EP112: Inside Enterprise Automation, How Yexle Delivers Real Impact with Appian w/ Vijay Poondy

Hello and welcome back to another episode of the Process and Automation Podcast with the Automation Guys. Yeah, as many of our listeners know, we are huge advocates for practical and applied AI and applied automation. And there's no better way to judge if AI and automation is working or if it's beneficial or has the right impact by working with clients on a daily basis. And from that thinking, we thought it would be great to speak with someone who has done this for most of his professional life, has built a successful consultancy business, and he also is as passionate about AI and automation as Arno and myself are. So, and then without further ado, it is a great pleasure to welcome the founder and managing director of Yexle. Welcome Vijay Pundi, welcome to the podcast.

Thank you, Sascha. Thank you for inviting me and having me. Thank you, Arno, as well. Wonderful to meet you guys again.

Lovely. Yeah, Vijay, we are excited to hear your insights today and learn a bit about Yexle and the work you're doing with the clients. And to kick off, maybe you can maybe share a bit about your background. How Yexle started and maybe how you started your career and what kind of organizations are typically working with you and with Yexle every day?

Quite a lot of questions in question number 1 itself, but not a problem. And this is Vijay Pundi here. And, you know, I go either by Vijay or Pundi, primarily because from my previous companies, one of my CEOs was Vijay. So he's like, you know, we should not have an identity crisis. So from that perspective, I've been addressed as Vijay, as how Sascha called, but in the Appian ecosystem, also referred to as Pundi. So I've got over 30+ years of experience hands-on, right from being a coder, worked on mainframes, Java, database design, and everything like that. Moved on to managing projects, programs, large, very, very large transformation platforms, and now running Yexcel as a manager, managing director and a founder based out of the UK actually. And, you know, I've worked a lot with the so-called workflow, the BPM, the process automation platforms like Appian, Pega, IBM Lombardi, and the likes. So a few of these technologies are low-code. Some of them have already transitioned to what they call as BOT, which is business orchestration and automation technologies. Appian kind of fits into all these actually, primarily because of how quick, easy, and efficient and effective it is to actually create requirements, convert them into configurable code, and implement them into a production environment, right? So from an Appian perspective, yes, I've known this technology for almost 12, 13 years now and know quite a lot of companies that work on it, have extensively worked with Appian as well, right? Up to 2019, I was actually working for different companies with the last position being head of customer success and delivery for EMEA. And then I was like, you know, I'm working for somebody else, you know, why not try something on my own? And that's when in early 2020, I started Yexcel. In Feb, almost Feb, we kicked off, Feb 2020, we actually kicked off Yexcel. Within 2 weeks, got wonderful news that yes, we are enabled as an Appian partner. Also in that 2 weeks, we also welcomed COVID. So we kind of call ourselves very proudly a COVID baby. So, you know, Yexcel as an organization does nothing else but make Appian bigger, brighter, and better than what it is today, right? You know, started, like I said, 2020, headquartered out of the UK. Fast forward to today, we are 6+ years, almost 200 people working for Appian XL. Like I said, we do nothing else but Appian. You know, UK is the headquarters, fully owned subsidiaries in India, Australia, US. We also work with customers across US, Canada, Middle East, and South Africa, right? And the kind of organizations that we work with today, typically any organization that actually is looking for automating their processes, right? Processes could be on paper, processes could be disparate, sitting on multiple systems. You know, users could be using swivel chair to look at things, one system data from one system, data into another, so on and so forth. Anything that can help support like an orchestration, there Appian kind of lends itself very well. It also lends itself very, very well to areas where there are very important regulatory changes. Imagine COVID, people were all sitting at home, didn't know what to do because many processes were manual. They wanted to deliver something as an application. Boom, Appian was there, could deliver in weeks rather than months or years, right? So from that perspective, yes, it's a very low-code, very transformative platform. We work a lot with banking, financial services, and insurance customers. Not to say that we also work with very, very niche companies, very large manufacturing companies. The moment you think of an automobile, I'm sure there'll be a few names that come into your mind and these fast, fancy cars, right? That, that kind of come into your mind, which puts a smile on your face. Yes. One of them is our customer as well. So those are the types of customers that we work with. So any organization, any domain that requires a process automation transformation, probably the product or the platform to be.

