Interview by Jonathan Kersting
What happens when a software company that's been around for two decades goes all-in on AI? Rahul Asanikar, co-founder of Benchmark IT, sits down with Jonathan Kersting at the Huntington Bank Studios to unpack the real, measurable ROI behind AI investments — not the hype, but the tools, strategies, and margins that are actually moving the needle.
Rahul shares how Benchmark IT evolved from building websites and mobile apps into a full-stack AI consulting firm helping financial services, healthcare, and product companies build AI-first solutions. He walks through real tools they've shipped — including Laibel, an AI system that runs hundreds of compliance checks on product labels in seconds, and a document extraction platform that reclaimed 80 hours a month for teams buried in paperwork.
Then the conversation goes deeper: the concept of a Company AI Brain — a system that ingests every meeting, email, project schedule, and public data point, then surfaces threats and opportunities before anyone asks. Rahul shares a story where the AI brain flagged a parent company's ERP consolidation initiative — a threat that could have cost them a client, but instead opened the door to five new contracts. He also breaks down how they use AI to generate 100,000 personalized outreach emails by researching each company's specific history — including product recalls — at a level that makes prospects ask, "How did you know this?"
We also cover why AI resistance fades when you give teams time to experiment, why Jensen Huang telling programmers to stop programming isn't crazy, and the one thing that hasn't changed in 21 years of business: trust.
Key Topics Covered:
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Transcript:
[00:00:00] This can be done at scale, right? Exactly, right. You can do this 100,000 companies and then have 100,000 personalized emails and that's where the, the fun part is. So- ... this, this brain can really correlate lots of these data points which ourselves, uh- You guys keep your brain in a jar there in the office?
This is Tech ?? Pittsburgh, and I'm Jonathan Kersting with the Pittsburgh Technology Council, and this is your front-row seat to all things around Pittsburgh's technology and innovation ecosystem. And it is just always a joy when I get to hang out with my members here at the Pittsburgh Tech Council, 'cause they're just working on some of the most incredible things out there today.
Every discussion I have, w- we always lead into some sort of talk with AI. We're gonna have a little bit of AI talk today , but we might go deep on a couple things that I'm particularly excited about, and that's really finding some ROI around your AI investments and your tools [00:01:00] and so forth.
And if there's someone that knows a little bit about that, of course, is Rahul Asanikar from Benchmark IT. So Rahul, it's great to have you hanging out with me in the Huntington Bank Studios today because before we hit record, I always love talking to my guests, and you had some fantastic stories. I was like, "Man, we gotta lead off with some of this stuff," ' and first and foremost for me is your journey to Pittsburgh, because at the Tech Council, we want people from around the world to come to Pittsburgh and build great companies like what you're doing with Benchmark IT.
And what brought you to Pittsburgh is very unique, and I think it'd be a fun way to learn a, a little about you and Benchmark IT- Sure ... and what brought you here to Pittsburgh for crying out loud. Yeah. First of all, thank you very much Jonathan for having me here. And I'm, I'm- I've been coming to Pittsburgh for almost 13 years now.
But thrilled to be a Pittsburgher now. Yes, you are. So yeah that one question definitely pops up every time I say I just m- I moved here [00:02:00] Right about two, two years ago- Okay ... a little over two years ago. Nice. And the first question is, why Pittsburgh? Yeah. And that why- ... is why the hell you are here.
Absolutely. It's not, it's never "Oh, really?" "Why did you choose Pittsburgh," right? But jokes apart yeah, so we have, as a company, started about 21 years ago we were in New York. Then we moved to Florida. Florida. And, Okay. ... and I was one of the co-founders, but then we ended up move- our headquarter came to Pittsburgh and it's a funny story.
One of the guys from Pittsburgh who is a, a friend now, and he found us on the internet- He was looking for some- ... on one of- He was looking for some IT service, some IT help he was looking for IT help, and he found on one of the portals back then in 2011 or '12, and we pitched him.
