From Billable Hours to Business Outcomes: How AI Is Rewriting the Rules of IT Consulting

Speaker A: With AI, we were all drivers. Right now we have access to an F1 car. If you think about it, it's cool.

Speaker B: Sounds dangerous.

Speaker A: You can go really fast, but it's dangerous. Someone still has to check the tires. Are they warmed up? Are you using the right gasoline and all that? Just because you can get into one, you're not going to get in. Oh, um, we're going to have a race. No. Normal businesses do not act that way because you can go from 0 to 250 in a few seconds. You can break really fast as well, but the walls get very narrow.

Speaker B: Hi and welcome to Enterprise Alchemists. This is a podcast for technology leaders and enterprise architects who are navigating what's now and what's next in the world of AI and enterprise technology. I'm your host, Dominic Wellington, Director of Product Marketing for data and AI at snaplogic. And my co host is Jeremiah Stone, CTO here at snaplogic. This series aims to bring honest and in depth conversations on the forces that are reshaping the enterprise, from agentic AI to workflow automation, and how to scale and govern the changing IT landscape. As part of the Evolving the Enterprise series from snaplogic, Enterprise Alchemists aims to deliver sharp perspectives, real world insight and occasional industry hot take. As Jeremiah and I go head to head and sit down with expert guests pushing the boundaries of what's possible. Hello and welcome to another episode of the Enterprise Alchemists. I'm Dominic Wellington, your host. I'm director of Product marketing for data and AI at snaplogic. I'm joined by my co host, Jeremiah Stone, CTO at snaplogic. Hi Jeremiah.

Speaker C: Good morning, Dominic. Great to see you.

Speaker B: Same, same. And we have a guest this week. We're joined by Alex Mensah from our partner, iWConnect. Welcome to the podcast, Alex.

Speaker A: Thank you. Good morning to both of you. Pleasure to be here.

Speaker B: Thank you. It's uh, a pleasure to have you on. So why don't you introduce yourself and iWConnect, for those who haven't already had the pleasure?

Speaker A: Sure. Thank you for the opportunity. I'm a founder and uh, managing partner at iWConnect, which is a integration consultancy. We portray ourselves as people that know integration and have been integrating solutions for major corporations for over a quarter century now. And we have partnered with, uh, snaplogic. Trying to think, probably over a decade now, Jeremiah, and we've leveraged that partnership to truly support customers around the world, both significantly in Europe, EMEA as well as the us but as a company, we are consultants. So we go Identify problems, we identify opportunities for improvement for, uh, businesses, and then we roll up our sleeves and help them out, do it.

Speaker C: Working with iWConnect has been really fascinating and fun for me. As part of the snaplogic team, I've worked with nearshore, offshore, onshore partners in the past. And working with IWConnect team is a blend both nearshore and onshore service delivery. And also fascinating from a geopolitical point of view. I'm joining you today, Dominic, from beautiful Skopje, Macedonia, at the IWConnect headquarters and working through at least my generation, seeing the break apart of the former Soviet Union and the Yugoslavia region, the Baltics, and working with folks from there, it's really been a pleasure. I hadn't worked closely with companies from this region before working with iWConnect. And so it's been really interesting to see them navigate both the change in technology as well as growing their country and investing in the region here with a very highly adept set of colleagues that are in Central European time zone and, uh, right here capable to deliver.

Speaker A: Yeah, Macedonia or Eastern Europe or the Balkans is not the first thing you think of when you talk about either wars have started here or there is always some trouble.

Speaker C: Right.

Speaker A: But yes, we are very proud of where we at. It's a beautiful country, great people, and we've been developing technologists, people that just love to think, uh, around the technology for a long time. So we're happy that you're here. And again, welcome. Thank you for joining us.

Speaker C: No, it's exciting. There's a budding startup ecosystem here as well. I think everywhere, I suppose, is a microcosm of everything else these days, but really fascinating to meet the team and connect with the other colleagues here as well. So you're at the heart of the global transformation, whether it's arbitraging labor cost or digital labor as well. And now you're transforming your business with this new term coined by Phil Fisch and the HFS group of services as software or service augmented software or software augmented service. It's really interesting to see how your portfolio is evolving.