Great. Quite exciting. It's a very, very sophisticated backend partner. I worked with Appian extensively myself with Sascha Cutura before. I really liked the product. And it's good to see that these partners are out there to help customers. Of course, we on the automation space as well, similar to you guys, use low-code platforms to automate virtually any type of process under the sun with the AI coming a little bit more sort of mainstream, you know, once some of the hype cycles has died down, you know, so we, we starting to do a lot more in that space as well. So, uh, just a question from my side. So where, where do you, um, see the, the competitive edge today that, uh, Yaxel has got, uh, specifically sort of around the value add, you know, you add on top of, of, of Appian?

Yeah, I think that is the keyword. I— you've asked the question, but you've answered it yourself, which is the value add, right? We don't want to just add people. We want to add value to any engagement and customer that we work work with. So from that perspective, I think one of the most important differentiators for us is basically the competency that we bring in, not just the capability. So just to, you know, I mean, from our perspective, what is the differentiation between capability and competency? Capability is, yes, you're trained, you know the platform, you know what to do. But competency is to do the right thing for the right customer, right? In the right way. Because there are, you know, as they say, GPS can also take you through many roads, but it depends on that particular point of time, that particular day, you know, and depends on how well you are able to maneuver the traffic so that the entire end-to-end experience is comfortable. Not just that, but what is the best and the most optimal solution for that implementation, right? So that is the competency that we are able to bring, one. And I think the other important thing is, you know, many of the people who have worked in the past, even in Appian as an organization, work with us, very senior people, right? Plus, if you look at, uh, EXL, we don't believe in what we call as a pyramid model of resourcing where you have bottom-heavy junior people and then it slowly tapers when you actually deliver or work for implementation of projects. We work in what is called as a diamond model, which means you have resources and people who have more experience in the middle layer. Naturally, what that does is gives a lot of technical competency, it gives a lot of technical governance. And with the experience that people have, they know how to make things mostly first time right. So that way, you're reducing the cost of rework, you're reducing the total cost of ownership. Right. So from that perspective, we've been very, very consistent, you know, from providing that kind of an edge to the customer. Right.

And yeah, that sounds great. And then from your experience, what are— what do you think? There's obviously lots of use cases. You touched on some industries earlier. Sascha Cutura, yeah, from your experience, what do you think are sort of the most useful and most impactful use cases delivered with Zepion right now?

I mean, many of them are, right? If probably my customers are listening to this, they're going to actually give me a lot of grief to say, why did we not come in the top 3? But suffice to say that, you know, all customers are important. All projects, programs, implementation is important because we are not just delivering user implementation and we are not delivering just an application, right? We are delivering a user experience. We are delivering value and business outcomes to the customers, right? For them, that is extremely important, right? So take an example for, you know, in banking financial services perspective, right? One of the projects we worked on was basically model risk management. You know, every bank has different models basically for the products and services that they are rolling out. So they could change based on a regulatory regulation, they could change based on an entity. For example, a credit card is a model, just as an example, right? So rolling out credit card in the UK could be very different from rolling out credit card in the US because of the regulations. It can have different overlays, it can have different adjustments, it can have different changes based on the regulation. How can we actually ensure that for a given entity we are able to actually assess the risk of a model getting changed or that a limitation on the model and overlay on the model, for example? Right. It's not very— I mean, we didn't do the simulation part of it because there are definitely better tools, but how to manage the change around it, typically from a case management perspective to see what is the, you know, which of the departments have worked on it, how have they simulated it? Is it actually compliant to policies, procedures, regulations of that particular geography or that location they have been in? This has been a very big problem for large banks. We actually implemented this for 1,100 models in a large bank. Globally for 49 to 50 entities of theirs within 26 weeks. So, you know, you can imagine the scale, you can imagine the integration, the interfaces, but you know, that's definitely a marquee use case. And, you know, we've had instances where financial institutions have mis-sold products, which means FCA have come back to them to say that you need to remediate these mis-sold products. So typical example again was remediating or going to live with a remediation case management platform within 51 days. For a customer. So they could actually triage and close it for 250,000 customers. And, you know, that's one thing. And then one of the impactful use cases, maybe not for us, but, you know, one of our organization's senior executives actually use chartered flights, for example. How could they actually request for the flights so that they can actually travel from one place to another? While it looks like a fun use case, there's a lot of actually bells and whistles around it because there's a lot of tax implications, whether it's for personal travel, official travel, or are there company by somebody else, etc., etc. There's a lot of rules that go behind it, along with the payment and along with the tax deductions, the compliance, the reporting, etc. So like I said, you know, it's not just from a regulatory perspective that use cases are impactful. It just depends on what value we are delivering for the customer and how much benefit they are getting from that also matters. So just, just a few examples of some varied cases.

Sounds good. Thank you very much.