We did some very small stuff, a few hundred dollars probably. Really? Oh my goodness. And one after the other [00:03:00] we... it was a snowball effect. We did well and yeah, I think in 2014 we got back then one of our largest contracts, a few hu- few hundred thousand dollars worth, ... and that was a Pittsburgh based, And a Pittsburgh company
company. You were slowly growing all this Pittsburgh business. It's wait a second. Maybe it makes sense to be here. Yeah. So that's really started in 2014, being that one of the largest contracts back then. That's awesome. I love hearing that. And then it was a snowball effect. So we ended up having seven, eight customers here over the years, and- Awesome
when I was gonna move which city was gonna be, of course, naturally, the Pittsburgh was natural choice. In fact that's when we decided to come here. I was originally gonna move to New Jersey. Oh my gosh. And then, Don't say it, Rahul. Don't say it. You made a good choice. Yeah. Yeah. But at the same time, Our daughter ended up going to a school here, and now she's in Pitt.
Awesome. But at the same time we [00:04:00] have amazing friends- Yeah ... who happen to be clients. Perfect. In Pittsburgh, and there are several of those, and they also are one of the reasons why. Amazing. We're glad you're here, man. Thank you. Simple as that, 'cause we, like I said, we want more folks from around the world coming here- Right
to build companies. And what Benchmark is doing is some pretty impressive work. Give us the elevator pitch for all the different kind of things that Benchmark IT does. And then- Yeah ... we're gonna start jumping into some of the cool technology you have, the problems you solve, your thoughts and inputs around some crazy cool AI stuff.
So yeah. Sure. Elevator pitch. We're going to the 10th floor. Sure. That, that's a long time. But yes. So Benchmark is a software company which helps the client build software products. So we provide software product engineering services to companies in financial services, healthcare, and sometimes any other industry as well.
Those sound like some very good Pittsburgh verticals right there. We've [00:05:00] got some- ... great financial institutions and some amazing healthcare here. Yep ... sounds like a good place for you guys to be. Yeah, we do have lot- some financial services company, a taxation software couple of healthcare product companies are co- are customers.
Nice. And that's what we have been doing for 21 years now. I like that. Yeah. For t- 21 years. Yeah. Just, a couple decades. That's... Honestly when you say that, I just find that really amazing- Yeah ... because in the fast-paced world of tech, when a company goes for two decades, you're doing something right.
I've seen companies that can kinda fake it for a few years, and eventually physics will catch up to them. But obviously, when you're in business for that long you're doing right by your customers. You're building software that works.
Yes, of course. Not only it works but we have clients who have been with us for 20 years. Okay. And of course, naturally, not only the software has to work- ... but it has to evolve over a period of time. So we have... Our clients have seen all these technologies come and go.
Exactly. Whether [00:06:00] it's web, mobile- ... whatever new stuff keeps coming up. It's funny when you say that 'cause you really think about it was, "Hey, are we doing business on the web?" Yeah." "How 'bout mobile?" "What? Using your phone? Yes." Sure. It just keeps moving, and it's just, it's always this- Yeah
it's kinda fun to see the cake build. Yeah, so tha- that's really has been important to evolve with the clients and ensure- That they don't look out for other partners because the one which they have is doing job, is able to grow with them- Yeah ... evolve over a period of time. So that's where- I feel yeah, if you had some customers you've been hanging out with for two decades, you're literally like, you're like their backup band at this point.
Like you're like part- ... of the team, but you're just not at the office every day. That- that's a very good point. And when we think about all these new trends which keep coming up and being around for 21 years more important is really to find out why the clients have been s- still continuing to work with us.
To bring a [00:07:00] different point is that what has not changed- Okay. ... since last 21 years- I love when you hear that- ... 'cause that, that's inter- 'cause so much has changed. But what has not? Answer that question you just posed. Yeah. And that's relevant when t- three years ago, or this question- has been popping us every few years. Why do the clients wanna work with us? And what has not really changed is that clients wanna work with a partner who they can trust. Especially in Pittsburgh. When people do right by people in Pittsburgh, they tend to stick with them, which is a good thing.
So yeah, so sticking to a partner is about trust, about reliability, right? And every client relationship has some downs and ups and- There's, it's life. Yeah, 100%. And then how do you respond as a company- Yes ... as a team? That really results in having a long-term relationship, right?
So we have cl- have had challenges and overcome those and really what has not changed is the trust of the customers, [00:08:00] right? And that stays true before AI, after AI. That is c- not gonna change. So when the mobile technology came up or whether- three, four years ago, generative AI has popped up.