Speaker A: On one end, it's evolving, on another end, it's challenging. So as we are being geographically positioned where we are, we are also seeing differences between how European side looks at the current state of technology and aspirations, and especially with AI versus the us US side is obviously run, and then when you trip, you dust off and you move on. And then when we have significant issues, we pause and then review. European side is much more cautious, uh, reviewing everything. We also have Geopolitical issues that some European companies are very afraid of just using US based technology. So from that perspective, we have to navigate all of that and it's just interesting. But as a company, the services side is obviously changing because now the expectation from a client perspective has changed. Uh, once you get behind the console of any of the agents, you think that the world's at your fingertips and now you can do whatever you want to. But the reality is that businesses don't change that easily and it's not that easy. So we have to navigate that. So part of what we've done to adapt is we are bringing in, along with our service, all our agents that we have developed and we are blending that. So to your earlier point, you, uh, augment the service with some work. Uh, but naturally we've been doing that for a little while. We have other products that we were bringing to the table and using that as a leverage and extra value for the customer. So now we are mimicking that with agents that simply enhance whether that's. If we're doing application development, well, we'll bring in some frameworks that help us push through that a little bit easier. Or if you're just testing, what frameworks can we bring in that agentically can generate the extra value. If we're doing support, what else can we do around support that maybe collects information and monitors an environment rather than just human beings? There's a myriad of ways that we have adapted our services so that when we approach a customer, one, they can rely on us for our experience, two, we can tell them that we know the AI world as it's developed and as it changes so that we can advise them on it. If you haven't done it, if you can't show it, and you're just theoretical, and everyone is theoretical these days. So rather than that we show them, here's what we do. Let's show you how we run our business internally. And that helps a lot because it creates a level of confidence with customers that allows them to see rather than believe in what will be concrete.

Speaker B: Examples are always very important. So you mentioned cultural differences between the US and Europe, especially around the perception of, of AI and willingness to engage. Do you also see differences between the different industries you operate and perhaps some of the customers that you worked with over the years?

Speaker A: Absolutely. Some industries naturally have closer touch maybe with customers versus others. So let's say a, uh, utility company, the touch point with a customer is much more rare than a retail customer. Right. You hook up your electricity and you're Done the time when you actually deal with the customer, quote unquote, when they call you back, is whether connect or disconnect or, or there is a problem, other than that they pay your bill, you're moving on. So that kind of a, ah, business can kind of look behind the scenes and optimize their own processes and improve whatever makes sense. As long as it doesn't really interfere the service, everything is fine, everyone's happy. So those companies pause and look at what can we do because they do have a lot of invoicing and reconciliation and those kind of processes that are really easy to optimize if there is a lot of manual work. Whereas a retail business, whether you're selling shoes or you're selling handbags or what have you, furniture, if you can't process a uh, charge, that's kind of a big deal. And it happens every second of the day. So those businesses are naturally hesitant to touch those areas of their business regardless of the improvement because an impact there would be catastrophic. So those businesses, depending, uh, on how you look at them, have different perspectives on what AI can do. And just like anything else, it's risk versus reward. What are they going to get? And is AI truly moving the needle for their business or just an incremental value add? Ah, that yes, we can now process an invoice a few seconds faster. But if you're processing 10 million invoice or 20 million invoices and you're spending a lot of time, that's a uh, significant savings. So it really depends, man.

Speaker B: That uh, drive for more concrete return on investment, more concrete business cases around ROI is starting to be a drumbeat in the industry. I think we're moving beyond the initial phase of excitement about just using the technology and making perhaps technology first decisions. We want to use AI, what should we use it for? And towards a much more business oriented situation. As you say, we want to shave some time off of our invoice processing and we expect that we'll have certain defined impacts on our business and that helps us understand also have we succeeded? Is the investment we put into this process commensurate with the return that we're getting back from it? Uh, all of these things are the signs of a maturing industry that we have these more concrete applications. How are you seeing that evolve in the market?

