Session Information:

Getting started with Intelligent Automation - Identifying opportunities for early success and roadmap to scale

With a myriad of automation tools to choose from, many organizations are grappling with how to start their automation journey with the right strategy and operating model. Join us for this final session of the Intelligent Automation (IA) webinar series as we talk about how to get started with IA and scale your automation programs to deliver maximum transformative value.

We will share an effective model to help you navigate from identifying opportunities for intelligent automation to implementing and scaling them across the enterprise. You will learn how to leverage IA technologies for business transformation by building your centers of excellence (CoE).

We will be offering a unique Quick Start Program that guarantees a trained Nividous RPA Bot in production in just 3-4 weeks for those who are new to any automation technology.

In this session, gather insights on:

• How to identify and prioritize opportunities.
• An effective model to start and scale your automation.
• Building your CoE – key insights and best practices.

Session Transcript:

Thank you everyone who's joining us today.

Hopefully, in this session, we will give you a good overview of intelligent automation, and for those of you, that this is not a new topic, maybe we will give you some additional things to chew on, especially as it relates to scalability, Which often can become an issue.

Before we get started, let's just take a minute, and, Kayleigh, can you put up the first poll?

And this will give us a good sense for where you are in terms of Yore Automation, Journies, at your company.

So if you can just take a minute and select which of the answers is closest to your situation, that will give me some idea of how many of us are, are veterans versus newbies, versus somewhere in between.

So cable has, as you start seeing the responses trailing off, you can close the poll and then just let me know.

And everyone, what the results look like, Because I can't see them either.

Oh, So, it looks like half of us are currently running it in production, and the other half are planning to explore what's in the next 12 months.

OK, great, You can go ahead and close that poll then, and we'll get into the content here.

We're going to start off with some of the key business challenges that companies are facing, that we haven't listed here, as the impediments to digital transformation.

But, a lot of these are just impediments in general, and if probably will be familiar to you more than one of these will be familiar to you in your particular work environment.

Often, we're dealing with a lot of repetitive manual tasks, outdated systems, paper-based processes, no visibility to where things stand, A lot of different data sources, it makes it very hard to get the data you're looking for or to get it all together so that you can easily report on it.

And, all of these things create a tension within employees, where, you know, they want to focus on, on doing their job, and creating the most value they can for the company, but, because their attention is often split between their primary job, and all these other things that they have to do, in order to just keep the lights on and keep everything running.

Often, you know, they're, they're not, they're not doing the best that they can because of that, And then, the final thing that's challenging for everyone is, customer expectations, in general, are just going through the roof.

Everyone expects us all to be able to do everything, and do it quickly, and do it for free, or, or for very little. So, you know, all of these things combine to create an environment where it's very hard for your business to succeed without some help.

And so, what we're going to talk about today is how you can use technologies like what we're going to discuss, intelligent automation, to ease some of these problems for you. So we're going to be talking about really a holistic approach to automation.

You will hear, many companies talk about automation in many different ways.

You will hear RPA companies, you will hear, in some cases BPM companies or workflow companies, process mining companies, we don't have shown on here. And also various flavors of, of AI and companies that focus on that. And all of those things play a role in this.

When you look at the challenges that we've already talked about, you can see that these technologies can each help out in certain ways to solve the problem. But, really, you don't get to the end goal, unless you're able to combine all of these in a holistic approach that's going to solve it all for you.

And so that's what we're really going to talk about today.

How, how can you most easily embrace that holistic approach, and not have it, break your bank, and not have to hire 100 people to be able to implement and manage it within your company?

So, we call this intelligent automation.

And it's combining these technologies that, we're talking about, the robotic process automation, the business process management, and the artificial intelligence functionality, into a single platform.

Now, there are some other pieces to this, as well from a technology perspective, but we're going to primarily focus on these three, because with these core three technologies, most of your business processes can be addressed.

There are some more fringe things out there that can sometimes be required, and many of those are built into our platform, as well. But we're not going to focus on that today.

So one of the big differences between what we're talking about here, as compared to other companies and their technology offerings, is that all of this is available out of the box in India with this platform.