We have evolved ourselves and morphed into, ... an AI consulting company- Absolutely ... along with building the software as well. So- Yeah. Yeah, you're following the trends as to what's building the software and- ... last time I checked, AI has been probably been one of the biggest trends you've seen come through- Right
in, since web. ... I think in so many ways. Since since thousands of years probably, but- Yeah ... but true. That's where things have not changed in one way and things have changed- ... in the other. Interesting. I like hearing that. Yeah ... so yes. We continue to work with the same customers before AI, after AI, and hopefully whatever next, next-
stuff comes along. I love that. That that, that's so cool. And obviously, the big thing to talk about today is, of course, the technology you're deploying in order to make AI happen for your customers, to make it something that is [00:09:00] of business value. It's not just this feature or this thing that's like, "Hey, we're working on AI," but the whole fact of wow, this is a powerful business tool that's helping them achieve a goal or margin that they're looking for, and not just by a little bit.
You guys go big. It's not about these little increments. It's about 10X types of changes and so forth. And so much of what you do, obviously, is around some of the key the key product and services that you guys have, of course, at Benchmark IT. And it's really around this whole thing of being like, like a full stack of AI.
It's not just this one thing you're gonna do, but really it's the full solution am I putting that correctly? Yeah. Yeah, it's interesting that you use the term full stack, and- It makes me sound cool when I say that. Full stack, man. Yeah. That's a very engineering term, where you have full stack engineers- ... who work on the front end, the back end as well. But that recently is really a trend which I can see not just with Silicon Valley, but our customers as well- Yeah ... is full stack AI companies or full stack approach in building [00:10:00] AI- first company. And when I talk about it for example instead of selling... And we work with lots of product companies- Yes ... to build their products. And one of the trend I can see, and we are work- helping some clients is, instead of selling the software to the law firms, why don't you provide the services- Which the law firms provide yourself rather than- Bringing that in.
Yeah, absolutely ... and lots of companies are doing it in a AI first way, and traditionally these companies would not do that thinking that they're a product company and their valuations are gonna be higher- Okay ... by being a product company. But now with AI, if you're able to have the services which are Significantly better, let's call it 10X better.
I like that. And you're able to provide those 10X faster. Then you can enjoy product kind of margins as a company. Yeah that, that's what brings the margins right there. Yeah. When you got [00:11:00] the speed and the quality going- ... on at that level of improvement, then it's wait a second, this whole new world starts opening up as to how you actually look at your business and how it's gonna- Right
provide services. Exactly. And the, there's another challenge is that in the AI adoption itself, right? If you build something, an AI first experience, then in helping or instead of trying to enforce these new tools to the customers why don't you use those in-house and provide these services?
And you can iterate on these things better so your product with AI- Yeah ... is better much faster, rather than- And absolutely ... educating thousands of users to use your AI first approach of using the software. You might as well build it and use it in-house and be a law firm, be an accounting firm, and be a any- anything you do- Absolutely.
Yeah ... be a service or some- Yeah ... that's the full stack and it's in- Exactly ... it's interesting that you say that. Nah, I love it. And so this gets me thinking when you said this when you said the [00:12:00] words like AI first, I feel like every project has been like, there's been this technology going on, and then they're tacking AI onto it in order to take it to this next level.
But now the game's gonna be changing 'cause you're gonna be using AI first to develop these things. So it flips it around, and I think it's gonna make it even more powerful. And it's not just tacking it on at the end 'cause this is what's been going on, but now all new tools are being developed with AI front and center driving it.
E- exactly. So not only the cost of building the product- Yeah ... is crashing 10X or 100X. Okay. But the, y- you can build things faster. So- Yeah ... the, the real question is then what's the moat, and- ... and are you able to have that speed as a company and- ... and then ultimately provide that value faster, cheaper, and better?
And all of these things were more of you can have one or the other- ... but you can now [00:13:00] have- Yeah ... these faster you can provide those cheaper because you can deliver those faster. And then it's the s- it's a snowball or a flywheel, which just keeps spinning. Just, so it's an amazing time to be around.
And I mean- for, you gotta be having so much fun ... because literally, I feel like it's, I don't know if the word renaissance is quite the right word, but it's like this- expansion of what we can do with tech- ... with what's happening with AI. So for someone that just likes, 'cause you're a tech guy at heart, right?
I mean- Yeah ... you love the code, right? Yeah. And the idea that you can just start doing so much more has just gotta be very exciting for you. Plus the fact that you can see more powerful solutions being built for your customer. You're wowing your customers, right? They're like, "Oh my God, you built this amazing thing."