Speaker A: So Jeremiah and I actually had this conversation. Some businesses, although they are seeing AI evolve, they're not really just going to jump into vibe coding just because it's cool. They're really trying to identify what is the real business case, what are we trying to do? Even fast invoice processing means nothing if that's not your core business. But if you're uh, really dealing with invoice reconciliation, for us, for example, making sure an invoice is right the first time is really important because it will delay payments, it will delay reconciliation with customers, and it has to be matched with the hours that have been worked or with the service that has been committed. So having that sort of, uh, easy validation ahead of time is significant because we have been able to tie actual hours and time that's spent from accounting upward in terms of troubleshooting. When there is a problem that costs money. And for us that's easy to create a case. If we delay an invoice by an hour because of this, in most cases it's a few days. This is what it cost us. And if you think about it on uh, say a couple of million dollar revenue or invoice per month, well, what is the delay of five days? Just in interest? That's real money. So from that perspective, and we're a small player, right, A major corporation that has something like that could easily see benefits. But it is a challenge if they don't see that. A lot of times businesses just don't know what's happening. So we have to traverse through the organization to identify what are some of the things that you're doing as a mundane task, but you're ignoring a lot of the benefits that you could see. And that's part of the art and part of the science that we as consultants do when we approach businesses, because it's not going to fit all the same way.

Speaker B: That's consultancy and advisory right there, uh, helping the customers figure out where they can apply the technology. Especially because again, a symptom of the maturing of the market. And uh, this is something that Jeremiah and I have talked about, is at the early stages, you try to apply the technology to how the process runs today. And then the M maturing is when you start refactoring the entire process based on the new capabilities that you have. It's like the switch from the early cars, which were called horseless carriages, because that was a paradigm people had in mind. And then people realized, wait a minute, this is not a horseless carriage, this is an automobile. We can do different things with this tech.

Speaker C: At an event in Germany last week where one of the attendees said, look, we need to all internalize the fact that every single process we have is a legacy now and we have to redesign Our businesses around that. And you know, I think the places where it seems, based on what you're saying that you're seeing this most really is there a competitiveness dynamic in terms of acquiring a new customer? So speed to be able to show the potential for value and speed to deliver. Interesting to hear how you talk through that customer acquisition process changing, you know, does the client engagement discuss and change relative to describing what the company can do versus demonstrating what the company can do? And then there's the financial competitiveness dimension which you talked about a little bit more here, which is, look, how are you managing your balance sheet? Are there ways you can get collections in faster? Can you manage your cash flow differently in terms of the business itself? And there's these two different dimensions, I guess, or business growth, competitiveness and then how you operate the business from a financial dimension, either volume or savings. Yeah.

Speaker A: If you know what you're doing, you just need more resources to actually get, get going. Right. So you're looking at, I have a great business, a great idea, uh, I just want to rev it up. Right. So that's volume or speed so that you can compete.

Speaker C: But you're a mid sized services provider. Right. Which is arguably one of the most competitive knife fights out there. Because these days particularly, I would imagine with the advent of AI, the ability to, you know, start up a consulting shop is pretty low. It doesn't take a lot. If you're smart and you have a lot of work ethic, how is that changing the competitive dynamic for you? Are you finding pressure from new entrants that are smaller, perhaps more nimble than you, or do you find this as an opportunity to go after those global system integrators?

Speaker A: We see it as an opportunity because you're truly in that middle. And you're absolutely right that you have companies that are popping out every day because what else are they going to promise other than the world? Right. We can do anything. And I asked the person, would you put software that kind of business is going to create in the machine that's monitoring the heart of a patient? And would you be willing to be that patient? I certainly wouldn't because we get the enthusiasm, but we also need certainty. And then let's not forget about compliance. And everything else then is the global size who know all this and they have much wider width. But it's not easy to change the direction of the Titanic. Right. So now you got to go check and make sure that everyone is doing the right thing. But that takes time. We are much more nimble. We have the ability to be an R and D shop when we need to, but we are smart enough or wise enough to know that you can't act like a bunch of yahoos, right? We're just going to go and do whatever. And that mix and experience allows us to not just sustain, but we've been growing over the past few years because of that steady approach, while we are actually being truly R and D driven and we go after what the marketplace offers from a technology perspective, but also what customers are looking to do. Because customers are going through evolution as well. Uh, businesses in general are going through an evolutionary path of adopting AI. And there's still plenty non believers that believe that if I do this, I'm really sacrificing the people. There are, uh, others that are just dabbling. They're trying it out and seeing. And this is where vibe coding is still cool. Those that get off of that and start thinking about how do I actually move this into a meaningful way so that everyone in the organization pulls on the same cart in the same direction. They realized that you can't just keep it all open and you can't just say, well, everyone does whatever they want to and this is where they started struggling. They've allowed people at the bottom basically to explore which is good. The organization hasn't changed for that exploration. It's not easy to have an R and D shop and have an organization that's siloed and that needs from hand to run because these people are going to want to run quick and they hit the wall or the ceiling. And you've got to change the organization for that. And that's what we call the hero mentality for AI, uh, is organizations that have realized that you got to change across the board, you got to change your people, you got to change your processes, and you got to uh, change the product that you ultimately supply to the marketplace. But that takes time and it takes an understanding much deeper than what you would be led to believe that it's all possible, you just need to subscribe and things are just going to happen.