So we have these technologies already integrated together in a single platform that's available for a single license fee, and more importantly, can be implemented through a single studio. So we'll talk a little bit more about that as we go.

But often the biggest barrier to adopting these kinds of technologies is getting people with the right skillset to be able to get it implemented for you, right. You might, you might have a product that will do this for you, or maybe you have a combination of a lot of different products that will do this for you. But your IT department is too busy you, and maybe, you know, be six months or 12 months, 18 months before they can get to it. Or maybe your IT department just doesn't have people with these kinds of skills that you need.

Or maybe you don't really have an IT Department, and maybe, you're relying on outsourced IT or something like that, where it's not even really an option for you. And so we're going to talk more about all of those different scenarios as we go here, just digging down a little bit deeper into each of these components so that you know what we're talking about.

Based on our survey earlier, I'm guessing most of you are familiar with the basics of what each of these technologies is.

But robotic process automation, that's the task based automation, where software, robots are taking those repetitive mundane tasks off of the plate of your human employees, which makes it so that those repetitive mundane tasks can be accomplished more quickly.

That work can be done around the clock, and also, that work can be done with less errors, typically, because bots are going to do the work the same way.

And then the same amount of time every time.

The artificial intelligence piece gives you the ability to do even more types of automations, then you can, without it, because it brings in a higher level thinking component, that you don't have without it.

So, for simple rules, based processes, where you can say, hey, in this scenario, know, if, if these conditions are met, and do this, if the conditions aren't met, then do that. For those simple kinds of scenarios. You can build an automation, without artificial intelligence.

But if you want to have the computer be able to do some higher order thinking, you can use an existing dataset, And you can build a model where you say, hey, look at all of these.

You know, hundreds of thousands of examples we have, and the outcomes from each of those, and build a model that helps us, the next time we get in, something like that, figure out, you know, what, which path to take. So, you don't have to have explicit, well defined rules when you bring artificial intelligence into the mix. So, that, that's, that's the added special sauce that artificial intelligence brings into this combination of technologies. And then the last piece, is the business process automation, or business process management. This is sometimes called the workflow piece, and this is also where the human involvement in the process comes into play.

So, one of the big differentiators between an RPA specific implementation and then intelligent automation implementation is that you have the ability to have human steps as part of the process.

So we're recognizing the fact that within most business processes, they will be made up of multiple steps. And some of those can be automated using RPA or other technologies.

And certain steps might not ever be able to be automated for whatever reason.

There might always be a need for human performers to do those tasks, And so for you to have a truly effective solution in this space, you need to be able to account for that. And to make that a part of that end to end process automation, you're building.

And so, using a platform like this, you have the ability to do that.

You have the ability to say, for this step in the process, there is a human performer, and then that human performer will interact with the system, in order to say, hey, I've started working on this.

And then, now I'm finished working on this, And then all of the same metrics that you get, with the automated steps you get with the human perform steps, as well. So you have that full audit trail of activity from the beginning of the process to the end of the process.

Know, each step, when it started, When it was completed, Who completed it, who, who may have worked on it.

You know, whatever handoffs there might have been along the way, all of that, you get automatically by building your end-to-end business process using this kind of technology.

So, let's step back for a second here.

And look at how you can really identify what candidates are a good fit. Candidate processes are a good fit for automation using this kind of technology. And so, when you look at this matrix, it might be fairly simple. But before we get to discussing that, let me just throw out this generic statement. And I say this all the time to people.

And, and I think a lot of times, they think, It's not really this simple, but, in a lot of ways, it is.

If you look at business processes that you have in your organization that require they use a lot of Excel spreadsheets, or they require the use of a lot of e-mail as part of the normal business process, then typically, that is a good target for automation.

And the reason for that is because those kinds of processes where you're using spreadsheets, typically, you're asking the human to be a substitute for good interaction or good integration between systems, right?

If you don't have systems that are able to talk well to each other, you might have to export data from one system, and then get a human to manually manipulate that data, or check that data, and then import it into another system.

Or take the data from both systems, and just manually combine it into Excel and get whatever reporting you need that way, or, or using some other kind of BI tool or visualization tool. But these are the kinds of things that we're getting people to do.

