theCUBE + NYSE Wired: Mixture of Experts Series | Ginniee Singh, SpikedAI

Ginniee Singh, SpikedAI

In this theCUBE + NYSE Wired: Mixture of Experts segment from the New York Stock Exchange, theCUBE’s John Furrier sits down with Raj Verma, CEO of SingleStore, to unpack how the intersection of technology and finance is shaping enterprise strategy. Verma shares why SingleStore is “on course” for the public markets, reflects on brand-building through the company’s partnership with golf Hall of Famer Padraig Harrington and connects that ethos to how SingleStore helps organizations fix struggling data “swings.” The discussion zeroes in on what’s next as Wall Street watches the AI infrastructure buildout: after chips and systems, the software and data layers set the pace for value creation. Verma outlines why enterprises must modernize “brown” data estates into “green” ones to safely bring corporate context, governance and compliance into LLM workflows via RAG – and why commoditized data-at-rest puts the advantage at the query layer that unifies data in motion with data at rest. He predicts agentic AI will gain reasoning capabilities in roughly 18 months, cites industry indicators like Google reporting ~25% of its software now built by AI and argues that high switching costs will give way to disruption as buyers reassess legacy vendors. The conversation closes with concrete momentum: ~33% YoY growth, ARR in the ~$135M range, gross dollar retention ~98%, cloud NDR ~130, ~50% of business now in the cloud, landing ~3 new customers per day, a path to cash-flow breakeven in the next two quarters and a teaser for AI-related announcements in the next two months. Listeners will find notable stats, real-world use cases and forward-looking views on how databases power reliable AI at enterprise scale.

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Ginniee Singh

Advisor

SpikedAI

play_circle_outline Trust and Transparency: Ginniee Singh on AI's Impact in Sales and Connecting with Gen Z in Advisory Roles

play_circle_outline Spiked AI aims to change traditional sales processes and reduce cognitive workload.

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Ginniee Singh, SpikedAI

Ginniee Singh

Advisor SpikedAI

search

>> Hello, I'm John Furrier, your host of theCUBE here in our CUBE New York Stock Exchange Studio. Of course, we have our Palo Alto Studio connecting Silicon Valley and Wall Street. Our two studios are access points for entrepreneurs, builders, advisors, and leaders. This is our Mixture of Expert series. Ginniee Singh is here. She's an advisor to an emerging venture and opportunity, Spiked AI. Ginniee, great to see you. Thanks for coming in to our NYSE studio.

>> Thank you for having me. Such a pleasure to be chatting with you.

>> So last time we saw each other, we were having a glass of wine at your winery you're a member of. And we were talking about all the endeavors you're doing. Talk about this new opportunity and what you're working on. I think this is compelling.

>> I can tell you there is an overall moment. And coming from the high-tech organizations, I think that's what I can bring it towards the working with the Gen Zs. I'm really passionate about how I need to groom these Gen Zs, especially I see they're feeling these days. And that's what has actually driven my thought process to get into the advisory roles where I can talk to them and be as I would say, transparent as possible, build that trust with them, and take them to the next level of evolution. So as part of the Spiked AI, what we are trying to do is we're trying to change the sales DNA. Sales are still being run in the traditional ways and with spiked AI, what I am trying to do is, I'm trying to reduce the cognitive workload. It's a simple conversation like you and I are having, but a conversation with an intent. It is, how do you bring in the conversational side of the things, the computational side of the things, and also the context under that? That's what we are trying to change. What happens is when I groom my teams all the day, as sales, what happens is we will forget something. We will realize that, "Oh my God, I did not answer this question properly." So, it's always an after effect of these things. And what happens is during these conversations with the customers, within those 30 minutes, you want to maximize on your revenue potential. You want to give them, the customer, the feeling that you are trying to address their questions as . So, that's what I am trying to do. I'm trying to give the customer the best feeling so that the customer stays with me in this conversation and doesn't go out of it. And I'm able to update my CRMs. Sometimes I call these CRMs as the iguanas. And it just keeps adding the workload as we go back, because the quality of input is going to be the quality of the output. So, that's where I am today.

>> That's awesome. And you know what's great is that part of this conversation is about the generative AI opportunity and the Gen Zs are native to that. How is AI playing into it? Because you're seeing people look at platforms and they're building their own. So, how are you looking at the technology piece of it? And how are the young builders that you're mentoring and advising thinking about that?

>> I think they come with no boundaries. They want to get to all these tools, experiment with that, and then they forget what happens. That's where I come in. As an industry leader bringing in that expertise to them, we bring the industry insights, they bring the technology insights. So it is the meeting of minds that happens out there because they come up with no boundaries, as I said. They will come and challenge me in every aspect and say, "Hey, I think I can solve for this problem." And that is the beauty of this, is that how fast you can do these things, how intelligent you can do these things, and break those barriers out there.

>> Yeah. Talk about speed, talk about the speed of execution. Because we are living in an era where the humans are driving, the human in the loop with AI, there's a human layer. CRM is an old mechanism, but these all kinds of emotional context, customers deserve better than a database.