And you're like, "Yeah, I did. No, the it's a magic show- Yeah. ... in all these conversations. Yeah. Not just with the customers, but everybody I speak with. Absolutely. So yeah, so I think the, just to touch base on what we talked about, what has not changed, right? [00:14:00] Yeah.
Yeah. Keep on that as well too. Yeah. The, the traditional when traditional ways of evaluating ideas- ... whether it's the traditional ROI, it hasn't changed. Where- ... when we talk to the clients and of course we come up with the ideas by brainstorming with the customers, and lots of times these these ideas are we can come up with 20 ideas and probably two of those are really good.
But the 18 are something which we collaborate with the clients and throw that away, throw those away. Yeah. And that's really that what, what has not changed. So traditional metrics around the return on investment, what are the, what is the definition of success? I'm glad you say that- Yeah
'cause yeah, these are the core things that you know that just drive real value at the end of the day. And that's not changing because there's some whiz bang around what's happening with- ... AI or something spectacular, but like the idea that no, this stuff still has to be in place.
So that has not changed. That has not changed. Yeah. So [00:15:00] it's the success metrics. If this is successful, what, what will happen? How do you measure those success criteria? And what if you are able to define those well ahead of time then the conversations on the ROI is practical. And then lots of ideas in a way are not even relevant.
And that's where we when we work with the clients, we come up with 20 ideas and start working on just one or two. So it's more important to- There's a lot going on the scrap pile there to get to the good stuff. So the job is to kill ideas- Exactly ... not just to come up with those. So what I find interesting is, with how fast AI has moved, some of us have used it for certain things and we've had some bad experiences or, if our expectations weren't what we thought they were, so we think that I'm not gonna try that again."
Your mindset is like, "No," and my mindset is too, is that no, the technology just keeps getting better, it keeps evolving. What is some of the resistance around AI? I just some people can almost been like shortchanged by it, but you realize no [00:16:00] it's, you gotta keep at it.
Don't, this, 'cause this isn't going away. Yeah, so the resistance has been it depends on whom. So when we talk about the customers, we have seen a lot of these things did not, these AI tools did not work- ... a few months ago and people have thought, "Okay it's still not good enough," and then probably they have not revisited those tools and see- what has changed. Yeah, 100%. And the rate at which these things change is phenomenal, right? And That's one thing, right? You might have tried something and hasn't worked. So for example, in, in coding internally last December was the time when things really changed, right? And so whoever was working on coding, whether these are engineers- in our company or in our customers who have their own in-house engineers- ... they themselves also we have seen that, okay, it's not good enough. It makes mistakes. And it does. Of [00:17:00] course, yeah. But just wait for a few months. Exactly. Yeah. So that's the answer. So that's where the resistance traditionally comes from.
The also there are some challenges that I, we have seen that we need to carve out some time to do the experimentation, so a lot of times people just don't have the time. Never thought about that. It being able to have the ability to carve out some time to actually experiment- ... and try to break it a little bit, until you can break it on in your own little sandbox- Right
as opposed to the customer sandbox. Yeah. So yeah. So lot of these c- curious minds need some time to experiment and find out its limitations. So once once our team members or people have that time then they, we have seen that resistance go away, right? And of course the collaboration among the team members where, "Oh, have you seen this?
Have you seen that?" And those kind of things also help if realize what are the possibilities- Yeah ... because it's such a generalized technology, somebody [00:18:00] can use the same thing and have a 10X, 100X experience. Somebody can just draft a better email. Yeah. And the same thing, right? I like good emails.
So- Very good for me. So you can have the experience which is completely different- Exactly. No it's very true ... same chat box. Yeah, it is. It's different. Yeah, and some people are able to just- stretch it to s- the limits where they're like 100 times more productive- and some people are just able to draft a better email-
which is amazing. But the expectations of the customers are different- customers are reading these news- ... where Jensen Huang is saying, "I want my programmers to stop programming." Yes. It's ki- and Isn't that crazy when you hear someone like Jensen say that? You're like, "What are you talking about?"
And then, then- So I can work in Nvidia now? Yeah. And then our customers talk to us and, "Okay, when is the Benchmark team gonna that, that's that's, in, in a way it, it is supposed to happen. But that's the pressure which [00:19:00] also- I see.