Because either we don't have the right skills in-house or the right technologies don't exist to be able to, well integrate those different systems.

And so, that's why I say, when you look at areas where you're using spreadsheets and e-mail, they're good candidates, because those are the cases where typically, we're asking the humans to stand in the gap between systems.

So, if we look this chart here, the on one axis, we have the value delivered to the company, and then on the other axis, we have the level of complexity.

So obviously, we, we want to focus on the things that have the highest value in the company, and the lowest level of complexity, Because those are the ones that are going to be the easiest, fastest, and least expensive to implement. And yet, they're going to deliver the highest value to the company. And so, that's really all we're trying to show with this matrix here.

Another way of looking at it is we have this chart available, and you can, you can download this.

This is one of the documents that that's available today with this session.

And that's just has broken down by these columns are kind of work areas, and maybe they will correlate two departments in your company, maybe not. But this is just kind of a quick reference to show you, within each of these work areas, what are the business processes that we typically see companies trying to automate using this technology, and be successful with it? So, you might not be able to read that chart too well on your screen right now, but if you download the document, you should be able to zoom in and have no problem saying that, But that's really just a guideline. This is not an exhaustive list. There's certainly plenty of other areas where automation makes sense, and that varies a little bit from business to business as well.

So, Kayleigh, why don't we just take a minute here, and you can pop up that second poll for everyone.

And this is going to give you a chance to answer of where within your organization you currently are using or you're thinking about using automation.

And, you know, there might be, there might be more than one answer that applies, or maybe you don't see anything that's a direct match for whitener, feel free to just choose whatever, whatever is closest.

And, Kayla, again, when you see the answers starting to taper off, you can just close it and let us know what the results look like.

And this will give us all a chance to understand, based on our audience today, what kinds of areas people are trying to use this technology to solve.

So, right now, most people are saying that they're using it for optimizing existing business processes, autonomy.

OK, shortly followed by data management, OK.

Excellent, you can go ahead and close that off for us.

So now we're gonna look at, we're calling this a roadmap.

But it's, it's really just a basic process, or, you know, a high level view of the steps that you need to go through, to put this kind of automation in place across your company.

Then, as I mentioned earlier, a key part of this, is being able to scale this across your organization.

Where we're finding, in the customers that we talked to, being successful in a pilot program, POC, it's very easy.

Almost everyone can get just about any product off the market and bring it in, and take some low hanging fruit, and get a good ROI.

And there are a lot of reasons for why that's true, but.

the key is, how do you then leverage that experience?

And we roll that out in an enterprise wide fashion, so that you can automate as many processes that make sense for your organization, and see that same level of ROI, consistently, for all of the processes that you're automating. And that's where we, we tend to see companies struggling, right?

To get the first one or a couple of projects done, it is fairly easy, but then being able to move forward from that is more difficult. And we'll talk a little bit more about that later.

But if you look at these steps here, they make, they make sense and this kind of follows along with the engagement process that we use here in ....

The first step being discovering and documenting each activity of the identified processes on hand.

So, we start this off with a discovery session we call it where we meet with the stakeholders within a business to kind of figure out, OK, no, not a list of every single business process that you have in your company.

But you know what?

What are those that we think could be contenders for automation and benefiting the company through automation and then trying to then take that list and narrow it down to you know maybe the 2 or 3 top ones That You want to move forward to the next step Which in here we call this define But in our engagement process.

We call this next step A deep dive where we take where we take those top contenders, that 1 2, 3 processes that have been identified and are at the top of the list, based on that discovery session.

We do a deep dive into that, And we figure out, OK, you know, if we really do decide to automate this, what are all the steps in the process, and in greater detail? Is this really a good target for automation?

And is there going to be an adequate ROI to make this worthwhile?

So that's what that defined step is all about. If you get past that point, and you have a single candidate process that you want to move forward with automating, then you get to this step of doing the design.

Which, one thing we don't have specifically called out in this, But it's an important part of this part of the process, is that there's also the need to take a look at the process itself. So, one of the things that we do, is, we document the as's case of the process, so that we can understand, Is this process truly optimized for automation the way it is?

