This season features conversations with key decision-makers who have shaped the evolution of today's leading technology platforms and ecosystems. We talk to C-suite executives, board members, investors, and others who must be brought into the platform journey.
In this episode, Avanish and Umesh discuss:
Host: Avanish Sahai
Avanish Sahai is a Tidemark Fellow and served as a Board Member of Hubspot from 2018 to 2023; he currently serves on the boards of Birdie.ai, Flywl.com and Meta.com.br as well as a few non-profits and educational boards. Previously, Avanish served as the vice president, ISV and Apps partner ecosystem of Google from 2019 until 2021. From 2016 to 2019, he served as the global vice president, ISV and Technology alliances at ServiceNow. From 2014 to 2015, he was the senior vice president and chief product officer at Demandbase. Prior to Demandbase, Avanish built and led the Appexchange platform ecosystem team at Salesforce, and was an executive at Oracle and McKinsey & Company, as well as various early to mid-stage startups in Silicon Valley.
About Umesh
Umesh Sachdev is the CEO and Co-founder of Uniphore, one of the largest AI-native, multimodal enterprise-class SaaS companies in the world. Sparked by his vision and focus to use AI technology to bridge the gap between humans and machines, today Umesh is recognized as an enterprise AI pioneer, bringing knowledge AI, generative AI and emotion AI into a single platform, allowing customers to harness AI’s powerful capabilities across voice, video and text-based applications. Known for his grit as a leader, his passion for customers and his deep understanding of technology, he is called upon to guide some of the world’s largest brands through their digital transformation. Umesh’s strong portfolio of patents serves as a testament to his innovative thinking and commitment to advancing AI technology.
As an international business leader, Umesh has been recognized with many awards including ‘40 under 40’ Bright Young Business Leaders in the Economic Times, ‘Next Generation Leader’ by Time Magazine, and previously, as an ‘Innovator Under 35’ by MIT Tech Review. Umesh is an alumnus of Jaypee Institute of Information Technology and an accomplished speaker and highly sought-after presenter.
About Tidemark
Tidemark is a venture capital firm, foundation, and community built to serve category-leading technology companies as they scale. Tidemark was founded in 2021 by David Yuan, who has been investing, advising, and building technology companies for over 20 years. Learn more at www.tidemarkcap.com.
00:00 Avanish: All right, everybody, welcome to one more edition of The Platform Journey. Today, another very special guest, Umesh Sachdev. Umesh is the CEO and founder of Uniphore. Umesh, welcome to The Platform Journey.
00:16 Umesh: Avanish, I’m excited to be here on the podcast with you.
00:20 Avanish: Thank you. First of all, thanks for taking the time. I think it’ll be a really fun conversation. And for full disclosure, I have been an adviser to Uniphore and the team for a couple of years, so just want to get that out of the way.
00:34 So, Umesh, you and your team have had a fantastic journey. I know a little bit about it. I don’t know how well our listeners know about it, so why don’t we just start there? Tell us a bit about your journey and the background of how Uniphore came about, and then we’ll get into the thick of it.
00:52 Umesh: Avanish, thank you for having me. And for the listeners, I want to start with introducing Uniphore, and then we’ll talk about how we got here. Uniphore is an end-to-end data and AI platform for large businesses. We serve a little over 2,000 customers across the globe, several of which are Fortune 500: the biggest banks, the biggest telecom companies, the biggest retail companies in the world, as they now look to build AI stacks within their businesses using their own data, generative AI models, and agents. They look at Uniphore for either our platform, which we call a business AI cloud, or our prepackaged set of agents in areas like marketing, customer support, sales, etc.
01:47 But it didn’t always start like this. Uniphore was founded in the year 2008 with a vision of conversational AI transforming how enterprises conduct their business. But there was no gen AI. There were no LLMs. There were no transformers. And seeing various generations of AI models since 2008 to now, Uniphore has constantly been at the front-row seat to see both how science is evolving – and in many ways a lot of people at Uniphore have contributed to that evolution of science – but more significantly, how do we make it work in the enterprise environment.