>> Totally. The way I'm trying to position this is that what happens is... And I'll give you an example of my day-to-day. I go in, input the data in the CRM, somebody will go and read it, and it'll be outdated very soon. What happens is we need to have these real-time conversations where we are inputting all these real conversations and converting them into conversions. That is what the CRM beauty is. CRM is your data source, but what happens in the intelligence layer and the conversations like these is, how does the CRM get updated in real time, is really important. So with Spiked AI, what we've done is we've been able to solve for these problems. And it's actually be prodding me into ask me these questions or somebody else has a different question. It's prodding me. It's actually helping me simulate the environment before, and then come up with the real avenue. And then take it forward and update that information in the CRM in real time.

>> I love the name of the company, Spiked AI. It's like football game when they get in the end zone, they spike the ball. Or you've heard people, "Don't spike my drink with too much alcohol." I mean, it's like the word spike is an action word of some sort of action. How is the AI working? Can you share your thoughts on how you see AI emerging in this? Because as more data comes in, that's an intelligent layer. You mentioned that. Every sales rep wants to spike the ball in the end zone after a touchdown or a goal.

>> I would say how AI is working. AI is actually helping me do my things in real time, bring that productivity into that. But at the end of the day, it needs to have a reasoning power onto that. And that's where I think we are all going wrong. We're trying to just go after the speed and productivity. We are not trying to use AI in the right way by which it can reason my aspects to it. And being a mathematician and a statistician, I think modeling comes naturally to me. And that's what I am trying to do, is build all these LLMs and the SLMs onto that where we can reason with AI. And it helps me be better at what I do.

>> Ginniee talk about the project. Where is the status? Can you share the evolution? Is it out there? Are people using it? Is it funded? What's some of the data behind the venture?

>> Oh my God, John, you've actually stolen the words out of my mouth. It is at a very nascent level. It is at the minimum lovable product level. It's in the hands of few customers who are actually trying and who are going to be our design partners. And what I'm hearing from them is that it is reducing the cognitive workload. It is a game changer. Regarding the funding process, we've just started to kind of kick off some conversations. We want to get into the funding level so that we can bring this product, test it and try, and bring it in front of our users as much as we can.

>> How do people get involved? What are you looking to do? What can people do? Where can they go? Share some coordinates and share what you guys are looking to do. And how do people get engaged?

>> That's actually a thoughtful question. I would say regarding the engagement, my idea is that we should get this in front of as many users as possible, and as many CROs as possible because their revenue offices all are worried about revenues. And in today's world, what happens is each rep needs to be like your top performer. What happens is only 25% of the team performs at that level, and there are many reasons to that. I wouldn't get into those details just yet, but what we want the users is, get into the hands of the CFOs, get into the hands of the revenue officers. Think like a CEO. That's what my mantra is. And I want each rep, each CRO to think like a CRO. So we want more and more users getting engaged and sharing their feedback process, so we're building that loops as we go along into this conversation.

>> Ginniee, great to see you. Thanks for sharing on theCUBE here in our NYSE studios. And next time in Palo Alto, come visit us. We'll get you back on. But looking forward to collaborating more with you and your project. And thanks for spending the time.

>> Thanks for giving me this opportunity to chat with you, John. It's always amazing to meet. And also I think that wine conversation is actually turning into Spiked AI now.

>> All right, it's great to have you on. Silicon Valley to Wall Street. That's theCUBE. We are connecting the world from builders, early stage, to pre-IPO. We're bringing everyone into the Mixture of Expert series. Thanks for watching.

Ginniee Singh, SpikedAI

search

>> Hello, I'm John Furrier, your host of theCUBE here in our CUBE New York Stock Exchange Studio. Of course, we have our Palo Alto Studio connecting Silicon Valley and Wall Street. Our two studios are access points for entrepreneurs, builders, advisors, and leaders. This is our Mixture of Expert series. Ginniee Singh is here. She's an advisor to an emerging venture and opportunity, Spiked AI. Ginniee, great to see you. Thanks for coming in to our NYSE studio.

>> Thank you for having me. Such a pleasure to be chatting with you.

>> So last time we saw each other, we were having a glass of wine at your winery you're a member of. And we were talking about all the endeavors you're doing. Talk about this new opportunity and what you're working on. I think this is compelling.

>> I can tell you there is an overall moment. And coming from the high-tech organizations, I think that's what I can bring it towards the working with the Gen Zs. I'm really passionate about how I need to groom these Gen Zs, especially I see they're feeling these days. And that's what has actually driven my thought process to get into the advisory roles where I can talk to them and be as I would say, transparent as possible, build that trust with them, and take them to the next level of evolution. So as part of the Spiked AI, what we are trying to do is we're trying to change the sales DNA. Sales are still being run in the traditional ways and with spiked AI, what I am trying to do is, I'm trying to reduce the cognitive workload. It's a simple conversation like you and I are having, but a conversation with an intent. It is, how do you bring in the conversational side of the things, the computational side of the things, and also the context under that? That's what we are trying to change. What happens is when I groom my teams all the day, as sales, what happens is we will forget something. We will realize that, "Oh my God, I did not answer this question properly." So, it's always an after effect of these things. And what happens is during these conversations with the customers, within those 30 minutes, you want to maximize on your revenue potential. You want to give them, the customer, the feeling that you are trying to address their questions as . So, that's what I am trying to do. I'm trying to give the customer the best feeling so that the customer stays with me in this conversation and doesn't go out of it. And I'm able to update my CRMs. Sometimes I call these CRMs as the iguanas. And it just keeps adding the workload as we go back, because the quality of input is going to be the quality of the output. So, that's where I am today.

