In our video health data series, "Leaders in Leveraging Health Data", we chat with Ali Chaudhry, Chief Strategy Officer at Openbots. 

Reducing the workload of the practice through RPA (Robotic Process Automation).

Discover how to scale up RPA in your organization to decrease processing time by 70%. If manual labor is automated, you can reduce costs and enhance employee satisfaction. Through their zero-license pricing model, Openbots enables users to reduce manual effort in a cost-efficient manner.



Openbots with Ali Chaudhry: Reduce Practice Burden with Robotic Process Automation

Ryan Carlson: Today, we're here with Ali Chaudhry from Open Bots and he's the Chief Security Officer. And so Ali, thank you so much for being here. 

Ali Chaudhry: Nice to be here, Ryan. Thanks for having me. 

Ryan Carlson: So OpenBots, what do you do? 

Ali Chaudhry: Yeah. Open Bots is the world's most flexible enterprise RPA platform. RPA stands for robotic process automation.


Ali Chaudhry: It's basically a platform where you can go in and create bots or digital workers to help with a lot of the repetitive and manual tasks that happen across the organization.

Ryan Carlson: So give me an example of who your customer would be..

Ali Chaudhry: So our customers in the healthcare space, it's going to be, you know, both on the payer and the provider side. On the provider side, the areas that we really kind of help with. In health care, there's so many disparate systems, right? And there's a lot of manual work that has to get done on top of those, for sure. Right. It's not API friendly if you will. And so I think where we come in is things like interoperability, right? Extracting data. Once you have extracted data, you can pull from the different systems.

The bots can be trained to pull it out, process it, put it back into a different system. Create reporting. There's revenue cycle management. So a lot of these are very, people intensive type of task, and that's where the bots really kind of, you know, you can program them. And what they're essentially doing is they're decreasing processing times by about 70 percent.

And they're eliminating 100% of the errors because they're bots following a set of rules, as opposed to people manually going through the sequence. 

Ryan Carlson: Yeah. I always think about the old manufacturing pick lines for assembly. Yeah. And then once it went to the robots moving the arms they're exacting. Right. 

Ali Chaudhry: So that's right. The first wave of robotic automation was on the manufacturing and industrial floor. Right. This is now the more office friendly automation.

Ryan Carlson: As far as amongst your customers. I want to talk a little bit about like the, the actual challenge. If you could help bring me down to who, who in the office will welcome their new digital worker overlords. I mean, companions, I mean, yeah, that's right. 

Ali Chaudhry: They're friendly. They're all friendly. But I would say that it's going to be very heavy in two areas. One is on the finance side, anyone who's kind of in charge of, you know, the billing, whether it's work around the coding, right. Inputting data into the systems for reimbursements, doing up for reimbursement. These are areas where the bots can really provide a lot of assistance. And then also there's, you know, the data from the different EHR and EMR, right. And there's reporting that needs to get right. So it's, I think helpful that it reduces the burden from the team and creates more consistent consistency in terms of generating reports for management as well. And for the consumption of that data. 

Ryan Carlson: So what I'm hearing is that, because imagine this in healthcare. Systems, don't naturally talk to one another. Yeah, there is the, I go into one system. Log in, pull some information and then I put it into another piece of software. Right. And that's the human portion.

And so your digital worker is given the same access as if they were a person at a workstation go into this field, copy paste, move into this. Is that, that simple? 

Ali Chaudhry: Yeah, that's exactly it. I think, you know, when we say there you go, you figured it out in 10 seconds. When we say digital employee, I think you encapsulated it right.

It's almost as if they have a virtual machine where you provide credentials, just like you would to your employee, they can use those credentials to log in, follow a set of rules, right? Whatever those rules are, whether it's logged into system one, manipulate the data in this fashion or that fashion, put the data in the system too, create a report, email the report, all of those are very manual, repetitive rules-based steps.

And so as long as you have a set of rules,the bots can be trained to follow that. And they run on virtual machines, just like an employee would have a laptop or a desktop, and they use credentials that your company gives them. It's the same thing. They piggyback on your internal security infrastructure, just like another employee only digital.

Ryan Carlson: And what I have to imagine is interesting as given how many people are doing remote computer work. This is probably going to be a by and large, a fairly transparent process. It's just one less confusing phone call. 

Ali Chaudhry: Yeah, that's right. That's right. And I think the best way to think about it is it's moving everybody up the value chain, right?