02:32 So our first avatar was building AI models for speech-to-text, text-to-speech, natural language. And even before gen AI, we found applications of that in enterprises, starting with customer service call centers. Then, as Covid occurred and most areas of business operation became virtual, we then extended our underlying platform of conversational AI to start to build new apps for sales teams, for marketing teams, for HR teams. Because everyone had gone remote, and they were conducting business on calls or Zoom meetings, etc.
03:18 And so, finally, when the era or gen AI and LLMs, the last two years ago, mainstay and hold in the world of consumer first and then enterprise, the fact that Uniphore already had a large distribution, thousands of enterprises who were using our AI applications – which were all built on a platform, but the platform was mostly only used internally and not exposed externally – gave us an opportunity in the new era to expose what only was available to Uniphore engineers, namely our Business AI Cloudplatform, and make it available to our customers.
04:06 So that’s how Uniphore has reached where it is today as a provider of the business AI cloud to thousands of businesses.
04:15 Avanish: So, again, I think it’s a fascinating story. It is similar to some other companies who built their own platform, drank their own champagne, as we would say, but didn’t necessarily see the need or the opportunity to expose it to their customers or maybe their partners, etc. And it sounds like you hit that point, and there were some outside-in accelerators, such as the pandemic and the greater digitalization.
04:44 What were the signals that you saw, that you said, hey, this is the time? Because that is not an easy decision, right Umesh? It’s a complicated business complexity, product complexity, distribution complexity. What were the signals to you, as the founder and the leader of the company, to say, hey, this is the time to open up that platform and bring it out and take the next step in the company’s journey?
05:18 Umesh: Before I talk about the motivation to open up, which was relatively recent, in the last couple of years, in Uniphore’s history, I want to build this up and talk through what was the motivation of the platform architecture in general.
05:32 Avanish: Love it. Even better.
05:35 Umesh: You know, working with AI models, and making them work in businesses, as we had crossed a couple hundred customers in our journey, it became obvious to us that for each of our customers to benefit from our AI applications, we would have to go and access that customer’s data, fine-tune our AI model, and then deliver a business outcome through these applications.
05:35 Avanish: Basically one on one, almost. One by one.
06:12 Umesh: One by one. And initially it was a lot of hand-to-hand combat. We were using some of our most talented, and therefore expensive, resources on data science, and top engineers to go into each customer’s environment. Because the customers weren’t ready for AI. They probably still aren’t. But about six, seven years ago, they didn’t even have empathy to understand what does it take to make an AI application work in the environment.
06:42 So as we crossed a couple hundred engineers, it was necessity. We had run out of smart data scientists to throw at each customer’s side. And so we started to look at RAG, or what is, in general, knowledge extraction. We started to look at creating automated data pipelines. We started to look at running multiple AI models on a singular platform architecture. Because no two customers were going to share data. No two customers were going to share AI models.
07:14 And all of that to say, we started to build this platform-like tooling to make our implementations easier. And management of customers easier. Because the scale was forcing us to do it. That translated to – I vividly remember late 2022, early ’23 – two of Uniphore’s most important customers, almost in the same time period, because we had a great relationship with them – one is one of the biggest banks in the whole world, and the other is one of the largest telecom companies in the whole world – with both of them, the CIOs, I had developed a personal rapport. Uniphore was already working with them for a few years.
08:01 I remember getting called in, or summoned, in person into both of their offices in a two-month gap. And they both were delivering a similar message to me. And the message was politely saying, Umesh, we are proud of how Uniphore has grown with us. Your AI applications have done really well. And because we care about companies like you, we wanted to do this in person. We are beginning to sense there’s going to be an expiry date to our contract with you.
08:30 Avanish: Hm. Not what you want to hear, as a CEO.
08:32 Umesh: And, by the way, for the listeners to recognize, these two companies were 10% of our revenue. Two of our largest accounts. So after I had recovered from hot flashes and feeling like the world is going to collapse and gathered my composure, I was able to ask them why. Have we done anything wrong? I haven’t heard of any outage on the platform. I can fix anything. Can we talk about this?
09:04 And they said, listen, our direction of travel post gen AI is shifting. We will move from an architecture of hundreds of individual SaaS apps, of which Uniphore was a part of, to an architecture of a horizontal data and AI platform on which AI agents will be built across the whole company. And that will negate the need for several SaaS applications.
