figuring out what to do with them.
Um, just a general lack of visibility on your end to end business processes.
Sometimes, you might have good knowledge of where you stand with regard to individual tasks, or maybe individual employees. But maybe not, not the complete big picture review.
Or, it could be reversed.
Sometimes you have a better sense of what's happening, from an end to end basis, but you're blind to what those individual tasks might hold.
So, I'd say both of those kinds of problems can be solved multiple and inconsistent data sources. This is, this is highly related to the previous point.
But often, you have data that exists in lots of different places. And it's hard to get it together in an easily reportable way.
And in a format, that's going to make sense to the people that need it, and also deliver it to them in a timely fashion, so that they can really use it to run the business.
The inability to focus employees on high value tasks, this gets back to the repetitive manual tasks.
If you're taking up a lot of their time, or even just a small portion of their time, doing what those repetitive manual tasks may be, that can take time away from other things, and cause focus issues. And we already talked about the changing customer expectations.
So, now that we have gone through those in detail, let's look at how the combination of the technologies and intelligent automation can be used to solve this problem.
So, what we're calling intelligent automation here is really just a combination of different technologies.
We have robotic process automation, which is using very human interfaces for software.
In a way that, that previously human work is done by bots to accomplish those repetitive manual tasks.
So those situations where you are relying on a person right now to copy and paste information out of one system, into another system.
So that you can get the kind of data that you need for the kind of reporting that you're looking for.
Tasks like that are typically very easily to automate using a technology like RPA. So that's one piece of intelligent automation.
But RPA on its own, can only do so much.
It's really just focused on automating single tasks, and it's very good at doing it.
It's also very good at giving you that detailed information on that task. How long does it take to perform that task for each person that does it?
When was each of the tasks that they're doing started and finished? Where are the bottlenecks, those kinds of things?
You can collect data around and report on, and take action on to improve those individual tasks using an RPA tool.
But, as I said before, RPA on its own can only do so much.
So RPA can be combined with AI or artificial intelligence, so that the kinds of tasks and then the number of tasks across your enterprise, that can be automated, are increased.
Because simple RPA relies on processes that are very rule based.
So you have to have well defined, what are the specific steps that are taken, and decision points that need to be made, so that a bot can perform the task. in a way that will be consistent with how well human would do it.
But when there's more advanced reasoning required, a simple bot is not enough to do that on its own.
And that's where we add in artificial intelligence capabilities, so that some of that higher level reasoning can be accomplished.
And therefore, there are more tasks that can be automated when you combine RPA with AI than you can just with RPA on its own.
And then the last piece is BPM or business process management.
And the reason why this is so critical to add into the mix is this is where you get the ability to manage complete end to end business processes, rather than just discrete tasks.
So if you look across your business, each of your business processes usually has many, many steps involved.
And each of those steps are steps that are maybe performed by a single individual, or maybe a group, Or maybe it's something that's automated, maybe, even by an existing system that you have in place.
And so, when you look at the end to end business process, in order to track that holistically in a way that will be useful, four, your staff, to manage the business, you need to have details for each of those steps across the entire process.
And that's what business process management brings to the table.
That that workflow piece, where you're collecting that data at each step of the process. And you're able to use that in combination with your existing business data.
To come up with the dashboards and reporting that you need to really effectively run and manage your business.
So, robotic process automation, artificial intelligence, business process management, the combination of those things will help you to address all of these challenges that we have brought up today.
So, the way that intelligent automation can do that, and let me just take a minute and point out here, in this presentation, we're calling this intelligent automation, But there is a lot of different terminology that is used by different vendors to describe this combination of technologies.
So, please be clear that anytime I'm talking about intelligent automation, it's in reference to combining RPA, AI, and BPM, So you may hear people using other terms to describe that same thing.
We, for convenience during this presentation, will always call it Intelligent Automation.
