What If Every Student Had A 24/7 Relationship With Their College

Three million calls a month is not a marketing flex. It’s a signal that higher education is moving into a new operating model, where AI can expand student support without pushing humans out of the picture. I sit down with Ruben Harris and Timor Maester, co-founders of Outrival (and previously Career Karma), to unpack what they mean by a “digital workforce” and why outbound AI agents are becoming a real tool for admissions, advising, retention, and re-enrollment. 

We get specific about how colleges and universities can deploy agentic AI in ways that are measurable and responsible. Ruben explains why treating AI like an intern with a job description and a clear objective helps leaders move past vague pilots and into outcomes you can track. Timor shares use cases that work on the ground, from proactively reaching stop-outs months after they’ve gone silent to re-engaging applicants who started the process and then disappeared, all while giving students the option to connect to the right human at the right time. 

We also talk about what most vendors gloss over: performance management, experimentation, and compliance. Dashboards, text-based feedback loops, call reviews, and even A/B testing voices and scripts can help teams improve the quality of conversations while respecting policies and outreach rules. We close with a five-year vision of real personalization at scale, where a student can text their college 24/7 and feel known, guided, and supported. Subscribe, share this episode, and leave a review so more higher ed leaders can learn what’s actually working with AI right now.

Transcript

Meet Outrival And The Big Idea

SPEAKER_02 0:09

Hi, I'm Eloy Ortiz Oakley, and this is another episode of the Rant Podcast. Welcome. This is the podcast where we pull back the curtain and break down the people, the policies, and the politics of our higher education system. In this episode, I get to sit down with two entrepreneurs, two guys who have been working in the higher education landscape for many, many years, starting off as the co-founders of Career Karma. Many of you may have run into them at Career Karma, and now as the co-founders of Outrival. And I'm talking about Ruben Harris and Timor Maester. Ruben and T. Moore, as I said, are co-founders of Outrival, a company that's building digital workforce solutions for colleges and universities throughout the country. And what do we mean by that? Digital workforce. I know we've talked a lot about AI on this podcast as well as other agentic solutions and how these solutions are helping more and more colleges and universities be more precise with their learners, create a more personal experience for them. But Timor and Rubin are creating digital workforce solutions. And they'll explain it much better than I can. These solutions aren't meant to displace the human in the loop because as we all know, whether on this podcast or other experiences, that the human is central to the student experience. But their solutions, their digital workforce solutions, help expand the opportunity for the humans to reach more learners, to engage more learners. And so they'll talk about their uh agentic technology and how they deploy it, how they're learning, how they're helping more colleges and universities engage more learners. So I'll let Ruben and Timor explain more about their technology and the kinds of use cases that they're deploying and how they're keeping the human at the center of the engagement with the learner. One other thing that they're doing that I want to make sure you all are aware of is they are producing a new podcast video series that I think you all will enjoy. It features many of the same guests that have been here on the Rant Podcast, people like Scott Pulsifer from Western Governors University or Greg Fowler from the University of Maryland Global Campus, talking about how they are deploying on the ground innovative solutions using AI to drive more engagement. Ruben and Tim Moore have titled their new video series, podcast series, The New Normal. And I think that's a great title because this is the new normal. Deploying AI and other agentic solutions, I think, is going to be key to developing the new normal when we're talking about engaging learners and what they expect in return. So their video series called The New Normal kicked off on June 25th. So make sure and check it out. I will put a link to their website in the notes section of this podcast. So check it out. And with that backdrop, please

Outbound AI Agents Explained

SPEAKER_02 3:20

enjoy my conversation with Ruben Harris and Timor Maester, co-founders of Outrival. Ruben and Timor, welcome to the Rant Podcast.

SPEAKER_00 3:31

Thank you, Elo. We appreciate you.

SPEAKER_02 3:33

Yeah. Excerpt a pleasure. Well, it's great to have you both. Uh, it's great to have some leaders in AI on the podcast. We we talk a lot about AI on this podcast with uh CIOs, CTOs, university and college leaders. But it's great to have a couple of individuals who are doing this work on the ground, helping colleges and universities leverage AI. So we'll jump into all of that along the way. But first, let me start by by asking you two: how are things going in Outrival? You guys are co-founders of Outrival. You've been at this for quite some time. You've been in higher ed for quite some time. How are things going in Outrival? And describe your mission.