09:33 So I said okay, how imminent is this? And the answer was, well, it could take a couple of years, could take slightly longer, but we are very firm in the direction of travel.
09:42 Avanish: And, to be clear, this is just a couple of months after ChatGPT had come out.
09:45 Umesh: A couple of months.
09:46 Avanish: We’re not talking a year or two. These are forward thinkers.
09:51 Umesh: These are absolutely the most premier adopters of any technology in AI, these kinds of firms, I would say generally Fortune 100 US, have really taken the lead across the globe. So these companies have done early pilots in partnership with their hyperscalers that used either the Google model, which was called Bard at the time – this was pre Gemini, or ChatGPT. And they said, look, it’s early days, but we know now this is going to happen.
10:19 So I said, look, if it’s at the very least two years out, maybe more, really why am I here? Why did you call me here? And that’s what the conversation led to. They said, the reason you’re here is because, for a couple of years, you’ve been trying to tell us you have a platform. And we really care about your application. But now that we’ve done in-house pilots, we know gen AI works. But it took us six months to do one use case. If you need velocity, if you have to roll out gen AI company wide, have lots of agents, lots of fine-tuned models, we can do this one POC every six months. We need a platform that’s at scale and mature.
11:02 By the way, we also need a platform which is independent from any one cloud environment. We need the ability to feel like we can run it anywhere. Whether it’s premise or any cloud, multi-cloud. And you’ve been trying to get our attention by saying you have a platform. Is it true that you have a few thousand customers running on a single platform? And I said yes. Next question was, is it true that no two customers of yours share their data, which means you’re running multiple data pipelines on a single platform? The answer was yes.
11:38 And finally they said, is it true that no two customers share their models, which means you’re running multiple fine-tuned models on a single platform? The answer was yes. And so they said, that’s why you’re here, Umesh. If you and your company are willing now to open up your platform – forget about the applications you guys have built on it and we use and we like. If you give us your platform and allow us to build our own applications or AI agents, as we now know them, then Uniphore is going to be a very important part of our future.
12:14 And it was having these deep customer relationships, Avanish – as I look back in retrospect and think about what helped us with this decision – customer intimacy, having their trust, and having a keen listening ear, that gave Uniphore probably a six- to eight-month head start from the rest of the world. The fact that we already had a lot of their platform built for ourselves. But we were able to launch it with some of the biggest enterprises before even the hyperscalers and the likes of Bedrock from Amazon or what’s now called Legion Space or Vertex from Google and similar platforms emerged, Uniphore got a head start.
12:58 I think that’s, when the history book of Uniphore is written, that would be a pivotal moment of how some of our most important customers told us that we should be moving in this direction.
13:14 Avanish: What a great – I mean, I asked about signals. And what better signal than your customers demonstrating trust, confidence, intimacy as you called it, and saying, hey, look, the world’s going to change, is changing, probably faster than any one of us had ever seen it change. And we want you with us on that journey. And, by the way, if you decide not to be with us on that journey, then the contract could end. But that is not why we called you here.
13:45 I mean, talk about powerful validation, right? So amazing context. But as we know, the transition into something like that, where you’ve built the tooling for yourself, you’ve built primarily an application company, and now you come back from these trips and say, folks, we’ve got a new business plan. We’ve got a new technology strategy. We’ve got a new way that we’re going to go to market. We’re going to become a platform. We’re going to expose our platform.
14:19 That requires not just you shifting your gears. You’re already a sizable company by this point. You need to start shifting the whole company in that direction. Talk a bit, what are the attributes of the team? And think as broadly as you could, from board members and investors – you have some amazing board members, who I know – all the way to the team itself. What does that transition look like? And how did you manage, are you managing, that expansion of the business from where you came to this next generation?
15:02 Umesh: The last two and a half years, to the outside world might look very exciting, were probably my hardest years as CEO of the company. And that’s to amplify the point of these platform shifts, even for a company that already had a platform, like Uniphore, was just a huge, humongous, open-heart surgery on the whole company.
15:57 And here’s why. It wasn’t enough that we had most of the tooling built up, the platform built up, the building blocks. The whole company, up until that point, was built to optimize selling of AI applications. Our buyer wasn’t a technical buyer. Our buyer wasn’t the CIO – up until then. Our buyer was line of business. We were selling business outcomes.