So the way that this can help deliver value is really through solving those challenges, you will see enhanced productivity, it really enables scalability, especially important right now as companies are looking for ways to bounce back from the impacts of the pandemic.
I think, in some cases, companies are finding that productivity has been impacted in making the switch to working in an office, versus working for home from home, and they're trying to find a way to close that gap, and also recover profitability, perhaps, or just increase, increase, revenue, order to meet the plan for the year.
And, all of these things can be achieved using intelligent automation, without having to add a large number of additional employees to accomplish it. So, you can offload a lot of these tasks that you would have in the past, had to really rely on employees to do. You can ship those off and have the bots do that work instead.
And this creates higher employee engagement, higher employee satisfaction, better retention.
And it also gives you the ability to focus on some of those more long term things that we talked about, like strategic thinking and innovation.
And it gives you greater insights and accuracy, because you have a lot more data available and better data available with which to manage your business.
So, let's just throw up a poll right now, because I want to get a sense for where you as an audience are related to the use of this technology in your business.
So, if you could just take a minute and answer the poll, And maybe, you would say, None of these options are really an exact fit for my business.
Just pick whichever one is closest, And this will help me to know how much detail we need to go into, on the background of some of these things, especially as we get into the demo.
So, I didn't mention that already, but after we go through some of the basics of Intelligent Automation, we're going to take some time and walk through a demo where I will show you how this technology can be used for a specific use case to solve these problems.
Jay Leno, whenever you think, we have good number of responses. Feel free to go ahead and close out that poll.
OK, well, unfortunately I can't see what the results were. Maybe. Oh, there we go.
So, looks like 40 plus percent already are using this technology and production, and most of the others are thinking about it or planning, to do it sometime in the future.
That's a good background, so a good amount of veterans here, Almost almost half of you.
This is going to just be a refresher course as you get familiar with what we're talking about here today.
So thanks Shelley for sharing that.
And let me go forward to the next slide here where we're going to talk more about each of these components.
And we kind of already went through this at a high level, but robotic process automation brings a lot of things to the table besides just automating those repetitive manual tasks.
one of the things that we find over and over again as we implement automation solutions, companies, and all kinds of different industry verticals, is that there's a good amount of surprise in seeing the results of the bot doing the work in comparison to the human performers of the work.
And this is, no, this is not any kind of.
hidden agenda here, where the bots are coming for people's jobs. I know, sometimes, that becomes a fear.
But the reality is that many of these tasks, these repeatable, but boring tasks that we're asking our people to do, are things that are outside of their core area of expertise, or they're outside of their job description.
And so they're really just doing them to get through the task.
And so what that results in is usually a high error rate.
And so, you know, especially the more that they have to do it, if they're doing it for hours a day, we're going to see the error rate generally climbs over time, the more they have to do it.
Whereas, with the bot doing the work, the bot is going to do the same thing, the same way, every single time.
And so that the error rate is really only present at all based on the quality of the input.
So if there are discrepancies in the input coming into the process, the bot can certainly make a mistake.
Or it can be stuck in some way, but typically if the input quality is good, then the bot is always going to deal with it perfectly.
And that's not something that can be said, said about the human performers.
The AI technology, we've kind of already talked about, in general, how that can expand the scope of what can be done with bots.
But the other things that we haven't really talked about that it can add to the mix is being able to do other, more advanced functionality, like, doing, um, cognitive analysis of existing data. So that you can do things like predictive analytics.
So that you can take data that exists from a process that's already been done in the past.
And use that data to predict how things will tech turn out in the future.
So, this can be especially helpful for things like fraud detection, and things like that.
There's also a lot of other different ways that you can use that for situations where maybe you have large volumes of documents coming in. And currently, you have to have people manually sort through those to figure out how to disposition or classify each of those documents or each of those.
Maybe it's even e-mails and bots can be trained to do that kind of task automatically and also have inbuilt way to be able to deal with validation and also error prevention. So, we will, we will cover some of that in the demo.