SPEAKER_00 4:16

Yeah, things are going really well at Outrival. I'll be brief on my side and let T-Mor follow up. But essentially, we're building these outbound AI agents for the education industry and other organizations that have a lot of people essentially serving people throughout their student journey or their customer journey. Uh, we're currently at about 3 million calls a month, uh, targeting about 10 million calls a month by the end of the summer, and many more text emails and voicemails. It's all about proactively supporting students and anticipating what their needs are, not just on the enrollment side of things and the engagement side of things, but also on retention and throughout their whole student life cycle. So I'm very excited about what we've been able to do with schools across the nation, offline, online, across all kinds of formats. And um, we are excited to tell you more on the show. Timo, anything else?

SPEAKER_01 5:05

Yeah, Eloy, thanks for having us. Now, I'll just add that uh I've known this guy for now close to 15 years. Um, we first started career karma because we were on a mission to um help adults upscale, pivot their careers, uh, figure out how they can get to that uh opportunity in terms of their careers. And funny enough, ended up uh building a large proactive call center team that would reach out to people looking for guidance and they're leaving the military and they want to maybe pursue cybersecurity. Do they go back to college, boot camps, uh, online courses? What's interesting now without Rival is we get to both combine kind of our passion for serving the student. And also uh we have a very deep perspective on how do we help institutions that are also looking to leverage technology. AI is one of those technologies to help their advisors, help students, and so on. So very excited to share our learning so far. We're still in an early inning, and uh, this is just a very exciting time to be builders. Right. Oh, absolutely.

SPEAKER_02 6:11

Let me ask you this, um, Timor. How did your journey, I mean, you began your journey, as you mentioned, with Career Karma uh and the work that you all were doing there, and I think that's where I first met you guys. How is that journey informed where you are today without Rival?

SPEAKER_01 6:29

Well, it started with uh Ruben and I first doing thousands of calls with prospective students and students ourselves to understand uh what's holding someone back, what what what is their plan in terms of picking a school? What's important to them? Uh, how does an advisor or a coach guide someone? And um, those learnings helped us now design experiences that are digital. And you can see the folks behind me, they're actually, that's not a virtual background, it's it's our team. And our team helps to uh take uh repetitive work. We call it repetitive work that becomes digital work. Things like proactively reaching out to someone uh to remind about something, they're missing a transcript. How do we get that student who's going through the admissions process for the first time? How do we get them kind of to understand what are all the requirements, right? So they don't fall through the cracks and actually make it to the to the outcome, which is picking a school and enrolling. And so we've been able to leverage a lot of that expertise as well as tailoring it to our customers' uh enrollment process or re-enrollment process or other types of uh questions that students have. And students have thousands of different questions depending if they're already enrolled or not. And uh, we've been very successful in terms of driving impact. Like Ruben said, we're making over 3 million calls per month in terms of driving impact, but also uh creating ROI. For a lot of our institutions, ROI is someone is able to retain for longer, they're able to graduate, or they're able to take people who already are expressing interest and enroll. So excited to go deeper, but that's kind of the experience that led us to now uh be very familiar with the student journey as we build out Rival.

SPEAKER_00 8:19

The the only thing that I'll add is another piece that we learn from career karma is that making decisions are often more emotional versus rational. So when you're choosing between schools, you're not just comparing what they offer versus the other. There's like a lot of things from an emotional perspective, from a parent's perspective. There's a motivation perspective. Maybe you're the first person that went to college. So how do you how do you figure out what's the balance between give moving someone through an enrollment funnel and also motivating them and encouraging them by connecting them to the right human? So as we go through this conversation, we're gonna share how we thought through not just being on the phones, but the balance between digital workers, humans, motivation, psychology, and decision making.

Digital Workers As Measurable Interns

SPEAKER_02 9:10

Well, let me pull on that thread a little bit, Ruben, with you. What when you're talking to college and university leaders, how do you talk about the relationship between the support that you're providing them, the technology that you're providing them, and their own workforce? How does that conversation go? And and for somebody listening in, what advice do you have for them on actually articulating the value of leveraging the kind of technology that you bring?