Speaker C: Well, that makes sense from a macro change management perspective. But walk me through, what is it? When you're in that competitive situation, you have a client who understands their scope, or they think they understand their scope. But we've all know that scope change involves. That's why tech consulting stubbornly remains a time and material business rather than a fixed scope business, because the scopes change. How is that competitive moment when you understand the scope and um, you know, you have two Three, four other service providers competing for the same business. How have you changed your business or how are you thinking about changing your business so that you become more competitive in that moment?

Speaker A: So to your point, we've changed quite a bit in that regard. We are now offering our time and material business as an actual service. So rather than count the hours, we count the outcome. So we go and talk about we've gained the ability to manage risk better. Right. With AI, uh, because now we have a solid feeling that yeah, I may over promise in some areas, but my risk has been reduced because I can rely on AI. And obviously during negotiations I would know whether the customer accepts it or not, that we use AI, etc. But it gives me the ability to flex. Right when I tell you that yes, I will do this by end of the year and this is the amount of you will get a jug of milk. My mistake. Rather than traditionally 20, 30% would be 5%. I can live with that. And I can price it appropriately so that I don't need that wide margin. So when a competitor comes in and just goes on time and material one, the risk is now transferred over to the customer. That's one thing. If they go price it as a fixed bid and they don't have the knowledge or the experience, then they would have to widen the margin. So the margin would be. If it's 100k they'll say it's 80 to, I don't know, 120, I'll say it's 95 to 100. So it gives much more certainty. And then we negotiate. Is this the real value that you want? Is this worth 100k to you? If it's not, then what is it that you want? It changes the discussion. But we are pushing a lot more service based and outcome based measurement of how we perform versus the traditional time and material.

Speaker C: So you think this long desired outcome based pricing for project delivery is within reach. You can now compete on that. And because your ability to accept scope change orders, that sort of thing within the original price, you can now fit that more effectively and you don't have this brutal change order conversation anymore.

Speaker A: Yes, uh, and we are thankfully able to do that based on the technology. So say we have a six month project, a traditional six month project where you get some ideas, you go through an rfi, you get an RFP and then you spend some time pricing it out and you ship it back and they tell you this is where you need to be, you come up with an SOW and then you get to work to your point, made m the way through that, they realized that's really not what we want. But you've already signed a bunch of contracts, so you go back and you turn to that probably a few more times. In the sixth month comes to about 18 months, 12 to 18 is what I would expect. Rather than do that now, we say, why don't we actually build you something overnight or over two days? Is this what you had the feeling for? Right. And it's not going to be your, uh, fully fledged application, but you will get the few, you'll be able to put your fingers, touch it and see how things look like. So we churn through the spec, if you like. So we go through a spec driven development rather than developing on specification. What that gives the customer is a feel for what they really want. Because most of the time the challenge is the customer doesn't know the outcome. They know it in general, but they don't really know the specificity of what their customer will want. They naturally have to get to a point where they give it a try before they know if it's good. Well, if I can pull that back as early as possible. Rather than spend time on evaluations and timing and the cost and all that, we've punted on all that and say, here's a potential product, is this what you want? And nine times out of ten it's like, no, not really. Can we change it this way? We are actually compressing all of that time in the early design and the debate over contracts into really, let's iron out the specification. Once we have that, we have a high degree of confidence that they know what they want because they saw it.

Speaker C: So you're using rapid prototyping as a way to clarify spec and to get closer to outcome based product delivery. Uh, that's really cool.