There's really some very ingenious ways that the technology is being used so that you will not introduce errors into your process that could cause bigger problems downstream.
And the business process management piece, very big part of this.
That we haven't covered already, And one of the biggest reasons why it's necessary to include this technology, into the mix, is that often, those end to end business processes that we talked about, There are steps that are performed by humans, that always need to be performed by humans.
It's not possible now, and it will never be possible, that every single thing that a human does, will be able to be done, buy a bot.
And so, in recognition of that fact, business process management gives you the ability to orchestrate the tasks that are done by bots or other forms of automation, with the manual, human tasks, and report on it all holistically, and collect that data around that complete end to end process.
So, before we get into the demo, let me just kinda break down the major components of our intelligent automation platform, so that when we look at them in the demo, it will make some sense to you.
So it's really pretty simple. We have a studio, which is our visual development environment.
Developing an automation on our platform does not require you to write any code. It's really just a simple drag and drop interface that once you learn the commands, it's fairly quick and easy to do.
We find that most people who are familiar with doing this kind of work can get up and running in our platform in a matter of weeks.
If you're completely new to the technology, it could take you a little bit longer.
But still, we're talking about weeks rather than months to the point where you, you can be competent developing these kinds of automations in our studio.
So, for many organizations, they choose to build the expertise in-house, and we have training available to help with that. We have a community portal that was recently launched.
That you can go to to get the training that you need, as well as access to the product.
But, also, we have instructor led training available.
If you decide to choose that path, or in many cases, our customers just don't have any desire, or don't have the right expertise to build, in house, that capability and so, they rely on us, or one of our partners, for that part of the implementation. And then in that case, the Studio's kind of meaningless to you because, it will be hidden from you.
That's something that, the developers will work with, and you don't have to interact with at all.
The control center is really the centerpiece of the entire platform.
This is a Web portal based application that typically you only have one of those for your entire enterprise, and this is where the bots are controlled and deployed. This is also where all of the data is monitored and measured.
This is where your dashboards are available, and it's also where the human interaction happens. So, any of those human tasks that I mentioned, that are part of any of your processes, the human interaction with the system, will happen through the control center.
And that might not make sense to you right now, But when we look at this in the demo, I think it will all come together for you, And you understand what I mean.
Then, the last piece, it's the bots themselves and the bots live out there on user class machines.
Bots usually are set up with their own account, similar to human user, would be if they were assigned the same task.
We also have a separate smart Bott library, which is where all of the AI functionality lives.
What we find is that many simple automations don't require the advanced AI functionality.
So, we separated out that library into a separate component, so that, for really simple automations, your environment doesn't have to be complicated to support it.
So, you only would deploy the Smart Bot Library if you need that advanced AI capability.
And let me just point out, one other thing that we haven't mentioned, The iniquitous platform is not a SaaS based offering.
So this is something that will be deployed in your own infrastructure, whether that is your own data center, or your own private cloud instance of any kind.
And the reason why I make this point is that I know many of you are in businesses where security is an issue. And that can often cause major delays with implementing this kind of solution.
And so what we have found is by making this and on premise install where all of your data lives within your infrastructure, And, as I said, that can still be cloud based.
In most cases, it is cloud based, but it's your private cloud.
It's not public cloud, and it doesn't ever leave your own infrastructure that solves most, if not all, of the security issues, and it makes it much, much faster and easier to deploy a solution like this within your enterprise.
OK, let me just take a quick minute and go through a few case studies, before we get to the demo, and this will give you some idea of how some other companies have used this technology for their benefit.
Obviously, the use case that we will walk through in the demo, we'll show you in a little bit more detail, But I wanted to focus on business results here, so that you can see the kind of difference that this can make to your business. typically.
We will see it within companies.
Is that implementing projects like this?
is on a completely different scale from typical IT projects, where we're typically, we'd be talking about months, two years, to implement something that may achieve ROI within 2 to 5 years down the road.