SPEAKER_00 9:42

Yeah, so you probably noticed that I use different language than other people use. That's part of the human side of things, where instead of calling AI agents, we call them digital workers. So the first thing that we do is say, hey, imagine that your staff, whether it's an admission staff or a student success team, got promoted and it has people working for them. You understand that. That's great. Imagine if you brought on a digital worker or a human to work with you. What would you do? You would give it a job description, you would set an objective, let's say it's for an internship. If that human or that digital worker accomplishes that objective, then you will consider bringing them on as a full-time member of your team. People go to college, people in college do internships, it helps them understand what's going on. But you, if you're if you're going to create budget for a human or for a digital worker, you should probably assign it towards something that's going to add value towards your organization. And right now, a lot of the leaders that we're speaking with are saying, hey, I know I have to do something with AI this year. So they're announcing they're going to do something with AI. But a lot of times the things that they're trying aren't always leading to something that you can measure. Right. And there are things that you can measure when it comes to enrollments or transfer rates or contact rates. And you can actually prove things out in a short period of time. And the challenge for a lot of higher ed leaders that we see is they think in annual cycles or multi-year decade cycles for changes, but you can't move that slow in an AI-driven world. But you are used to the internship model, which is a shorter time span. So if you apply these digital workers to our specific objectives in a short period of time, you can prove things that move the needle and decide what you do want to invest in annually,

Practical Use Cases For Colleges

SPEAKER_00 11:35

multi-year, or on a decade-long cycle.

SPEAKER_02 11:37

Right. Timor, let me ask you: you're designing and building this digital workforce for your different partner colleges and universities. I imagine they all have sort of different ways, different use cases that they want to deploy this. What are some of some of those examples of use cases that you see happening in the field or that you think are prime targets for the kind of solution that you're providing?

SPEAKER_01 12:02

So I'll I'll share kind of three things we'll usually uh advise our customers on. I think the first one is how do we increase the amount of meaningful conversations that their staff is having, right? I think it also goes back to your earlier question in terms of how does AI work alongside their staff? The a great metric for that is let's increase the number of meaningful conversations there. The second um point that we'll discuss with them is what is the objective? Everything goes as um you want. Is someone retaining for longer, or are they enrolling, or are they navigating complexity of uh maybe filling out FAFSA and all the financial requirements, right? Like what are we actually trying to do in terms of the progression? And the third one, it comes down to the use cases that we've seen work that are easy in complexity to execute to build um support internally, that this is actually working. And so just to give you a few examples of those, for some universities, it's about having AI reach out to your stop outs, right? And when an AI reaches out to the stop outs, it's an easy one to um kind of get everyone aligned around. Because a lot of the time, the the person who stepped out might have gotten some emails or calls initially, but six months later, it's unlikely someone proactively checking in with them to say, would you like to come back? Uh, can I point you to more resources? And so this example is perfect for one of our digital workers to take on. Because if someone does answer and say, you know what, my family had a medical issue, so I stepped out. Now I'm ready to return, the AI could say, Well, I can schedule you with your advisor, Hannah Miller. So the digital worker does know who their advisor was. They know what the school's policy is on re-enrolling, and that it could either schedule them, it could send them a link, or it could guide them. And so that's one of the best examples to start since they're not doing the work that's um kind of the staff is doing, and they're increasing the number of meaningful conversations those advisors are having to drive retention on the enrollment side. Sometimes it's about reaching out to people that were actively speaking to their human advisors, and then they just went dark, right? The digital worker could reach out to them and say, again, I'm reaching out to you on behalf of your advisor. The magic with these uh kind of digital beings is that they're they're all connected to your CRM, whether you use Slate or Salesforce or uh an SAS system, and then it's able to reference what course they were studying or what document they're missing for them to proceed. And then it always um gives them an option. Do you want me to connect you to the human? Or do you want me to send you a link? And it's about creating that optionality for them. So I would say those are some of the powerful use cases in terms of adding versus replacing. Right.