It's a lot ... it's hard to- It's crazy ... deal with, right? I'm wondering if you could walk me through like some of your tools that you use at Benchmark, and maybe how you use them with a customer. I always love kinda seeing how you've actually helped someone solve a problem and how you're able to do that.
Is that something you can kinda walk me through? Yeah. So some of the tools we have built for our clients are, so for example I'll take an example of our, one of our solutions called Laibel. L-A-I-B-E-L. It's a funny name to have that. So we have all these products, for example, any food product has a label, right?
And apart from label, it has a design, which is an artwork. So lots of these companies come up with different designs throughout the year of the same product at times. Yeah. Absolutely. And when these designs are going through that approval process internally there are three or four different kinds of checks which the team goes through.
I see. The, the artwork goes through. [00:20:00] Marketing checks regulatory compliance- ... and then design checks. Yeah, standards- And, and- ... and brand adherence and all that kind of good stuff. Yeah. And you can have a, a simple product which is a water bottle can have hundreds of checks- Amazing
which users, people have to go through. Yeah, of- yeah, that's crazy when you think about that, but yes, that, that's part of the business. And how cumbersome would that be if a, a designer has to change the logo and maybe the address. But- ... sometimes something else gets changed. And the, the impact of that is if the product is if it's a food product- Okay
and there is a mistaken ingredient- Yeah, ... then not only it's it actually results into product recalls- there's liability there ... but also there are law- lawsuits, right? Yeah. So the solution we ended up building for one of the largest companies in the world is AI, which basically does those hundreds of checks in a matter of few seconds.
Oh, wow. Okay. Saving time of course, but beyond [00:21:00] that - avoiding the risk of having the lawsuits ultimately- Exactly ... avoiding those lawsuits. So these use cases probably not probably, these use cases never existed. If AI is able to check the fonts, check the layout check the spelling mistakes, of course, that would've happened pre-AI as well.
Check visually barcode, whether it exists or doesn't exist. And lots of these things if you're actually having two different artworks, it just compares and finds mistakes. Of ingredient has a different meaning. It is wrapped to the next line and so on and so forth. So h- dozens and hundreds of these checks could be done- In m- in a matter of minutes, which otherwise it's very difficult for a human to keep doing that all day long That's monotony right there is what that would be It's fatigue, it's frustration.
Nobody wants to do this. No one to do it. Exactly. And so that's one of the use cases, right? That's a really cool thing where you think, first off, I can see how you're getting ROI out of that. As a company- Yeah ... you're [00:22:00] being like, "Wow," "I'm putting my employees to better use," doing- Right
other things, knowing that you've, you're gonna avoid the lawsuits, that things are gonna be done right. I can see lots of ROI happening there. Yeah, so that's one thing. Yeah. The other thing is completely mundane tasks. You have documents which, say, tax preparation is happening and- and you have hundreds of pages for estate tax or you're going through a property transaction and you're trying to understand what data is inside those property transactions property documents. And extracting that data, making sense of that and applying some rules- Yeah ... as simple as entering that data into the software it generally takes hours of...
In, in, in about 160 hours a f- month, we've seen some people spend almost half month, half of the month or 80 hours a month. 80 hours. Oh my God. Just looking at the documents. Just looking, oh my goodness. Looking at the documents, entering the data. Yeah. [00:23:00] And they're not really looking at- What is the objective, right?
Yeah. Objective is to- Yeah. ... Understand whether these implications of- ... these documents, what's the impact on the tax? How do we z- do things better? Are we missing any advice to the customer? So these solutions, what we build is basically allows the users to extract the data, evaluate, identify any mistakes across these documents, and ultimately help the user do that job faster so they can work- Yeah
with the customers more than just entering data. Going through papers and, ugh, yeah. That's phew. Count me out on that. But that's, once again, goes to show you where you can take care of the monotonous- ... and add some serious ROI. This is a fascinating conversation where I get to learn some of these insights on what's changed- Yeah
what hasn't changed, and the best uses- ... of AI and looking at learning more about Benchmark and what you've built for some of your customers. One, one more thing I just- wanted to talk to you about. What [00:24:00] we've seen is in recently is something called- Building a company AI brain. Ah, yes. So- Okay ... have you heard about this concept? Yeah. We were, we were loosely talking about this- and I'm like, I'm glad you brought this up. Very cool. Let's pull on this thread a little bit. But- Yeah ... we all have this information, right? Everybody is recording most of the meetings now. So imagine all the data, all the meetings which are, we're having with the customers- ... we're having internally within the teams all the emails all the documents- the project when they're- Yes ... building those. Project schedules and any publicly available information about the customer's customers. Imagine all of this information is collected and and stored somewhere. Yeah. And then AI is basically having not only access to the information, but having different lenses in which you can- see that information. Yeah. So imagine having s- the [00:25:00] CEO has defined the priorities of the company. In our case, the customer may have their priorities. And we have our own priorities ev- at every layer, whether it's our COO project manager, everybody- Yeah. No, absolutely ... who's working on it- Yeah, every...