With these kinds of solutions, we're talking about things that take weeks to implement.
And we see ROI, typically within months, if not within weeks, or even days, in some cases.
So, let's look first at this loan processing example, and this will be something that will resonate with many of you, even if you're not in a banking role or in a mortgage role.
Because you will be familiar with how the process works for obtaining a loan. There's usually a lot of paperwork involved.
There's a lot of people involved.
There's a lot of other kinds of agencies involved, and it can make the process very long and drawn out.
And what we have done for several cost customers is automating different pieces of this to make it so that the overall process can be done more quickly, But, more so, that the and user experience can be better.
So you can see there the kinds of saving numbers that we're talking about, 4200 man hours per month, 65% reduction in turnaround time, and 90% faster resolution to complaints.
A second example is one that is around customer onboarding, and especially as it relates to identity verification.
So this points out one of the other key differentiators of our platform, which is that all of the components of the ... platform can be deployed to run natively on a mobile device.
And so in a situation like this, which was a KYC solution where identities have to be verified using different kinds of government or other photo IDs.
That process could be deployed on a mobile device, but not just the fact that it's on a mobile device but that it can run natively on a mobile device, which means that the device doesn't have to have conductivity in order for the process to run.
And, this can be especially important in remote locations. or in situations where you don't have complete control of the network. And maybe there are security issues.
So, the, the process can be run in a disconnected fashion.
The extraction can be done and the data can be sync to on the backend later when a valid, verified, secure connection can be made.
And the overall process is not disrupted in any way.
So, in this case, you can see the numbers here, 75% of the process automated, giving a greater than 90% improvement in accuracy, and 60% reduction in the number of employees that were required to complete the process.
Here, we're talking about a situation where new business proposals need to go through a scrutiny step, where there was a large group of employees that had to verify lots of different tasks related to Documentation.
That was collected on new business arrangements.
And so some of this was KYC documents and other kinds of documents that were coming out of legacy systems.
So, there was no way to control for the document itself by saying why can't this just be done in electronic format to make this process less manual because there was no way to change that input.
And so, the process was automated by putting in place a solution where the bots, in combination with the Smart Bot Library, were able to extract the data from the documents in an automated fashion.
And provide faster, more reliable checks of the data.
Which reduced the turnaround time by greater than 50%, saving greater than 6000 hours per month.
And, more importantly, or, as importantly, huge reduction in human errors in their process.
And the last one we're going to look at is really what we're going to cover in the demo today, which is related to invoice processing.
And so, I won't go into great detail here, because we're going to show this in the demo itself, other than to say that invoices, and this is part of the reason why we're using this as the demo.
It's something that's common to every kind of business.
Everyone is receiving invoices.
And usually, you're also creating invoices, and it's the kind of thing where, as we were talking about, in the previous use case, you don't have control over what the invoices look like that are coming in.
And so, you need to have a good, resilient solution for handling those, regardless of what that input looks like.
So that you don't need to have a huge amount of manual effort to maintain the system over time.
Otherwise, what's the point of automating it in the first place?
So, let me just, uh, go to the demo now, and we're going to come back.
Um, we're going to come back to this chart, because I do want to talk about this, but I want to get to the demo first, so that you can start understanding what this technology really looks like, when it is at work.
So, let me stop sharing the presentation.
And then I will start sharing.
So what we're going to see in this demo is, we're gonna see the control center several times, but in the beginning here, we're gonna look at creating a template for being able to process invoices. So, it's a very simple process. You just need a sample invoice. And it doesn't really matter what it looks like, because, as I talked about before, you want it to be resilient.
And so, really, you are using the sample to define the fields that you want to extract.
And so you enter in those fields. And you also put in information about whether or not it's a table.
And then, when you click on Next, it's going to use that invoice as a way to tie the data that you're looking to extract.
In this particular case, and very important piece is what you see happening right now.
And let me just, let me just stop this for a second here, because, I think, uh, it's important to highlight the fact that these tags that you see on the bottom, are a critical piece of what makes this resilient.