Or do we need to make some changes to the process itself before we automate?

Because we don't want to just be automating a broken process, right, and so, you may be familiar with lots of process mining tools that are out there, that kind of aid you with, with some pieces of this.

We tend to rely on humans more for this piece of the process itself, because, even when you're using a process mining tool, it really takes an experienced human to be able to interpret the results, and know how to move forward, based on that.

And, because, within ...

process, understanding is a core part of our DNA.

We, we have a lot of people with that kind of knowledge, And we just find it easier to approach it that way, as compared to interacting with a process mining tool, which is often an extra cost clip, but within your organization, you may choose to use a tool. And that's fine, too. And then the next step is, after you have that, that process design done, then you go through the development itself.

And get to the point where you're ready for the next step, Which we're calling run here.

where you get something deployed in production up and running, And in many cases, this is where you have the first challenge, which is dealing with the user community, and the change that, this represents to them.

And this is off in, one of the things that organizations struggle with, is how to manage the user side of the equation.

And so we, we have learned a lot of tricks along the way, after doing this for many years.

And this is an area where, where, depending on your organization, you might require some, some extra help to deal with that, because you you do not want to leave that part of it out. I can't overestimate how important it is.

two.

Consider the human change that's necessary to put these kinds of technology automations in place.

And then the last piece here, we're calling scale, which is then, after you have that automation in place, how do you build from that and identify more opportunities to restart the process over again.

And just run through this iteratively until you have all of those potential automation processes completed and up and running in your organization.

So, we talked about the challenges with, with scaling this and scalability.

And one of the key ways that people are dealing with that within the organization is putting in place. Something called the Center of Excellence or sometimes a community of practice. I was just talking to an analyst at Gartner about this yesterday. And he was mentioning that for more mature.

Organizations, They're seeing this emergence of fusion teams, which is kind of a different twist on a center of excellence or community of practice, where they're having business and the IT collaborate together on completing these projects.

And he's saying that organizations that do that have a much better chance of success than those that try to drive that change across the enterprise from their existing silos, whether that's either solely on the business side, or solely on the IT side, that there's a much better chance of success when you have these fusion teams in place. And they're viewing that as being more representative of a, of a mature organization when you take that approach. So there's a lot of different aspects of this, and we're not going to cover this in any great detail in this session.

But if this is something that you have deeper interest in, please reach out to us and let us know.

And this is something that we can certainly share more best practices on, and maybe help you out with your journey as a relates to being able to scale up these projects across your enterprise, using centers of excellence. Are communities of practice?

So now I'm just going to take a minute here to explain the ... platform and how it works.

one of the things that I mentioned earlier, that's a big differentiator for us as compared to other platforms is that we have all these technologies already integrated and combined in a single platform.

They're all built by us. We're not licensing someone else's technology. There's no hidden costs.

because we're paying someone licensing fee Or, or you have to pay someone, a licensing fee. after the fact, to get a certain type of functionality.

It's all there out of the box.

And the other part of that benefit that we've talked about, is that there's a single studio environment, where you build all these automations from.

So, both the, the RPA piece, the BPM piece, the AI piece, it's all built from a single studio.

So for those of you who want to build this expertise in house, either because you're trying to deliver these kinds of services to your customers, or because this kind of work, you want to be able to do internally.

You only have to teach people a single tool.

In order to build and maintain these automations, they don't have to learn a number of different tools to do that.

Now, some of you may be sitting there and thinking, Well, that's, that's great, but we don't really have any interest in doing that at all.

We don't. We don't have the right people to do that, we don't have the right skill sets, and that's fine. And, in fact, most of our customers take that approach.

And so, we have a good partner community with a lot of skills available to deliver these kinds of implementation services for you and with you. And then, we also have our own in-house professional services team that can deliver these implementations for you, and not just build it and then hand it off to you.

But, for many of our customers, we keep an ongoing relationship where we have a team engaged in many cases for years, just continuing to build out additional automations over time as the need presents itself within their organization.

So, that's the studio piece.

From there, we'll move to the control center, and this is really the heart and soul of the platform.