16:24 And remember I said the buyer didn’t have empathy to what it took to deliver. They just wanted to buy business outcomes.
16:29 Avanish: Get it done.
16:31 Umesh: This was also at a time where we had raised a large Series E round. We were late-stage. We were coasting to a path of preparing ourselves for an IPO down the road. And when this shift occurred, lots of things changed very rapidly for us. Our buyer, overnight, was going to become the CIO or the IT organization, which is going to have very strong technical ways of evaluation.
17:01 Second, our product mindset, or engineering mindset, now we were no longer building products for customer support or marketing or sales. We were building products for developers. Sophisticated developers, but developers. And, by the way, on the macro, this was also coinciding with the US Fed deciding to take interest rates from 0% to almost 5%. Simultaneous to this platform and gen AI shift.
17:32 Why is that important? Because I had to go into a re-acceleration of R&D investment cycle. From a company who was preparing for an IPO, driving towards profitability, we had to throw that rule book out of the window and say, heck no, this is the time to shift gears fast. We have an opportunity. We are in the lead. Press the accelerator again.
17:56 But capital wasn’t free at this time, as it was for the last couple of years. So I had to relook at the entire talent of Uniphore, close to 900 people, and really, just to myself, go on a spreadsheet and say who’s ready for the shift. Engineering, product, sales, marketing. Who needs some coaching? Who needs help? And what parts of the company that we had built to sell products to line of business are not going to be relevant anymore? And that part of the company needs to be replaced by people who have the muscle memory of knowing how to build and sell products to IT.
18:37 So it’s taken a whole DNA shift of Uniphore to build a platform that developers are going to use, which are not Uniphore employees. It’s a big shift. They will not cut slack. They want the platform to have all the bells and whistles, and the stability, and the performance. They won’t pick up the phone or walk up to your desk if it’s not working. Which used to be the case with Uniphore’s own employees using the platform.
19:04 And we had to seed the market with some initial ideas of killer apps. Our own killer apps that would motivate them. Then we had to learn how to reposition Uniphore. Which, up until that point, had gained a good reputation as a conversational AI, leader of some magic quadrants, servicing customer care, to becoming a horizontal, enterprise-wide AI platform. That was a positioning and marketing effort. That was an engineering effort. And then have sellers who can go and speak the CIO’s language.
19:42 Because, as you know, in building ecosystems, until the company learns how to do it themselves, the partners come and scale. So I would say the journey has been arduous and hard. We are on the other side to report a big 3X jump in two and a half years of our topline and great success. But it was a near-death experience going through all of this. And one that I’ll cherish for a very long period of time.
20:12 Avanish: As you should. And what I enjoy about you is, you always still do it with a smile on your face. So even with all the hard work. And, by the way, it does bring a memory to me, which is that was a similar transition we had to do at Salesforce 15 years ago. Which was a single-product company in sales, and we were going to be a platform. And I think this AI wave is similar but even faster. And I think trying to transition established companies with hundreds if not thousands of customers, and trying to make that shift, it is not for the faint of heart. So I admire you and the team a lot for doing that and continuing to deliver a huge amount of value.
21:01 So you brought up ecosystem. And one topic we always try to dive into, because it doesn’t have a single answer, is platforms and ecosystems, are they two sides of the same coin? Are they two different things? How do you think about that, Umesh? How do you feel about platform strategy versus ecosystem strategy? From your personal point of view with these experiences, and frankly from Uniphore’s perspective.
21:32 Umesh: So what’s interesting to me, Avanish, is, by training, I’m a computer science engineer. That’s why I founded a tech company. But over time, as a CEO, I’ve become generally a pretty good commercial sales-oriented CEO. And so that vantage point gives me this insight.
21:55 Generally speaking, the word platform is born in the technical side of a company. Engineers and product leaders start to use the word platform before the rest of the company. So it feels like it’s a technical project. The word ecosystem is born in the GTM side of the house and feels like salespeople and then marketing people start to talk about the ecosystem before the rest of the company.
22:25 But as CEO, I can tell you, they both don’t go separately. They’re both parts of the same coin. Because I remember several quarters ago, in a board meeting, one of my board members said, Umesh, a platform is really not a platform until what happens? And I said, until other people are building things on it. And that’s where the ecosystem needs to come in.