So, and Vijay, yeah, thanks. Thanks for that. Sounds, sounds very, very interesting and quite aggressive timescales there. But yeah, like you say, you know, having an experienced team, a good methodology, it sounds like, you know, Yatso is very much, you know, it's got those capabilities to produce those outcomes. I just want to quickly touch a little bit on AI because obviously that's quite topical and just to get your view looking slightly ahead in, let's say, the next 3 to 5 years. Where do you see intelligent automation and AI sort of natively embedded in low-code tool and enterprise working? Where is that evolving to and what would the future look like, let's say in 5 years' time? You know, specifically around the things you guys are doing or the Appian platform.

Yeah. So see, Appian also has AI-related skills embedded within the platform. That is for sure. But see, I think quite a lot of ways in which AI is being used I definitely don't want to say I'm an expert in that area, but for sure, you know, there is agentic AI, there is, you know, predictive AI, there are AI prompts, you know, you know, many, many things. And we still have language models as well that are just doing the grunt work as well so that they can actually surface intelligent data by collating from multiple places. So from that perspective, yes, the intelligence can actually be used to make things quicker and productive, right? So like I said, the language models can basically parse and go through tons and tons of data, which usually could take weeks or days or months for someone to do within minutes, right? And it can bubble up very prescriptive, predictive, and adaptive types of information to any platform. But what happens is if, say for example, it is bubbling up such an information to a platform like Appian, which is actually known for case management, for business process management and business automation. What essentially happens is this becomes a very, very good combination for what we call as intelligent case management or intelligent hyperautomation. AI is basically doing a lot of grunt work in the background. Real time, it's adapting itself to give insights. Using that insights, a tool like Appian can actually move the workflow intelligently so that there is related and relevant next best actions. So from that perspective, yes, a combination of such AI and Appian can do what I call as hyper automation or intelligence case management.

Predictability of what's the next—

Yeah, it's not just— it's predictability, adaptability as well, right? And providing insights, right? Agentic AI, if you put them on documents, for example, what could take, like I said, weeks, it could summarize it within minutes, right? And based on the summarization, if you're configuring it in such a way that, you know, if there is a higher risk, you should move it to a department XYZ, for example, for workflow and for for process management. Yes, possible. But if you say that it's a low risk, then it could do a straight-through processing itself as long as the risk is much lesser. So there is, I mean, the options are endless. While that is one example, Appian also is trying to actually use AI and skills in order to make it move from low-code to a lower-code is what I call it, right? So, you know, you've seen many, you know, how should I say, high-code applications today. You know, someone can actually type you know, a set of requirements and boom, bam, it kind of spins out at least a very, very high-level set of code and codebase, right? So if a high-code can do that, something like Appian can also ensure that whatever is low-code now can actually be much more lower from, from the perspective of that. So, you know, it is also moving towards the ability to automatically generate code based on requirements or based on a set of instructions. I think where I see this going is people start tending to be more thorough with providing requirements, right, rather than writing requirements, right? Because if AI can do that grunt work and if it is helping us be more productive, then more time is actually spent on elaborating and ensuring that the requirements are correct and complete and reviewing if that correctness is also incorporated or is also manifested in the code that is automatically generated. So I think that's where things are going. And, you know, AI is a tool. It's going to be as effective as the person who's going to use it. It's the bottom line as well. Right. Okay.

Yeah.

Yeah. I think, yeah, very, very interesting things will definitely come up. And I think it's great in enterprises to see definitely these things being established to develop applications faster. Sometimes I'm quite surprised when you were talking about these impactful use cases. Sometimes I'm surprised that big organizations are not there yet. So, so there's still a lot of old legacy stuff out there. It's frightening actually how much still there is. But of course, we have a lot of work to do altogether in this industry and building these applications faster, get just time to market and time to value. If that is increasing, that's, that's very powerful. And I think this is where the real, real advantage of AI will be ultimately less, less of the nano banana kind of stuff that's not necessarily where I see a real impact at the moment.

Fair enough. The one thing we are always resistant to is also change. Yeah. It's always a fine balance.

Yeah, it's hard. Yeah, definitely. So if you were advising a company, um, sort of beginning a serious digital transformation initiative today, I think there are a lot of companies doing that, but, um, what would you suggest as your first 3 steps? To them?