If you take the average employee in almost any department, whether it's finance, marketing operations. 30% of their time is spent doing some sort of repetitive grunt work, right. Things that you don't love to do, but you have to do. And so if you can offload that to the bots, then the rest of that time can get reinvested into more customer facing, you know, management facing subjective type of work, which ultimately leads to more employee satisfaction as well. Right? Because now you're doing the more interesting thought provoking work and all the repetitive manual stuff is offloaded to these bots.

Ryan Carlson: You know, I've seen the whole internet of things in the industrial side, you know, the industry 4.0. And, and there was all of this fear of, oh no, we're going to have these virtual machines that are taking people's jobs that are actually to your point. That's never actually the case. It's helping people focus where human judgment is required, wherever our relationship is required. And so it is just offloading some of the drudgery that really is passe. It's not a style. 

Ali Chaudhry: Yeah. And that's right. I mean, I think there is like that, you know, fear of, oh, the robots going to come in and do this. So they're basically assistance to do the grunt work for you. So you can focus on what humans should be doing. But yeah, more thought provoking. 

Ryan Carlson: So tell me, what is it about OpenBots that uniquely qualifies you and open bots to solve this problem? What's your special sauce or yeah, thing that you really are proud of? 

Ali Chaudhry: Yeah. So RPA has been very hot in the fortune 1000 space in terms of, you know, um, the move towards digital transformation. The issue is, you know, in the beginning it was, um, the promise was that you'd have hundreds of bots across every organization.

And it never actually happened. It never scaled, right? The reason is the existing vendors charge, you know, up to 10, $12,000 per bot. And as you get to 10 bots, 50 bots, a hundred bots, that cost is not really scalable. Right. It's actually the efficiency you're supposed to get from automation is taken out.

 Open bots is actually, um, zero license platform. So any automations that you run on prem, whether it's on your infrastructure, on the cloud. It's zero licensed. So you could create a thousand bots and it's zero license. So our mission was more about scalability so that you could spend less on renting the technology and spend more on building more bots and more automations and driving efficiency.

Ryan Carlson: What I find fascinating is how many times just changing the pricing structure, the business model gets some of the human, emotional elements out, right? Like a pricing structure that charges per bot puts a barrier in the way of actually fulfilling the promise, right? Yeah. More bots equals more. Time-savings right. You'd think, oh, it's a cost benefit. We're just a cheaper, lower cost. of human worker when, when that's not the case, right? What your licensing is? The automation not. Task. 

Ali Chaudhry: Yeah, that's right. You license the actual automation under the current models. By removing that friction, it allows, allows companies to go deeper into each organ, each division to say, what are the different tasks that I want to automate?

And when you don't have that friction of per bot licensing, you can go through and automate a lot more and truly gain the efficiency. Right? So if you take cost savings, but then you're redistributing that money towards licensing, it's kind of. a wash. So we designed our model more around scalability.

 We, you know, have a support based model with some cloud solutions that are optional add ons to help you get the most out of the platform. But net net it's about an 85 to 90% savings relative to the current commercial models out there. So it's, it's redistributing that expense towards building more automations.

Ryan Carlson: That's awesome. So tell me about the training process. I know machine learning models, you know, are you feeding them, like, your bots, are they learning how to optimize on their own or is it really just a rigid micromanaged employee that don't stray from the path? Right. I'm curious. 

Ali Chaudhry: Yeah. So I would say it's a mix of both the core bots themselves are rules-based.

Now you can program the rules to get more complex. So if option A, execute steps one through 10, if option B use steps 11 through 20. So the rules can be added to create complexity, but the bots themselves are rules-based. And then we have another component on document processing where we have machine learning, so you can build templates and the more data you feed through there, it starts to learn those templates get smarter at identifying and, you know, so that's where the machine learning comes in, is more in the intelligence document processing side. 

Ryan Carlson: Is that kind of like how Google spreadsheets every once in a while ago, Hey, you didn't ask for this data, but would this be interesting to you? I mean, is it, is it something along those lines 

Ali Chaudhry: It's in a similar vein it's um, you know, it's basically the more data that passes through the machine starts to recognize and get better with the pattern.

Right? So for example, if you kept feeding images of trees through and showed hundreds of different trees, It's going to start to get smarter and recognize many different variances. Right. And it won't trip up as much. So that's where machine learning comes in is the more it sees the better it's record, the more accurate it becomes.

And then it gets rid of a lot of those exceptions and it becomes a more intelligent process. 

Ryan Carlson: So in this training process, is there a human in the loop component or it, you go through kind of like your Instacart order, right? Yeah, that's a, that's a substitute that I would accept, you know, that's a good substitute. 