22:49 But until we have inspired other tech companies in adjacent spaces, similar spaces, and eventually competitors, to use our underlying toolkit, framework, namely platform, as a way of them building applications, agents, that they can go and sell to their customers, it’s really not a real platform in the world.
23:16 And so I often think about both of those simultaneously. I still struggle to get my product people to think about ecosystem when they’re designing roadmaps and my salespeople to think about product features when they’re striking partnerships. But the magic happens when they both can be brought together.
23:35 Avanish: I love that. And I think it is… I certainly espouse that view. But I think getting the alignment across product, marketing, sales, customer success, etc., all of this together drives outcomes, drives customer value, retention, etc. It takes a while. So thanks for sharing that point of view.
24:04 I know you’ve recently announced some inorganic growth moves, which I think are quite well tied to this platform strategy. Talk a bit about what you’ve seen and done on that front and how you see those deals bringing additional value to both Uniphore and to the customers.
24:27 Umesh: Well, Avanish, the primary motivation of our two most recent acquisitions which we announced, Orby.ai and Autonom8.io, both companies AI native, one in a foundational model space – they developed a large action model, the other in enterprise Agentic Workflow space driving automation, very complementary to our platform strategy.
24:55 The primary motivation behind both of those was essentially to augment our AI talent and bring a lot more horsepower as we continue to build and compete with some of the biggest companies in the world. I have seen some pallet wars in my CEO career, but I’m probably seeing something of this magnitude and intensity for the first time. Where lots of tools are being used, a lot of money, a lot of resources, higher acquisitions.
25:32 And it is really a scarce talent pool right now. Very few people in the world today have any experience of either fine-tuning or building foundational models, ground up. And even rarer few have learned the art and skill of deploying value to these models and agents within. I truly believe, in the next two or three years, there’ll be a lot more people as more companies scale up and get experience. So we were looking for talent augmentation of a very scarce resource, which is AI talent. And these acquisitions have delivered exactly that. And we’re very excited to welcome those teams into the Uniphore fold.
26:19 However, when I think about M&A as it relates to platform strategies, I think a platform architecture first narrows the aperture for the types of M&A that companies can do. On the flip side, if done right and done well, there might be slimmer pickings, but the outcomes of those acquisitions are much more amplified if it’s a platform architecture versus not.
26:49 Let me explain what I mean by that. And I’d love your thoughts on this as well, because a lot of what I’m saying, I and Uniphore have learned from you in the last couple of years. But from my lens, because we are on a platform architecture, we have to be extremely selective in bringing on technologies or products which have to have nothing but a 100% alignment with our architecture. Because anything lower is a rebuild. And we cannot afford our platform to have multiple source codes.
27:26 So it’s a single source code. The architecture has to align. Which means I might fall in love with a company, a team, but if their architecture doesn’t match ours, it’s a no-go. Which makes it slimmer pickings.
27:40 On the flip side, if we do find those diamonds in the rough, where we like the culture, we like the team, we like the product – revenue is almost immaterial in those cases, because our own distribution is doing well at this moment – and if the architecture of the platform matches, it’s an almost instant unlock of newer features, newer capabilities, and therefore higher volume share from my existing customers.
28:10 So that’s been my observation of M&A as it relates to platform strategies. But I’d love to hear your thoughts on this one.
28:20 Avanish: I mean, look, I think your summary is spot on. I think there is the acqui-hire in the traditional way. And I’m old enough to remember when acqui-hires used to be single-digit millions. And now there is multi-billions happening. So the world has changed dramatically. But those acqui-hires really are, you’re bringing just the talent.
28:41 I think what you’re describing is much more than that, which is, hey, there are gaps that we can accelerate and close by bringing in the right technology architecture without having to rewrite, re-platform. And, by the way, we also get the talent who’s done it before. So it is, I think, being judicious about it and being thoughtful…
29:06 I have been in places where I’ve been part of the team that evaluated acquisitions with a pretty much preconceived notion, whether at the app level or the platform level, that it would be rebuilt. Because of a variety of historical, cultural, technical, whatever reasons. But that is expensive. That takes time. And you’re not getting the accretive impact as soon as you would like to. So you have to build that into your model, that this is going to be a medium- to long-term acceleration, but we’re now going to close that gap.