So, when we're going through this, and we define the fields that need to be extracted, we have the ability to drag and drop the field name, as well as the field value. And we can also enter in any additional validations that we need by defining what type of data it is. And we'll see that a little bit more as we go on.
But the tags that I wanted to highlight give you that resilience to be able to deal with invoices that are formatted differently, and that even have different terminology.
So, in this case, the first field that we're looking at is called invoice number, but what happens when you get an invoice that doesn't have an invoice number shown on it?
Maybe that invoice number is called something different, or maybe they use some kind of shorthand notation where they use invoice NO or invoice no, Or, in this case, as we're showing their bill bill number, or? Bill? No.
So, the template gives you the ability to design for that upfront and then also gives you the ability to change that on the fly. And we will cover that in more detail a little bit later in the demo.
But, as you can see, we're going to just quickly run through the rest of the fields here, and define the data that needs to be extracted.
And then, we're going to schedule the bot to run right away so that we can run some invoices through this process. And you can see what the results look like.
And also, so that you can see the other piece that I talked about, which is how you control for quality of the data that has been extracted.
So, right now, we're logged in as a manager into the Control center. You'll see the look and feel is a little bit different, depending who is logged in.
And so, the manager has access to all of the process.
Related piece is including the full workflow of this particular process for the demo.
You can see that we're in the approval step right now, so now we're going to log out as the manager login to log in as the person responsible for the invoice processing.
You can see their view is completely different and tailored towards the world of invoices.
So, if we look at those invoices, now, that, we have processed using the template, you can see that these invoices are completely different from the one that we use to create the template.
But, the data has been extracted here, we can see the original document on the left-hand pane, and the data that has been extracted on the right.
And, we have the ability to make any changes that need to be made.
We also have the ability to reassign this task to someone else, and then as long as everything looks good, it can be approved and it can move on to the next step in the process.
So, in this case, the next step in the process is posting it to an ERP system, but the next step could be anything depending on what your particular workflow looks like within your organization.
Let's see, that this also works on scanned documents, in the same way, And here is where we're going to show you what it looks like when something is below the confidence level that you're expecting.
That comes up highlighted in red, to give you a visual cue for being able to make those changes. And you can set the confidence level threshold to be whatever you want. That's configurable by the end user, and also configurable on the fly. And you can see what the confidence level is of each piece of data that gets extracted.
This same process will work if you're receiving your invoices through e-mail.
Here, you can see a bot is controlling the screen, and it's monitoring a new invoices folder, And all of the invoices that are found are being saved to a central location.
And those will be processed using that template automatically.
So that no human involvement is required, and looking at the e-mails, and saving off the invoices, or M cross, processing the invoices until you get to the approval step.
Which is what we're showing right here, and as long as everything looks good, then the human approver is able to analyze all the information and do the approval right there.
So, here's going to be the case that we talked about, what if something's missing?
So in this case, we defined invoice number as a field, but you can see this invoice has invoice hash or invoice pound, and we didn't define that as a tag.
So in this case, that got recognized by the bot and an admin task was created saying, hey, we didn't get invoice number in this case.
Is it here? If so, where?
So the administrator just has to highlight where that invoice number is, then that gets built into the model for the future, so that anytime that exception comes up, that will be handled automatically buy the bot in the future.
OK, so, let's go back to the slides and let me back up a second.
And Shelly, can you just put that second poll up there real quick?
We're going to put up a poll that has to do it, since so many of you are using this already.
How are you, how are you using it? And even if you're not using it, but you're planning to use it, how are you planning to use this kind of technology?
And the reason why I wanted to bring this up, at this point, is the next slide, we're going to show you a bunch of different processes broken down by functional area, where this kind of automation is commonly deployed with really great results.
So, surely, we can go ahead and close that out, if everyone's done responding, and if you can, pop the results up there.