Yeah, everyone has- ... have different lens ... every- everyone has their tool set a different way. So it's, we're gonna look at this a different way. Yeah. And then you give all this data and you define these objectives, and then amazing insights come out. So for example one of our clients I'll talk about we realized that their parent company announced an initiative to consolidate their ERPs into one.
Okay. And we were, we have built their ERP one, in one of their brands. Okay. Yeah. One out of the five brands the parent company holds. We've been working with them for 14 years. Now, that information was publicly available. Our engineers saw a request coming from their [00:26:00] team and say, "Okay, do you have access?
Can we access the API data through APIs and whatnot?" And this was flagged by our company brain that have you looked at this initiative of the parent company of client which is consolidating the ERP? Now there is a threat and opportunity for Benchmark- Yeah, absolutely ... that either they'll go with somebody else and you might lose the client, or you talk to your client so that you can talk to the parent company- And say, "Look."
And get the business of all five brands. There you go. So- I like where this is going now. Okay. So that's exciting. So these interesting correlations is something which AI can come up with. And I'll give you another example. When we approach the, the potential customers when we do the research about them, sometimes the research is so specific, right?
So I'll give example. I talked about this product label, [00:27:00] right? Yes. So imagine I'm reaching out to a company, X, who had a product recall in 2000- ... 19. Yeah, you can say, "Remember that? We can help avoid- Yeah, ... we can help you avoid that." Yeah, exactly. So we can actually say in the email that you had a product recall in 2022 and our software can avoid that.
Would you be interested? And then if we mention these product names and the year- ... and the month and what the problem was- ... the research is so specific- ... that the people are just blown away. Yeah "How'd you know this?" But this can be done at scale, right? Exactly. You can do this- ... for 100,000 companies and then have 100,000 personalized emails, and that's where the, the fun part is.
So- ... this, this brain can really correlate lots of these data points which ourselves, Do you guys keep your brain- ... surprise ... in a jar there in the office? Yeah. [00:28:00] Yeah we... it's active all the time. So- There you go. So these are some- Yeah ... fun things which, which- That's amazing ... we can build. It goes to show you the power of how this can help you- yeah
grow a business- ... and how there's this, there's data everywhere. It's being collected. And if you can feed that into the brain, for lack of a better term- yeah ... then it can- Yeah ... give you actionable insights. Exactly. So these- Yeah ... these amazing insight, even if it comes up with 20 ideas and 18 of those are not that great, two of those could really make a huge difference in your- Heck, if it's one.
If it's one, if it increases your top line and- Exactly ... increases your bottom line that's good enough. Amazing. So that's really the brain part of it. So you ha- we have to just give this data to the, the AI- ... and then ask the right questions and get those amazing insights. So that's what the- It's amazing.
Yeah. That, see, fascinating conversation all the way around. How much fun. Can't thank you enough for stopping by the Huntington Bank Studios here, tell a little bit of your story. That's just amazing. This is why you're making Pittsburgh proud, simple as [00:29:00] that. I must say, we're always stoked- Oh ... to have you stop by here on Tech Five- It's it is
Rebel. You are the best. Thank you, Jonathan. Thank you so much for inviting me on this podcast, and it's been an great experience. Awesome, man. Thank you. I'm glad you enjoyed it 'cause I definitely enjoyed it, too. I know you out there have to have enjoyed it, right? Come on. If you want more content like this, keep on coming back.
We have so many of these stories. We cannot stop telling them. And once again, this has been Jonathan Kersting with the Pittsburgh Technology Council, and of course, here with Tech Five, and I really look forward to seeing you on the next one, everybody