This is A web based portal application that sits on a server keillor, Either in your private infrastructure environment, in your data center, or in your private cloud.

And we do it that way, because this helps too alleviate any security issues.

There might be, if maybe you're in a sensitive space, or you have the need to have some controls over your data.

You have the ability to have the same level of security and control over the data that's that's being used on our platform as you have for everything else that exists within your infrastructure. Because nothing ever is really leaving your infrastructure at all.

So, the Control Center is where all of the bots, ARR, deployed from controlled from. This is where you have your full audit trail.

This is also where the human interaction with the system takes place. So, if you think back to that example that I mentioned earlier, about how there's a step in a process that is a human performed step.

So that human would log into the control center, and they see they have a task assigned to them.

And so, they, they pick up that task, Which says, hey, I'm working on this, and then they go back in, too.

Complete that task or later now. depending on what the task is, there might be other parts of that Task that they have to interact with the system on also. You know, maybe they are entering some data.

Or maybe they're checking some data, there could be all kinds of different parts of it, but, but at the highest level, it's really just about them.

Notifying the system hey, I got this task, and then, letting the system know when the task is complete as well.

Then, the last piece of the puzzle are the bots themselves.

The bots are app, they're installed on end user machines, end user class machines, but I don't want to give the wrong idea, because there are some kinds of automation technologies that are actually running on users' machines, where there are more something that's a, that's a human assist.

And, that's not what we're talking about here, so our bots are sitting on a user class machine, but that machine is dedicated to them, so, that machine, the bots will have access to all of the systems, that it needs to have access to, in order to complete that automation.

Now, the accounts that the bots are using will be specific to the bot, so that you have full traceability. When you look at the audit trail, or you look at those reports, you know, you know, what tasks are done by human, what tasks were done by a bot, A bot. And it's all very clear and clean.

Then, the other box on there saying, that says Smart Bought. This is where all the AI libraries live.

As I said before, like all the other components, the AI libraries are built by us, and don't require any additional licensing. But, we do have those separated out because, in many cases, your automation might not require that advanced functionality.

And, so, we separate this out because it can often make the implementation, as well as the infrastructure requirements, much simpler for more basic automations.

And, if you have any questions about what we mean by that, that's something that we can cover with you in more detail if you have a question on that and want to reach out to us.

Uh, so, let's do it a little bit more deep dive into those AI capabilities.

So, there are a lot of different, I'll call them buzzwords, or, or flavors within artificial intelligence. And, we're just going to touch on a few of those here.

Computer vision is basically giving you're bots or your computer, the ability to recognize dots on the screen and turn them into some kind of meaningful, structured data or text, right?

And, so, the reason why this is important is, in many cases, you're dealing with documents that are coming from various sources that you don't have any control over. And so, you're really just getting those those as images.

And so, um, that same kind of thing can happen with legacy applications as well.

If you're dealing with legacy applications that are just coming through a terminal emulator even though on the screen it shows up as words. As far as a computer knows, it's really just dots on the screen. So computer vision is what can turn those dots on the screen or ink on the page into real meaningful, structured content.

And then there's also natural language processing and predictive analytics. That gives you some other capabilities, like being able to do sentiment analysis, and predictive analysis, text classification, entity extraction, document classification. All of these different things that you might need, especially in the cases of intelligent document processing, which is a very important use case for this kind of technology.

So here we're just going to show some of the good things that some analysts are saying about us.

And I won't spend too much time looking at or talking about this.

But we just like to throw this up so that you know, even though you maybe haven't heard too much about inhibitors as a company and maybe haven't heard too much about our platforms, you can at least have some confidence that we're working with analysts. And they're talking to our customers. And everyone is saying, pretty good things about us.

one of the things that I will point out here is that we are rank well within the RPA space, as well as the IDP or intelligence, document processing space, which is a pretty unique combination for us.

Yeah, we have a bunch of different solution frameworks, which are basically accelerators to get you going down A particular path.

If there's a solution that you're really interested in, this can be an expedited way and sometimes more cost effective way to approach that. So we have some examples of that up on the screen here, but we have many, many more.