80% manual data management, 60% optimizing existing business processes, really, across the board here. And I think this is pretty common. Thanks, Shelley. You can dismiss that.
I think it's pretty common that data, and data reporting is a core piece of functionality that this technology is used for.
And so, it's no surprise that in this audience, that seems to be true as well.
But, but as I've mentioned, you can see on this chart, and if this is something you're interested in, I'm not sure if this is one of the things that we've made available for download for you. But if not, we'd be happy to get you a copy of this.
It's really just, it's not an exhaustive list, but it's a simple breakdown of basic processes that are ripe for automation. But typically, we find that it's even easier than this.
We often tell companies, think about those places where you're using a lot of e-mail, or you're using a lot of spreadsheets in your processes, and those are usually the places where you could stand to gain tremendously by looking at automation.
So let me move forward here.
And let's just cover quickly some of the key differentiators of our platform as compared to other things that you might be using or considering.
And this should be review, because I think we've touched on all of these things already.
But the human bot orchestration, you will hear other technologies talk about orchestration and even sometimes human bot orchestration.
I think the difference with our platform is that we're not talking about using humans.
two, resolve errors with bonds. So in many RPA platforms, you will see that there's an escalation path where, if there's an exception, if there's a problem that a bot runs into, than a human can be used to resolve that. And when, certainly our platform is capable of that as well.
But when we talk about human bot orchestration, we're not talking about that, We're talking about being able to automate end to end processes, which include completely human in tasks. So these are human perform tasks that become part of the end to end automation.
And therefore, part of your reporting and data that you have available to run your business with.
And what we see is that, at the executive level, especially, this is critically important.
So the other piece is, we've talked about the AI capabilities, but I'm not sure that I specifically made the point that within our platform, all of the AI capabilities are built by us. There is no external licensing required.
There's no other vendor that you have to be reliant on in order to perform this advanced AI functionality features. Once you have our smart bot library deployed within your infrastructure, then all of your boss, we are enabled with the technology.
And the BPM piece, or IV PMS, as we are calling it here, that's the piece that brings in that end to end enterprise process management that that we've talked about.
We talked about the on device extraction, rapid development.
We didn't really touch on this, but because everything is built and our single studio environment, that means that, from a training perspective, it's very quick to get people up and running. They only have to learn a single tool.
And it's also quick to deploy solutions.
We have recorder's available for multiple different kinds of environments and that can be used as a way to jumpstart.
And then, we also talked about the security issues. one thing we didn't touch on is Extensibility and scalability.
Our platform is really something that's built by developers for developers, which I know is a little bit of an anomaly.
Since I said, you didn't need a developer in order to build an automation on our platform.
And that is completely true, but if you have developers at your disposal, what you can do?
No, there's no limits, because everything it is completely extensible.
Customizable, and scalable, and open to you.
We have perpetual and subscription based licensing.
one of the big things that we are seeing emerging as a use case for this is intelligence document processing.
And one of the big differentiators that we face in this area is that we don't have any transaction based pricing.
So, there are no charges per page, processed or per document type or per template.
Once you have the system setup, you can process as much as you want to, and that's just covered by your licensing and there are no additional costs.
And then the last thing, really is from a services standpoint.
We feel like this is a huge differentiator for us, because when we hear from so many customers, how negative the experience can be when you engage with a big vendor only to find that you then get passed off to a partner that maybe doesn't know as much about how to use or deploy the technology.
And things can take a lot longer and maybe not measure up to what you were expecting during the original sales cycle.
And so we put a lot of things in place to prevent you from having that experience, when you're dealing with us.
And then the last thing that I'll leave you with is that we do have a Quickstart offering that allows you to get up and running either if you're just starting out in this space, or maybe you, you've started, and you you've stalled out, you know, you need to get a jump start to get going again.
This allows you to get everything that you need, both licensing and services, to get one process up and running in production, in a matter of weeks, and we'd be happy to give you more information about that, if that's something that's interesting to you.