Speaker A: All right. And we have tools like what I mentioned. Robin allows us to actually go do that constantly. So as recordings are coming in, we even push back on the customer. We allow the customer to come into Robin and type up what they want. And if the requirement is not smart, it pushes back and says, well, you're missing this and that. So they don't like it. But ultimately it's good for everyone. Once we actually get a good requirement, we have an option to say we want to visualize this how it will look against the context of, uh, the actual real application. That's hard to do unless you've done some prep work. When they see it, the business analyst or the product owner says, m, that's not really What I wanted, I meant this. So they go redo it, but they update the spec, they don't change any whiteboard, they update the spec as soon as they're done with the spec and they're like, yeah, this is what I have imagined. It gets shipped to development where now an engineer looks at it, feeds it into another AI that generates tasks and those tasks become actual workable code. But you have high degree of certainty that you know what you're going to get because you saw it and seeing is believing. Exactly. And it's all sped driven, so it makes it for us. What it means is that I know that the chain requests are going to be minimal. Maybe they've missed a major thing. And we aren't really in the business of being hunted by customers. We truly partner with them. Most customers are five plus years, seven plus years. You don't do that. They're just called, hey, we're going on a fishing trip, we need extra hand to carry the fish. Right. Uh, we're planning on, we will be in the fishing business. What are we going to do, what kind of boats we need, what areas we need to go to. And that takes time. So if we miss something, it's a cordial discussion. Hey Jeremiah, we missed this or this isn't what you told us. Let's find a way and we'll correct it going forward. So that gives us the comfort to say once we know what the outcome is, we'll price it and we move on and it moves much faster.

Speaker B: I love the parallel with agentic software development where a lot of the process is iteratively developing what inner fed becomes a spirit spec for the final output, the final product. So what you're doing is at a higher level of complexity. You're effectively helping your customers, our joint customers, to build a better spec so they get closer to what they need, what they're uh, looking for in the first place.

Speaker A: Yeah, because ultimately they're not bad players in software development. It's just all of us do what we feel is the best thing to do, but we rarely or sometimes we pass each other. Right. We don't listen to each other. So what we've done with the agents is we give a counterbalance that's not another human, it's an agent that acts based on the Persona that we've defined. You are basically business analyst that needs to challenge the owner on what do they really want is this, ask the specific questions so the owner feels like it's one heard, but also that they got the real feedback that they need to really iron out the product. And going through that iteration at each, uh, stage of the is actually powerful because you get to something really truly valuable and what people want it.

Speaker B: Yeah. And how do you then ensure the adoption? Because a big part of getting a successful outcome is also making sure that what was built gets adopted and gets used in practice so that you can actually achieve the original goal. How do you help the customers make that happen and get the adoption throughout their own organizations?

Speaker A: Uh, lots of communication and transparency. Where the hesitancy comes is one cost. Right. You're using AI, but I have a never ending cost line that basically keeps growing. So we are trying to tie that cost to the actual value delivered so it's always visible. What did we do? How did we use this? And I always comment, we don't charge customers for our own R and D. So when we deliver an agent or we deliver, some technology has been developed in, uh, our R and D shop burning our dollars for that technology rather than theirs. So when they use it, if they ask, I need a test case for Solen's test case. By pushing back on what I was talking about earlier on the requirement. And the requirement is solid. Once you get a solid requirement, getting the test case for that requirement is valuable. Right. The, uh, cost doesn't matter. Someone is going to have to do it. And if we can show that's what we spend dollars on for an AI, uh, agent, that's meaningful and they're comfortable with that. But it's not going to be this, well, I'm going to go and ask a question 15, 20 times to get something by the time you're done, you could have just done it by hand. Right. Uh, so you don't get that feel because all of that iterative steps that you would have to go through with normal, just a chatbot, are taken away by some of these frameworks. We get to a point where we're able to show that there is true value out of uh, whatever we would give the customer from an AI perspective. And the rest is how you expand it across the board. Right. One is on line by line delivery, whether it's code or test or deployment scripts or whatever. But the other is how are we doing across the board? Right. And uh, you and I have talked about some toolkits and agents that we have that actually monitor that. How is your organization performing? Are they faceted in, in terms of delivery and volume or not? Which part of the organization is able to do better? How is AI used across the board? What Are people doing automatic coaches? As we talked about last night, even for us, we have toolkits that basically monitor how we are using AI. And if we see higher productivity in one area that is fed into the system so that others can get coached on. Here's what we're seeing good results with. Try that. I changed this model because it's cheaper. You can still get the same thing done and those things are fairly helpful.