29:45 I think having the luxury of a smaller aperture, in some ways, and saying, hey, we’ll only pick and choose the ones that fit naturally and can almost plug in quickly, I think that’s a very smart way to think about it.
30:05 Very good. So let’s switch into one final topic. We talked a lot about Uniphore. We talked about your experiences, which again I think are just fantastic. Let’s share a bit of what those lessons are to some of your fellow peer CEOs, peer CXOs, board members. Again, you’ve talked a bit about it – this is not an easy journey – how alignment becomes a key issue. We talked a bit about how we have to identify which skills could scale to the next level, which skills might require coaching/training, and which skills may not work.
30:47 What are some approaches that you’ve taken that, if you were to advise someone, say hey, here’s one or two or three lessons, if you think about this platform plus ecosystem strategy, that they should adopt as good lessons, and perhaps one or two things that you say, you know, if I had to do it again, I might do differently?
31:12 Umesh: Yeah. So you’re leading me to reflect on what did we learn, and if I were to redo it, what would be my rubric. And there’s three things that come to mind, Avanish.
31:26 The first one is a framework that I certainly saw for the first time from Inreason, and I think they were the ones who put this out, which is when you think about a startup, or even a new product in a larger company, it’s very important to think about it in the lens of is it a feature, or is it a product, or is it a company? And I think that framework, from a founder CEO’s lens, has constantly forced me to evaluate what is our relevance to the world? Are we truly a company, or are we a product? Or are we merely a feature in a larger ecosystem that belongs somewhere else?
32:14 And as someone who always has a long-term ambition for Uniphore, I’d like Uniphore to be a stand-alone public company, a large-cap company, and I’m not looking for potentially a M&A-type outcome. If my assessment leads me to believe we are falling in the feature situation, or even a product situation, but not a company or a platform situation, I’m always paranoid about that.
32:44 And so, for a leader, for my peers, to develop a framework that leads to paranoia is the first thing.
[Laughter]
32:54 Because each time complacency sets in, we could be doing really well from a go-to-market standpoint, it could be a very sweet run from a growth standpoint, but we shouldn’t get complacent about what is our place in the broader tech landscape, tech ecosystem. That’s the first thing.
33:13 Once the paranoia sets in, and there is a desire from a leadership standpoint to develop a platform mindset, or enhancing the platform mindset, then, from a talent standpoint, I place a lot of premium on people who I think – I call them system thinkers. Whether they’re engineers or product people or go-to-market leaders, not everyone is able to think at a broader systemic level. It’s much easier to think more focused minutiae of solving today’s problem in your silo.
33:58 But if you’re not taking a systemic lens, you’re probably going to make decisions of either the technology side or go-to-market side, which might become very hard to unwind when you’re forced to make that platform shift. So placing a high premium, and especially surrounding yourself with leaders or system thinkers, makes the journey toward a winning platform much easier.
34:25 And then finally, as my journey has been evidenced, there is absolutely no substitute to staying very close to customers and listening keenly. I often tell my team there was only one Steve Jobs who knew before the world knew what it wanted. All of us mere mortals, we have to learn from the market, from the customers. And that is the best way of developing a platform roadmap and ultimately a winning strategy.
35:05 Avanish: That is such a brilliant piece of advice, Umesh. All those three points. Be paranoid. Have talent that has a systems orientation, because that again will allow you to morph and think big picture. And the customer piece. Again, a lot of people, frankly, in their arrogance, will say, oh, I know better. But there was only one Steve Jobs. Maybe there’s one other one out there right now, but there’s very, very few people who can pull that off.
35:39 And like you gave the example of your telecom and banking CIOs. They’re telling you where to go, right? And once you see that pattern, shame on you if you don’t listen to that.
35:53 One final question, Umesh. I think, again, this has been, as expected, such a delightful and insightful conversation. Success metrics. I know you’re very data driven, you’re very outcomes oriented. How do you know when things are working? How do you know, as you go through these changes, how can one track… These are long, again systemic thinking requires also thinking about systems-level outcomes and metrics, and those don’t happen overnight.