So, I'd like to thank you for your time, and we only have a few minutes left here, but if we have any questions, Shelly, um, give me an easy one that can be answered quickly.
OK, yeah, we do have a couple of questions. one of them is, Do you have a browser based BPM modular, or do I need to use something like ...?
So, we, in our current release, we do not have a browser based modeler. That is something that is being worked on for future releases, but it's not currently available.
It is available within the Studio Environment, though, So within the Studio Environment, you have access to all of that functionality within the studio, and also, that integration can be made with whatever source code, control, or repositories that you use for managing those on the backend.
OK, great, another question is about unstructured documents. So does this work with unstructured documents as well?
Yeah. That's a great question that I think.
I tried to make that point clear in that demo, but, but, yes, absolutely, this works with unstructured documents, and, in fact, I'd say we see that, more commonly used with unstructured documents, rather than structured documents. Because, quite frankly, they're just a bigger challenge, and you don't often get the results that you need using OCR on its own.
And so our platform is built in a way that leverages OCR technology in combination with the different AI technologies to give you much better results than you would have with OCR on its own.
And therefore, it makes it much use more useful in dealing with extracting real, useful, highly accurate, structured data from unstructured documents.
We do have a couple of minutes left, and maybe we can take another question, which is around ROI. How do we measure the ROI of an Intelligent Automation Project?
Well, that's a great question, and it makes me wish that we had another slide to give you the URL for this.
But I would say the best answer is to go to our website, ...
dot com, and we have an ROI calculator that's freely available there.
You just, you can enter in the parameters for your project and it will give you a quick ROI calculation.
And if you choose to enter your details, then it will also create a very in-depth detailed PDF report that will get mailed to you.
So, this will give you not just information on the automation of your process but also how building that process out on different commonly available platforms can be compared.
So this can be very useful for you internally for figuring out a way forward when it comes to both building your automations and also deciding which processes to prioritize and to accomplish first within your enterprise.
OK, I'll a quick follow-up question. We have, which is around OCR. Do we have our own OCR or some cloud service? For example, division.
So our platform does have an OCR engine built into it.
However, as I said earlier, our platform is completely modular.
So if you have your own OCR engine that you have already invested in, or maybe it's just some open-source OCR that you're using, that you really like to use, it's very easy to swap that out for what we have included in our platform. So, so, you can use whichever OCR engine you want. But if you don't have one available, we do have one built-in ad.
In any case, it will leverage the advanced capabilities of using OCR, not on its own, but in combination with the artificial intelligence functionality that we have built-in.
So I see that we're, we're at the end of our time.
If there's any other questions that are unresolved at this point, as I said earlier, we will follow up with you after the fact.
But we appreciate your attention, and, um, hopefully you got something good out of this session, that's useful.
Yeah, and I would like to thank Ellen for such a wonderful session, in-depth session. And a quick note that we have our next session scheduled on October seven at the same time, which is 1 0 PM eastern time, and we're gonna cover some more new use cases in DJ that that will sham more knowledge around intelligent automation with respect to industry and function. So, we hope to see you in the next session as well. And meanwhile, if you have any questions, please reach out to us at contact us at ... dot com.
Thank you, Thank you, everyone, for your day. And thanks, Alan.
Alan is a Proven leader and entrepreneur who has a wide range of business experience in large and small companies. He has over 30 years of experience applying technology to solve real-world business problems.
Alan comes to Nividous from Freedom Mortgage where he ended his tenure as the Senior Vice President, Office of CIO. While there, he built a global technology team that delivered award-wining results that helped to grow business revenue dramatically while reducing staffing requirements through automation and process optimization.
A focus on process-centric thinking to drive innovation and strong sponsorship from the executive team allowed for these impressive results to be delivered in under four years. The hybrid team concept which combined onshore and offshore resources and was largely responsible for the success at Freedom Mortgage is now serving as the model for growth and expansion of Nividous in the United States.
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