And that's, again, something else that we can talk to you about as, as you have an interest in, that, if you want to pose that question to us separately.

So now we're going to take some time and go through some case studies, But before we do that, let me just pause things here for a second, because I got to get things a little bit organized on my side. So I'll be back with you in just a second.

OK, sorry about that.

In the interest of full disclosure, I'm not operating out of my normal office today, so, hello.

I had to quick plug my laptop in before the battery.

OK, so let's go through some case studies.

So for each of these, There's obviously a tremendous amount of detail involved in all of these processes, and these are all things that, uh.

We could go through the details with you.

If you want to take a deep dive, but we're really just going to be looking at the high level here.

Sorry, literal out of breath.

OK, so, this first wonderful, is with a leading drink and brewing company and this is about invoice processing.

So, this is one of those solution areas that we talked about, and we have a pretty good framework created for invoice processing in general, and, if you see the screen at the bottom right there, that would be the vendor portal.

Ben?

This is just kind of an example of how the solution frameworks can be used to get you further down the road.

Then, what you would be able to do without it where, in this case, you have the portal already, basically, pre-built for you where your vendors can come and they can enter any invoices and also track their status over time.

In this particular case, we were supporting two-way and three-way matching as well, and you can see the kind of that resulted 90% reduction in manual effort and, uh, improvement and turnaround time and 50% reduction in full-time employee involvement in the process.

OK.

Next, we have.

For those of you outside of the US, this might be a more familiar concept for, for those of us that are in the US, but they're, in many cases.

For auto manufacturers, they have this, this bonus process that works, between the manufacturer and the dealer, which is something where they get incentives.

If, for example, maybe you're an existing customer of theirs, and you're trading in a car that you had that you bought five years ago, and you're getting a new one.

Or it could even be the same kind of things, but there incentivizing you to trade from one of their competitors cars to one of your cars.

And so, in any case, there's a bunch of data and validation involved in that process for the dealer to get the money from the manufacturer.

And so that's what this process was all about, the dealers.

In this case, we're having to complete these long drawn out processes of being able to validate this data from the customers, so that they would be entitled to get that that rebate money from the manufacturer.

And so we were able to put something in place to automate that, which dealt with a huge number of documents.

And, it got rid of a lot of manual effort, and resulted in a great improvement in turnaround time, and ultimately created a much cleaner pasche for the dealers to be able to get that money back from the manufacturers.

OK, this next one is A document handling process for a logistics company.

Yeah, I would say logistics is in the area where we see this technology in use.

A lot of logistics and supply chain is very, very data heavy and because of that, you know, there, there's a lot of manual work to be done, to reconcile the data from one system to the other.

There's also a lot of proprietary systems out there in this space that don't talk well to each other, and also, yeah.

There's a heavy use of Your ERP is in that space, that, although they can't be implemented with all these other systems, it often, it's very time consuming and expensive to do that.

And, so, we see automation solutions like this.

Especially Intelligent Automation Solutions, being a great solution for, for this kind of problem set.

Because you're able to get the work done much more quickly, and reached receive usually greater benefits, than could, would, then with a direct integration with your ERP.

So, in this particular case, we're talking about 890 hours of savings per month.

And 80% reduction in the human involvement of, of these tasks, But really, no.

You can read what it says on here.

But really, it's all about dealing with all of this data in these different documents and systems. The same kind of thing that we were talking about earlier, where, you know, you have these cases where you're asking people to wade through all of this information and data.

Make something out of it and figure out what to do with it. And those are the kinds of situations where solutions like this are just great to be able to put in place.

So I know.

We're getting to the end of our time here OK, well, let me ask you, Do we have any questions that have come in?

Yes. We have a few that have come in. You want to take some time now? Yeah.

Yeah. Let's take a question or two.

OK, how do you measure the ROI of an IAA, project?

So I'd say there's a lot of intricacies in this, in this answer, depending on your, on your company and the particular project you're talking about.

But the simple thing about most of these kinds of automation is that you're equating what the machine is doing to something that a human had previously been doing.

Even if it was only a part of that person's time.