Ali Chaudhry: So I would say the human in this process is more about framing the model, right? What does the template look like? So it's structuring it and then you want to look at it. You want to constantly be, and this was in the, um, it's in the machine learning AI sessions yesterday, and this was a hot topic.

The AI is there to become more intelligent, but without human configuration and setting the models and setting the rules. The AI is not very helpful, right? So you've got to, you know, narrow the scope of what is the problem you're trying to solve. Create the models, monitor the progress, tweak things in your model.

And over time, if you follow those components, you'll have an incredibly intelligent machine learning process. That's going to reduce the, you know, inaccuracies in the work. 

Ryan Carlson: Say for instance, I wanted to hire an entire army of digital workers to automate some nefarious. Well, I mean, very legitimate plot, a plan project.

Yeah, we'll go with that. So I may not have the skills to teach these bots what to do, build these models. What does that look like for, you know, a hospital or a practice? Do they need a specialist? Is that something that you provide, you do matchmaking I'd like to hear a little bit about this. 

Ali Chaudhry: That's a good question. And I think, um, that's, you know, our Open Bots itself is the platform that enables the creation of these digital workers, but to actually create them, you need someone with basic development skills, right. It could be a little bit of citizen development, but also they need some, you know, knowledge of like rules-based.

Um, but we actually have a network, a global network of implementation partners who specialize in developing these robots and they're certified on Open Bots. So while OpenBots has programs to help you get started with your first couple of bots, as soon as you need to scale, we have an entire network of, um, very high end.

 The cost structure can also be kind of managed. We have some that are on-shore in different countries, so you can kind of pick your geography, pick your cost structure. And we'll partner you up with the right company to help you deliver those solutions. So from a business standpoint, you don't need to have in-house development resources.

We can easily set you up with the right resources and get you digital employees up and running pretty quickly. 

Ryan Carlson: Sounds just like anytime you buy a, you know, a CRM or a, uh, you know, marketing automation or any of these tools were out of the box, it's really not fit for how your business operates. So you usually bring someone in to configure it and build it.

So it's a similar business service model. With a bunch of parts of partners.

Ali Chaudhry: You're right. Yeah. Just like Salesforce might have a whole universe of consultants who help you build out the complex logic. Um, we have clients who have in-house developers and they take it on prem build, you know, hundreds of bots, no zero license.

And then we have the other end of the spectrum, which is like, we love automation. We want to do it, but we don't have the bandwidth or the team. And so we'll help them build their first few bots. And then we'll pull in partners to build, you know, go from bot 10 to a hundred. 

Ryan Carlson: What is the one thing that people kind of walk away or they kind of have that double-take or they lean into the conversation? Like, what is the thing about OpenBots? Where like, wait, wait, wait, you just said what? Yeah. 

What's the big light bulb moment. 

Ali Chaudhry: I think it's the fact that you can cut your processing times by 70%. You eliminate errors and you're doing it all on a platform that does not charge per bot. Right. So yeah, you truly can build a lot of automation achieve the digital transformation.

 And there's just a lot more efficiency right? And so I think it's the two folds, it's the execution. What the value is back to your company. And then the kicker is the revenue model that we have is very customer friendly. 

Ryan Carlson: I think what you've got as a platform for building a capability for digital automation.

Ali Chaudhry: Yeah. Right. I, I am shocked Ryan, that you actually picked up on that so quickly. We actually view ourselves as a disruptor in the industry because we are positioning open bots more as an operating system for automation. So if you think about what Amazon did for retail, right? You could be an, a average retailer and have a globally e-commerce business, right?

 Almost overnight because they handle all of the infrastructure. We're doing the same for automation where we've got the platform that allows corporates companies to build. You've got implementation partners who can build their entire managed services, businesses on it. And you have platform companies like Healthjump that can create a layer of automation, extensions that they can offer to their customers for that last mile.

Ryan Carlson: That's awesome. 

So thank you for talking all about, digital workers and automation. This has been really great. So thanks for sharing your story and, where can people learn more about OpenBots.

Ali Chaudhry: They can learn more about open bots on our website. It's Um, and I want to say, you know, it's incredibly impressive what Healthjump has built in terms of, you know, solving the interoperability problem.

The fact that you can pull that much data across, you know, 150 plus systems, it's very incredible. So, I think layering the bots on top of that is just a match made in heaven. 

Ryan Carlson: I love to hear that. So thank you so much. 

Ali Chaudhry: Okay. Thanks so much, Ryan.

New call-to-action