See, the first thing I would tell them is, you know, don't just look at the outcome and don't look at just the fancy flashy tools that are available in the market just to say that, you know, I've also jumped onto the wagon. I think the most important thing is to understand from a process of transformation, what are the KPIs, the KRAs, the values, and the tangible benefits I'm going to get? When I say I, it's the organization is going to get. From the perspective of the transformation exercise, right? If there is nothing much, but you just want to say everyone says I have, I want AI, so I'm going to get into it, then there is actually no, you know, adoption of a use case where you are going to expect real benefits. So I think it's basically, this is my perspective, right? It's basically the outcome is not just a successful application delivery or a successful change from one platform to another, but it's more outcome based on the KPIs, the KRAs, the value value the organizations are going to get, right, from, you know, and the business outcomes. That is one thing that, you know, or the first most important thing I would say organizations should look into. Once they have understood that, yes, there is going to be these values that are going to be achieved by this transformation exercise. The next I would say is to look at the bigger picture. I always say think big, but start small. Think of the whole transformation as a box of Lego bricks, for example. Yes, you need to exhaust all the the bricks that is there in order to make what is there at the final endgame. But that doesn't mean that the endgame is the only thing that is there. You start looking at things from a bigger picture, but start putting it incrementally so that each component interacts with each other seamlessly and is able to deliver value and is functional to the level that it is actually built to. So that is what I would say as a second thing. So that way, what happens is The moment you have started small minimum viable products or incremental releases keep going into the production environment, which means the users are able to use that, right? And they're also able to see value to the inputs that they have provided because it's a constant release and a change management cycle. So there is more adoption, there is more willingness for them to participate in the transformation exercise as well, because at the end of the day, they are the ones who are going to use and their inputs, their interest, their involvement is basically the one that's going to make any exercise or a transformation initiative success. That would be my second thing. So a collaboration, a feature team from that perspective is very important, right? I think the third thing is we all know how disruptive technologies are today. What we have today is probably almost obsolete this evening or not available tomorrow, right? So from that perspective, we are building systems that should stand, applications and initiatives that should stand the test of time. So from that perspective, having a look ahead from the perspective of future-proofing, from the perspective of scalability of your application, is very important. So from the, you know, how robust your application is today— I use it for 20,000 people, tomorrow I use it for like 40,000 or 50,000 or 100,000— from a scaling perspective, is my system going to work? And second is, today I have, say, 100 functionality. Today, tomorrow I'm going to have another 50 more because regulation is changing or regulatory is coming or new entities are getting added. It. How is my system going to scale? So from that aspect, not just take care of the coding perspective or the codability of the applications. I always say make applications more configurable rather than codable. So that way it becomes scalable. You're also kind of giving that power to the business administrator, not just the systems administrator. So, you know, as long as you're able to do that, then yes, you know, it's a win-win for all of Yes.

Yeah.

Yeah.

I think you've almost answered my next question, which was going to be, you know, what's the biggest reason you see transformational initiatives fail? I think all those, those 3 points you touched on, it is almost not actually hitting those points. Like you say, setting out what is the value of the change, you know, what thing that, what is the value that we're going to drive here? You know, can we collaboratively sort of work with the with stakeholders? Do we have scalability? Is there anything you want to add to that, you know, reasons why you feel these transformation initiatives fail?

I think, I think one of, like I said, you know, sometimes when we are excited about that thing, big starts small. I've, in areas seen, you know, the definition of small becomes bigger and bigger as well. Right? So, you know, we always say that try to keep anything that you can do as smaller increments. See if you can make releases or viable products every, you know, 10 to 12 weeks. The reason is because it's a quarter, almost a quarter. And Appian, I'm purely also talking from an Appian perspective, right? So Appian releases its upgrades every quarter, which means there are new features that come in, new, not small ones, right? Very, very good Very nice usable updates and upgrades on the platform come every quarter. So what we try to do is, as you keep going through the process, make sure that there is agility, there is, you know, nimbleness in the team, there is prioritization. So you understand what a minimum product is, what can be delivered within 12 weeks. That way what happens is— sorry— that way what happens is you've released it in quarter 1. By the time you're ready for the next quarter, you already know what are going to be new features of Appian that are coming in. You could actually start using them so that the system also scales. There is better backward compatibility of the, the application as well to new releases, right? So that's what I'm talking about, future-proofing, scaling as well. So again, just to add agility, you know, teams being very nimble and prioritization of requirements so that you could actually deliver things to the end users, say, in 10 to 12 weeks.

Fantastic. Yeah, very insightful. Thank you very much, Vijay. Vijay, we have a tradition here on the podcast. We and our listeners like to get to know our interview guests a bit more. So not just from the, from the business perspective, more, so more, yeah, more on the personal side. And if you're happy with a couple of sort of, sort of quick questions, then we get to get going. All right. So the first question we always ask is, who's your idol and why?