Or, it could be the part of, of many people's time, or it could be full-time for many people, depending on how big of a process it is.

But because of that, it usually makes it pretty easy to equate the amount of time spent two, the amount of money spent by the company, and then compare after the fact the amount of time spent for the automated version of the process.

And then the difference between those two is the ROI.

So, you know, just taking a simple example, if you have a process where you have a number of invoices coming in, and, it's taking a team of four people full-time to be able to deal with those invoices.

Then, you put in place and automation that does most of the work, but still require some. Some human interaction, maybe to correct things, or track things down, Research things, whatever it might be, but it reduces the amount of humans that are required.

Instead of needing for people to keep up with the volume of work, you only need two people.

Right?

So in that case, you could take the, the money are equivalent of that time spent by those two people and equate that to the savings once you deduct whatever it costs to implement that.

So it's a very this is why these kinds of technologies are being so widely embraced, because it's it's generally very easy to track and create the ROI from these kinds of implementations.

So one thing I would suggest, for any of you that are interested in looking into the ROI in any greater detail, on our website, we do have an ROI calculator, which would let you enter in the parameters for your particular automation project, and it will come back to you with A pretty detailed analysis of what kind of ROI you should expect to see for that process.

So what else do we have one more, Kayla?

Yes. Are there any industry specific or business function specific solutions available?

So there are some industry specific solutions available. I'd say the one that jumps out to me, and I'll spend some time just kind of describing this, even though I know that this isn't going to apply to everyone on the call. But this will kind of give you an idea of what we're talking about. When we talk about these kinds of solutions.

If you have a particular area of interest in your industry, or within your space or your company, reach out to us and ask the question.

And, you know, maybe we already have something there, Or, if not, maybe it's something that we'd be interested in working with you to develop.

But, but a good example of this would be revenue cycle management within healthcare.

So, we see a lot of health care companies struggling with the amount of manual work that is required in order to do things like claim processing, you know, Medicare claim processing.

All all of the codes that are required, and, And all of the paperwork that's required in order to make sure that they're going to not just get back all the money, that they're entitled to, but to get it back in a timely fashion.

And so, there are a lot of different elements to this, Both on the, on the claims processing side, as well as on the initial validation side of this.

one of the things that many healthcare companies, clinics, health care providers are doing, is doing a pre validation or authorization for patients before they provide any services, Just to make sure that's going to be covered by their insurance before it happens, so that everyone knows upfront, so that the patient will know, hey, this isn't going to be covered by their insurance, by your insurance.

And then the healthcare provider does get into this situation, where the service has already been provided, and then no one is paying for it.

So, there's all kinds of scenarios like this within this broad category of revenue cycle Management, where we have built a lot of automations that both accelerate the process for recognizing revenue within the organization, reduce the amount of errors, and also decrease the amount of money that's left on the table. So, you know, one of the things that that can be very interesting about how, how the billing is done in this space is that there are some cases where you can have multiple codes that apply in a given situation.

one will pay out at a certain number and another one will play a payout at a higher number.

And it's just a matter of understanding how that particular patient situation, the details of it, relate to those codes to know when not higher, that higher paying code can be applied and when it can. And these are all the kinds of crazy rules that are very hard for people to keep track of all of them. But when you have A, an intelligence based system that is keeping track of all of this for you, it makes the process a lot more manageable.

So, as I said, this self care revenue cycle management is just one particular case like this, but if you have a particular application within your industry, we'd be happy to talk to you more about that. So, at this point, I think we've already gone over the amount of time that I thought we were going to be spending today. I appreciate your patience and sticking with us.

If you have any additional questions that we haven't already answered, we will try to answer those via e-mail.

And if you have additional questions that you haven't posed yet, feel free to send those to us via e-mail.

And we'd be happy to get any kind of additional information you're looking for or if you want to see a product demo, or are interested in learning more about any of the solutions, or the the platform itself, how it works. You know, we'd be happy to give you those little details. We didn't really have enough time today to go into a demo. And so, you know, if that's something that you want to see live. You know, just let us know, and we're happy to do that for us or for you.

So, again, we appreciate your time today, and we look forward to hearing more from all of you in the future.