36:29 How do you know that you’re in the right direction?
36:32 Umesh: This is a good topic to probably tie our entire conversation in a bow. Because as I looked at the planning for the current fiscal year of Uniphore, fiscal year ’26, this was the second year of a big platform shift that we had done. I knew a thing or two more about how the adoption pattern is emerging. And in the beginning of the year I was very thoughtful on what’s the right goal to set for the business, which will tell us that we are making progress in achieving platform leadership and not just, of course, revenue and all those things matter.
37:21 So I looked at, is revenue the right metric? Adoption, is that the right metric? Number of use cases, number of partners. And I said those are all the outcomes to something else. And those almost seem like symptoms of a different root cause. And so the metric that I came up with for Uniphore, and I started to rally the whole company around it, is that our core metric, our number one measurement for this year, is the five-by-five metric.
37:57 So what is this five-by-five? We came up with this relevant to Uniphore. Something generalized might apply to other companies as well. I said, look, by the end of this year we’re likely to have somewhere between 2,500 and 3,000 customers. Our goal is to grow our topline by 85%, all of those goals. But I’d like to exit the current financial year with a five-by-five outcome.
38:26 Five large enterprises and five either GSIs or consulting firms for whom the Uniphore business AI cloud is their SLM and Agentic factory. And I said the operating word is factory. How will I define that? It wouldn’t be enough if those five large enterprises or five large GSIs or consulting firms have built some agents on us or fine-tuned some SLMs on us, SLM being small language model.
39:00 But I want those five and five, every week, to be fine-tuning some models and building some agents. And if you now distill that definition, for that every week something of this magnitude to happen within these companies, which means hundreds of users within those companies should both be conversant with the platform and have found business value in newer and newer agents, newer and newer fine-tuned models.
39:35 If you distill that further, for that to happen, first we need to show them with the initial seeding of use cases and deliver big ROI, convince their boards, convince their management. And, by the way, make the user experience so simplified that I go beyond the remit of IT and technology people in these companies. Because those are not hundreds. We need hundreds of users. I need to get into the business user group.
40:04 Which means we are aiming to get a recruiter in HR, an accountant on the finance team, a paralegal in the legal team, to be fine-tuning models and building agents. And forcing ourselves to say, therefore, what kind of user experience should we have? If we start to teach them prompt engineering and rates and biases, this will never happen.
[Laughter]
40:27 So the metric of hyperadoption, led in different things, is really about simplifying user experience, creating those flywheel effects of big business outcomes, creating community engagements, and then unleashing the power of the platform. So for us, that became this five-by-five. It’s easy to understand. Everyone in the company, if you stop them in the corridor and say what’s your number one goal this year, they’re now trained to say it’s five-by-five. And that’s how we are measuring ourselves this year.
41:03 Avanish: Love it. I really, really love that. Because I think having pithiness in that, but something that’s very powerful, is extremely important. And then each individual, frankly, no matter what their role is – whether they’re an engineer, they’re a customer success person, they’re a partnership person – they can see where their contribution, their role, fits into that. Because, frankly, in that mindset, everybody plays a role. So that is fantastic.
41:35 Umesh, any final words? What a delightful conversation, but any final words?
41:39 Umesh: Well, first of all, again, I really enjoyed this conversation, this podcast. I want to thank you, you being Uniphore’s adviser, our thought partner, our guide for the last couple of years as we’ve done this platform journey.
41:52 When I think about rarefied atmosphere, just like the AI talent, if I scan Silicon Valley, the number of people who have not only done this platform journey once but several times over, at Salesforce, ServiceNow, HubSpot, Google, and now be willing to pay it forward and share all those learnings with companies like Uniphore, that’s very few. And you know you’re in rarefied atmosphere. I’m very grateful to have you associated with Uniphore, and hopefully the journey continues to be very exciting from here on.
42:32 Avanish: Oh, that is very, very, very kind of you to say. And I much appreciate that. But I think, again, what you guys are doing is pretty spectacular. So it’s just fun to be a bit on the sidelines and cheer on. So much appreciated.
42:46 Well, thank you, Umesh Sachdev, CEO of Uniphore. Thank you for joining us on this leg of The Platform Journey.
Umesh: Thank you, Avanish.