>> That's awesome. And you know what's great is that part of this conversation is about the generative AI opportunity and the Gen Zs are native to that. How is AI playing into it? Because you're seeing people look at platforms and they're building their own. So, how are you looking at the technology piece of it? And how are the young builders that you're mentoring and advising thinking about that?

>> I think they come with no boundaries. They want to get to all these tools, experiment with that, and then they forget what happens. That's where I come in. As an industry leader bringing in that expertise to them, we bring the industry insights, they bring the technology insights. So it is the meeting of minds that happens out there because they come up with no boundaries, as I said. They will come and challenge me in every aspect and say, "Hey, I think I can solve for this problem." And that is the beauty of this, is that how fast you can do these things, how intelligent you can do these things, and break those barriers out there.

>> Yeah. Talk about speed, talk about the speed of execution. Because we are living in an era where the humans are driving, the human in the loop with AI, there's a human layer. CRM is an old mechanism, but these all kinds of emotional context, customers deserve better than a database.

>> Totally. The way I'm trying to position this is that what happens is... And I'll give you an example of my day-to-day. I go in, input the data in the CRM, somebody will go and read it, and it'll be outdated very soon. What happens is we need to have these real-time conversations where we are inputting all these real conversations and converting them into conversions. That is what the CRM beauty is. CRM is your data source, but what happens in the intelligence layer and the conversations like these is, how does the CRM get updated in real time, is really important. So with Spiked AI, what we've done is we've been able to solve for these problems. And it's actually be prodding me into ask me these questions or somebody else has a different question. It's prodding me. It's actually helping me simulate the environment before, and then come up with the real avenue. And then take it forward and update that information in the CRM in real time.

>> I love the name of the company, Spiked AI. It's like football game when they get in the end zone, they spike the ball. Or you've heard people, "Don't spike my drink with too much alcohol." I mean, it's like the word spike is an action word of some sort of action. How is the AI working? Can you share your thoughts on how you see AI emerging in this? Because as more data comes in, that's an intelligent layer. You mentioned that. Every sales rep wants to spike the ball in the end zone after a touchdown or a goal.

>> I would say how AI is working. AI is actually helping me do my things in real time, bring that productivity into that. But at the end of the day, it needs to have a reasoning power onto that. And that's where I think we are all going wrong. We're trying to just go after the speed and productivity. We are not trying to use AI in the right way by which it can reason my aspects to it. And being a mathematician and a statistician, I think modeling comes naturally to me. And that's what I am trying to do, is build all these LLMs and the SLMs onto that where we can reason with AI. And it helps me be better at what I do.

>> Ginniee talk about the project. Where is the status? Can you share the evolution? Is it out there? Are people using it? Is it funded? What's some of the data behind the venture?

>> Oh my God, John, you've actually stolen the words out of my mouth. It is at a very nascent level. It is at the minimum lovable product level. It's in the hands of few customers who are actually trying and who are going to be our design partners. And what I'm hearing from them is that it is reducing the cognitive workload. It is a game changer. Regarding the funding process, we've just started to kind of kick off some conversations. We want to get into the funding level so that we can bring this product, test it and try, and bring it in front of our users as much as we can.

>> How do people get involved? What are you looking to do? What can people do? Where can they go? Share some coordinates and share what you guys are looking to do. And how do people get engaged?

>> That's actually a thoughtful question. I would say regarding the engagement, my idea is that we should get this in front of as many users as possible, and as many CROs as possible because their revenue offices all are worried about revenues. And in today's world, what happens is each rep needs to be like your top performer. What happens is only 25% of the team performs at that level, and there are many reasons to that. I wouldn't get into those details just yet, but what we want the users is, get into the hands of the CFOs, get into the hands of the revenue officers. Think like a CEO. That's what my mantra is. And I want each rep, each CRO to think like a CRO. So we want more and more users getting engaged and sharing their feedback process, so we're building that loops as we go along into this conversation.

>> Ginniee, great to see you. Thanks for sharing on theCUBE here in our NYSE studios. And next time in Palo Alto, come visit us. We'll get you back on. But looking forward to collaborating more with you and your project. And thanks for spending the time.

>> Thanks for giving me this opportunity to chat with you, John. It's always amazing to meet. And also I think that wine conversation is actually turning into Spiked AI now.

>> All right, it's great to have you on. Silicon Valley to Wall Street. That's theCUBE. We are connecting the world from builders, early stage, to pre-IPO. We're bringing everyone into the Mixture of Expert series. Thanks for watching.