Speaker C: It's incredible. As Alex is mentioning, we had a extensive dinner conversation last night. I have to warn you, if you come to the Balkans, if you come to Macedonia, bring your appetite and your ability to say when. Because man, it's definitely an infinite ability to have wonderful things. And Al shared with me the agents they've been building here and the agents they're delivering. What I find fascinating about these is not only the quality and what's interesting here. For example, the PRISM agent that is giving transparency into the entire dev shop, plugging right into JIRA and datadog and other monitoring solutions, et cetera. What I find really interesting is that the way you think about this isn't as iwconnect as software company. These are embedded into the service and they're delivered with the service as part of the service engagement. And you're essentially creating this declarative transparent environment where the tools you're using to deliver your improved service, you're then giving the client a experience as part of a team, complete transparency. And if the client wants it, that can be a completely separate conversation and a service delivery. Yeah. And so uh, I find it really interesting that this is software augmented professional services and service as software again that is then delivered in concert with faster time to value outcome based projects and essentially helps you compete for business.

Speaker B: It's super interesting and it aligns cost and value because as we're saying, if you've got the meter running for the tokens, then you need to also be delivering continuous value to match that continuous cost. And so I see Pete there at the bottom. I was talking to one of our common customers about how they're using Pete to help them understand their own integration process and increase the maturity of how they use the snaplogic platform. And again, that's not a one and done. That is a continuous ongoing process that you engage in.

Speaker C: Alex, what's your favorite one of these that we can dig in here and walk us through kind of the thought process, how it came to be and how it's being experienced to customer, how it's changing the relationship between iWConnect and

Speaker A: the customer, they serve various things but if you hit Robin for example, that covers the full sdlc. So it goes through the process of developing software. Let's say we're dealing with a company that has application development as core of its business and that's what they see as their advantage. Well, with Robin we allow them to really remove whatever is dubious process within their system into a much more streamlined process. Because Robin embeds the sdlc, includes the human in the loop, but uses AI for those side chats, fire chats and stand up discussions where you're debating things. What does the real customer want? We've taken that out of the discussion at least to a degree where when we get the specification, it's solid. Once we have a specification, the actual development is now orchestrated rather than developed. We have a number of agents depending on the technology and workflows that our process. Let's say we are developing something for snaplogic and now thanks to the new CLI ability, we'll be able to create a workflow that out of specification generates the snaps logic code. But ultimately it's driven by the spec. We aren't and it's all tied to Jira and DevOps and all that. We are able to change one the narrative but also the speed of delivery so that the customer can actually see the final result. And so all that is possible part of Robin as a framework. So it's really a uh, multi agent solution that we bring to the table along with us and say this is what we do. We can do it the traditional way if you don't want to use AI or we can use this. Everyone benefits because we get to do this better, faster. And to your earlier point, if the customer says well can I use it? That's a different discussion obviously. But we bring this to the table because we are no longer talking about how many hours are we going to work on. I'll just ask, what do you expect, uh, to have? How will you measure that? You succeeded, not me. I'll just make sure it happens. And if I can do that in a certain amount of time, then it's a discussion again. How much is this jug of milk worth to you?

Speaker B: A much more productive conversation for everyone. Yes.

Speaker C: Yeah, it's totally fascinating to me that I think many service providers that we work with are certainly reinventing themselves and changing, changing how they deliver, but a lot of it's behind the curtain. I think it's fascinating here is you're being declarative and saying, look, this is the way we're going to deliver your project. And by the way, you're going to see the, it's like the opposite of the sausage factory metaphor. Now, this is like you look into one of those highly automated manufacturing environments with obakuka robots and stuff, and it's beautiful. It's like a ballet of automation and humans working together on a rolling line. And it seems like that's what you're reaching for here, is to say, look, we're going to be completely transparent. You're going to see all of the workflow, you're going to see how it flows through, and the tooling we use is going to be apparent to you. So there's not even a suspicion as well that you have something behind the curtain?

Speaker A: Uh, it's not just that, but we also are totally transparent with the customers that what we're trying to do is remove that void, that area of the SDLC where we are in our own bubbles and wasting time effectively. So now that we know, we are basically optimizing and early on, even internally, we had the fear. Yeah, but doesn't this cannibalize our work? Well, it doesn't cannibalize you. If you're just sitting around doing nothing, waiting on the customer to tell you, then that's not cannibalizing. You're just telling the customer that we are wasting time. And it's much harder to do that when you're across oceans and you can't really see, uh, each other. But if we have a system that actually explains that pushes back and makes us more efficient, now the customer actually sees the value they want to do more, not less. So what we've seen is that the customers that can realize the value that we're bringing, they're giving us other work because they're saying, wow, you guys are excelling two, three times.

