← The Digital Executive
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- [00:00]
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- [01:09]
Podcast Host
Welcome to Coruscant Technologies, home of the Digital Executive Podcast. Do you work in emerging tech? Working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.corazant.com brand welcome to the Digital Executive. Today's guest is Alex Roy Rajan. Alex Roy Rajan is the founder and CEO of SalesBox AI, a go to market advertising platform designed to drive pipeline and revenue growth through AI powered engagement. With a vision to transform how companies detect demand and orchestrate buying groups, he built SalesBox AI to automate pipeline creation and make revenue generation smarter, faster and more precise. His approach emphasizes practical AI innovation, measurable outcomes and scalable systems that empower teams to operate with greater clarity and confidence across dynamic, fast evolving markets. Well, good afternoon Alex. Welcome to the show.
- [02:05]
Alex Roy Rajan
Hello.
- [02:06]
Podcast Host
Hi Alex. I appreciate you again jumping on making the time. I know you're hailing out of New York today. I'm in Kansas City, so just an hour apart to get this podcast going. And if you don't mind, Alex, jumping into your first question, you founded SalesBox AI to automate a unified AI go to market platform, bringing together advertising, lead generation, first party intent data and intelligent orchestration. What was fundamentally broken in traditional go to market strategies that pushed you to build this platform?
- [02:39]
Alex Roy Rajan
That's a great question. So back in the day when I started SalesBox AI, the core realization was that the traditional go to market system was just inefficient. It was actually structurally fragmented. So there were fundamentally three things which were broken. Firstly, it was a lead centric model. So instead of what we call as an account centric model with buying groups, it was very lead centric back in the day and signals were not actionable. So while we had signals captured, it was very difficult to operationalize. And thirdly, the execution was very manual. So what I mean by that is one had to export lists, upload it to different platforms. You had to manually launch campaigns, it had to be manually assigned to SDR teams who would then manually call. So this actually slowed companies down and where speed was the name of the game. So the goal of sales box AI was to provide to move from a campaign driven to a signal driven platform where you can execute much faster.
- [03:47]
Podcast Host
Really like that. Moving that from that campaign driven model to that signal driven model. I really appreciate that. And you talked about that there was a big need in the market, it was structurally fragmented. You talked about the three things that it was and needed to be improved was, you know, it was a lead centric model, the signals were not actionable and execution obviously was very manual. And I really appreciate those insights and how you're making this a better platform for Everybody. Alex, SalesBox AI focuses on a unified platform for a complete go to market using AI agents. How does AI change the way companies go to market? I understand your AI agents work together. Can you explain that concept?
- [04:30]
Alex Roy Rajan
Sure, yeah. So it's all about turning data into action. So sales box AI agents help you orchestrate a signal driven and proactive approach to reaching prospects at the right time with the right message compared to the traditional reactive and manual campaign based approach. So with Salesbox you can have a set of specialized agents. So for example, you have an intent agent that's listening for intent signals. You have an outreach agent that's crafting personalized outreach messages. You have an advertising agent that allocates ad spend and decides whom to be showing the ads to. And of course you have an orchestration agent that is coordinating the actions between these agents. So each of these agents have, give a certain level of, have a certain level of controlled autonomy that you're able to provide. And they are collaborative. So the net result of this is that you have an always on signal based, signal driven revenue engine that's running for you.
- [05:35]
Podcast Host
Thank you, I appreciate that. And I like how you kind of broke apart the various agents. You know, there's obviously there's an agent level orchestration that goes on but you're turning this data into action with your agents by them helping with a proactive and action based approach. They're listening, collaborative again, it's an orchestrated orchestration model of multiple agents doing various tasks to maximize the effort and really dial in that sales. So I appreciate that. Alex, A unified AI go to my go to market platform sounds powerful, but companies fear losing personalization. How do you balance automation with meaningful human centric engagement?
- [06:15]
Alex Roy Rajan
That's a great question. Right. So when we talk about human centric engagement, we have to unpack this a little bit. Right. So being human is not just about biology. Right. It's about we have to look at what the qualities are. So you have empathy, you have reflection, you have creativity, moral reasoning. So it's about, you know, how do we help marketers amplify those human traits using an agent? So, so that, you know, the prospect feels understood. They feel then they are being helped and not sold to, et cetera. So traditionally we have these different Personas and we optimize for scale and relevance less. Whereas with the agents we are able to kind of amplify those very human traits that you that we talked about and do it exactly like how the marketer really wishes to but never had the resources to do.
- [07:08]
Podcast Host
That's awesome. And it is important that we keep that. And I know we always have humans in a loop, but AI is getting better as far as these agents to really mimic or as close as we can get that human centric engagement at the agent level. But we do know that agents now can understand the customer sentiment, obviously, as you mentioned, providing that listening, that empathy, that relevance, so that it is relatable to the customer. So I appreciate that. And Alex, as we look ahead here in our last question, how do you see a unified AI native go to market platform reshaping revenue organizations over the next five years? And what skills will modern chief revenue officers and chief marketing officers need to stay competitive?
- [07:57]
Alex Roy Rajan
Sure, yeah. The biggest change is that revenue teams operate across today they operate across disconnected tools. Whereas in the future you have a unified AI native platform that becomes a single revenue brain. Right, for the company. And it's actually ingesting the signals across the entire customer life cycle. It's predicting opportunities and risks, orchestrating actions automatically and learning continuously from outcomes. So what this means for CMOs and CROs, the leaders today is that how do you transition from becoming an AI assisted leader to, to an AI native leader, as I would like to mention it. And it all starts with AI literacy. So it's not about Technical AI literacy, but it's more strategic. Leaders don't need to build models. Right. But they must understand and they must have a way to question the AI outputs themselves, which means they need to understand how AI makes predictions. They need to understand what are the limitations, what does bias mean, when, and moreover, most important, when human judgment overrides the AI. Right. So I would bucket this under the AI literacy bucket. And then as leaders, we need to be really good at orchestrating AI agents and humans together and workflows. So there's like three parts to it. What is automated, what stays human, what are the escalation points, how do you have governance and control around it? So our skills around this area needs to improve. And lastly, I would say the decision velocity as a leader. So AI as you are aware, compresses time. And so you need to, to stay competitive, you need to make those decisions much faster. There's that learning loop. You need to be faster in learning and adapting. So, yeah, so as leaders, you need to be able to stay always on and adapt based and take decisions faster, I would say.
- [10:01]
Podcast Host
Thank you, I appreciate that. Absolutely. Leaders need to be ready to adapt, make decisions faster. Of course. And you talked about current revenue streams right across the workforce within companies. They're using different systems of spare systems. However, we know in the future, agents will be able to connect with each other and work and share this information to be more efficient and make better decisions. Of course, moving from that AI assisted to that AI native environment. That's. You talked about that. And leaders don't need to just build models, but really understand the AI language and learning to orchestrate these AI systems. And I think that's really important and I appreciate that. Alex, it was such a pleasure having you on today and I look forward to speaking with you real soon.
- [10:46]
Alex Roy Rajan
Yeah, I mean, it was an absolute pleasure to be on the show and thank you.
- [10:50]
Podcast Host
Bye for now.