I would say actually, I could give a lot of celebrities and stuff, but I would be realistic to say my parents have actually been my biggest idols. Started from very humble beginnings. So I've learned a lot of resilience from them. I've learned a lot of, most importantly, how to go together as a team, go together as a group of people during very difficult times. I think that has taught me a lot of humility. That has also taught me how to be very judicious, you know, with the spend, with the money. Et cetera, right? I think those have actually constantly helped me because it has helped me root to my basics. So from that perspective, yes.

Yeah, thanks, Rohit. I've got one for you as well. If you could instantly absorb the knowledge of one book, which one would you choose?

Okay, so I've actually started getting a lot into quite a few spiritual books, you know, and there is a book by a person called Om Swami. He wrote a book called The Monk Who Sold His Ferrari, right? So he was a very successful entrepreneur grown-up businessman, left everything in search of who am I, what am I kind of a thing, right? So this is one of his books. I've done a read and a reread. The reread is not only to brush up for me, but it's to ensure that my wife doesn't bin the book or donate it to charity. So even from that perspective, but yeah, I think the things actually in that is, you know, it's, it kind of gives you a very simplified outlook of complex things in life, right? It's more like a keep it simple kind of a breakdown of things through his own stories or his own life experiences, right? And basically also to say how you could follow and how you could have a purpose, have a goal, right? How you can actually constantly try to improve yourself, right? I think one of the other most important thing is it used to be, it was very ideal for me as a beginner to start with because it gave me a lot of discipline and advice that actually I could action on or work on or improve on. So I think that's, that's a very simple book that I kind of like still. It's probably my go-to book as well.

Yeah, I think if you have a link for that later, maybe I can send that, put that in the show notes. Maybe our listeners like to—

I will. So that's one. There's another book that I'm doing a reread, which is Radical Candor as well, that I kind of, I kind of actually recommend this to our team as well while we are doing team building, because it kind of tells you how to be very open, very clear with the customers, when to say no and when to say yes, but, you know, kind of scenario. So that's, that's a good one from a professional perspective.

Thank you very much. So what's the best advice you have ever received?

Keep your head down, ignore the noise.

Yeah, that's also very straightforward, simple.

Yeah.

Yeah, it's crazy how much just in our world and AI and automation, I think we just look into our LinkedIn feeds, isn't it?

Sometimes AI itself is becoming the noise, right? For example, right? So I mean, nothing against it.

But, but yeah, I just got a final one for you, Vijay. If you could be an Olympic athlete, and of course, this is assuming you're not already an Olympic athlete, which sport would you choose?

I think I would prefer swimming, actually. Two reasons. One, I'm not great at it. So definitely this will give me an opportunity to improve. The second one, most importantly, is it takes you out of your natural element. Environment. What I mean by that is we are naturally surface-breathing people, you know. Put you into the water, you need to understand how to adapt, how to survive, breathe in that environment, right? And function and move forward and stay alive, stay afloat at the same time, right? So it kind of teaches you a lot of things. And, you know, and if you have to be an Olympic athlete or whatever, you're not just surviving, you're basically having to excel in it, right? I mean, you wouldn't reach that level without having beat quite a few people either in your country or across many countries to reach where you are. So not only is it the competitiveness, but to basically grow in, in a different environment, which is not yours in the normal perspective. So for that, you know, it requires a lot of discipline, a lot of dedication as well, right? And then a little bit of a grounding in your head. That's why the keep your head down, ignore the noise works very well in those environments as well. As well. So yeah, that's what I would say. Thank you.

Yeah, yeah, Vijay, it was a great pleasure to have you on the podcast today. Very insightful. Thank you.

Thank you, Sascha. Thank you, Arno, and thank you both for the opportunity as well.

Yeah, of course. Yeah, it's always, always nice to speak with others who are, as I mentioned in the beginning of the podcast, who are really as passionate about these topics as we are. Our listeners would like to get in touch with you, I'm sure, after that episode. What would be the best way to reach you?

I'm on LinkedIn. You see my name here. I think if you search Pundi, I don't think there is quite a few profiles there. Okay.

Yeah.

So the hit would probably be almost instantaneous. So yeah. Okay.

Perfect. I will put that profile link then also in the show notes. Yeah. And then, yeah, with that, we are coming to the end of the episode. Thanks again. Thanks for joining us today. And also a big thank you to all our listeners. We will be back as always with another episode very soon. And until then, let's automate it.

Thank you for the opportunity and keep smiling and keep rocking as always. Thank you, Sascha and Arno.

Thank you.

Thank you. Cheers. Bye now.