Speaker C: Yeah, it seems like you're getting three outcomes here. You're decreasing your time to high quality proposal pretty dramatically. You're increasing the quality of what you're delivering because the fidelity of the requirements are so granular.

Speaker A: And the consistency, that's the other thing. Thanks to certain processes, we have something called center of excellence, which is a combination of our experience or decades, the standards, and it's all well documented. Again, compliance. Right. But now that's all embedded into a system so that when we deliver code, everything looks the same.

Speaker C: It's not sitting on a SharePoint in a document, it's in embedded into the system.

Speaker A: Uh, and that's valuable. And the beauty is if we change because new technology comes out or whatever. Now that's much easier to proliferate throughout the systems. And we just say, hey, what you did yesterday, go and review it for these specifics that changed. And it goes and does it. So the governance is included, the consistency is good. And as a company of 350 or so people, it's hard to imagine that everyone will do what we think they should do. So we're punting um, on that part of the education and consistency in creating frameworks that will do that, uh, for us. So we're still doing the same service based delivery, but we've removed some of the nuances that are usually hurting all of us in the delivery side. And that's cool.

Speaker C: No, it's fascinating. So decreasing your time to proposal, increasing quality, increasing transparency and governance and increasing speed. So are we now fighting the devil's triangle of quick, fast or uh, was it speed, cost and quality? Are you able now to go or are we just changing the quanta of speed, cost and uh, quality?

Speaker A: It's still a triangle. It's skewed a little bit, but it's still a triangle. But now we have an easier choice. So a company knows the volume of what you can do that cannot change. There is a certain cadence. But if you believe that you have the funding, you have the idea, you just need the time and energy to actually accomplish something, then it's how much can I do as fast as possible. The other is if you're struggling to figure out what your business will be now, uh, you can reduce the cost. You know what the reduction in cost will mean for the productivity. So you can turn the knobs with a little bit more comfort so that you take the time to figure out what you will do. Because another thing is AI is great if you know what you're doing. But if not, it's like making a millimeter change from here. But you're looking at the sky. Yeah. You end up on Mars versus the sun. Going to the sun is going to hurt you a lot more than Mars. Right. And that's kind of a thing. It moves fast, it's great. But if you don't know what you're doing, you're going to be in trouble. You could be going the opposite way.

Speaker B: Increasing the speed without knowing the direction of travel might not be helpful. Yes.

Speaker C: It's just fascinating to see the change in the competitive dynamic. And as a European nearshore combination onshore delivery, it's obvious that you saw uh, this cost arbitrage risk. But instead of trying to focus on a rate based Delivery or something. You're embracing this, and now you think you can compete for bigger, more complex business as well, is what we want to see. Because increased competition should increase the vibrancy and the quality of the market itself, correct?

Speaker A: Correct. But I totally agree. And m. Another metaphor I use is obviously F1 racing is popular or a lot more popular recently, but with AI, we were all drivers. Right now we have access in F1 car. If you think about it, it's cool.

Speaker B: Sounds dangerous.

Speaker A: You can go really fast, but it's dangerous. Someone still has to check the tires. Are they warmed up, Are you using the right gasoline and all that. Just because you can get into one, you're not going to get in. Oh, um, we're going to have a race. No, Normal businesses do not act that way because you can go from 0 to 250 in a few seconds. You can break really fast as well, but the walls get very narrow.

Speaker B: And if you're trying to deliver some pallets, then, uh, F1 car is probably not the best vehicle.

Speaker A: Excellent.

Speaker B: Alex, you've been very generous with your time, and I know you and Jeremiah have places to be, but this has been a fascinating conversation. I hope our listeners have also found some nuggets to take away from here. If they want to find out more about iWConnect, where would you point them?

Speaker A: Just the website, iWConnect.com or our LinkedIn page. Or they feel like we got to work with these kind of people. Saleswconnect.com we will take care of them. We've been taking care of customers for, like I said, quarter, uh, of a century. And we're honored and thank you guys for the time. This was a pleasure.

Speaker C: That was a great conversation. Thank you.

Speaker B: Thank you so much. And for our listeners, we will talk to you again soon. Thanks.

Speaker C: Bye.

Speaker A: Bye.