SPEAKER_02 15:13

So you're adding capacity to the human,

Student Feedback And Quality Signals

SPEAKER_02 15:15

you're helping them reach more learners, do more on any given day. How how do you how do you measure the success of the interaction with the person on the other end, the learner, the student? Do you is there a way to survey those students? Is a way to learn whether or not that interaction is actually successful? How do you do that part?

SPEAKER_01 15:37

So our team developed um, there's a few ways we gather that feedback. One way is literally following up with someone after a conversation through text message and say, hey, I know you spoke to um like the digital assistant. How did how would you rate this experience on a scale from one to five? And someone could respond over text, right? So you're not sending someone an email with a survey, and then people ignore that email and no one actually does the survey, right? I do that all the time. It's kind of like it's kind of like the restaurant reservation. Like are one for when you're if you're gonna attend, two if you want to cancel. We have a similar system that's able to have a natural language conversation with a student, and then we're able to take their responses and structure in a way where on a dashboard or a report, a leader who is deploying AI could actually see like, are people enjoying and finding it helpful? So that's one of the one of the very like easy ways to gather that. Another way we do this is we create a word cloud for the leadership team around uh tens of thousands of conversations that are happening, and a human or uh advisor, like manager, cannot possibly absorb tens of thousands of conversations, concerns, objections. We're able to show it to them, and then they can click on each term or each reason and actually hear conversations between students and the AI to be able to further understand what's actually happening. So now we're actually leveraging this technology in a way that gives way more insights, it's way more impactful, and it also builds this uh notion of like we're only doing things that are adding to the experience of the students versus uh doing things that um dilute the meaningfulness of having an advisor or having someone kind of enroll into your program.

SPEAKER_02 17:34

And do you use that feedback to help the digital worker get better? How do you improve the interaction over time? It's a great question.

SPEAKER_01 17:44

So a lot of the time, we'll first ask like, how would a human, if this was a human workforce, right? If you just hired someone brand new to be on this team, what happens today, right? And the reality is that usually there's a handbook or an onboarding document that someone has to go through. They do mock sessions, they listen to calls to observe like how are these conversations uh sounding? And then their manager actually reviews conversations to give them feedback. So we've been able to productize and even have uh we created a new role called the digital worker manager. It's a human on our team that manages the worker, and then they train the school on how to how do you tweak maybe the way the agent sounds? How do you tweak their voice? You can make some voices could be um more cheery, some voices could be more direct. How do you uh kind of tweak the like objection handling, even right? Some students are saying, hey, um, I'm busy right now. What's the best way to respond to an objection like that? Right? Should it be I can send you a link so you can find a time, or you could say, hey, I'm gonna call you back. So those are some of the things that we then train our counterparts. And uh then the school is able to use our platform to be able to be kind of self-sufficient and manage the digital workforce like they do with their human staffs and create that co-intelligence that

Performance, Experiments, And Compliance

SPEAKER_01 19:15

kind of works alongside the existing advisors.

SPEAKER_02 19:18

Ruben, the three of us were recently at the ASUGSV summit and it's 8,000 people talking about AI, you know, a whole slew of vendors talking about how their new AI solution is gonna solve all your problems. When you're talking to leaders about the work that you do at Outrival, how do you differentiate what you do versus what now every vendor says that they do?

SPEAKER_00 19:46

It's a great question. I'll say all agents are not created equal. I'm gonna go back to the whole human analogy, right? Managing humans is hard. Managing agents is hard, and managing both of them together is even harder. And so it's not just about creating digital workers that can speak that are intelligent. Most of the agentic solutions that our people are creating have a reactive flow. It's more like an inbound, like, or if there's any time a problem comes up from a student, like they'll handle it or they'll solve it. And a lot of people's approaches is creating these like one-size-fits-all workers that can answer anything that take a very long time to train and implement. When Timo and I think about setting up a digital worker, each one of them have a separate job description with a specific objective. So that's one, it's not like a one-size-fits-all. We have a proactive approach for how to set them up. But we're not just thinking about agents that are that are aligned with the workflow and an objective. We're thinking about performance. Timor talked to you a little bit about the dashboard and the surveys and things like that. But what one of the biggest challenges managing humans is is uh knowing what they're doing all the time, whether you're in-person or out. Some schools are in person, some are remote. If you're a manager, maybe you're doing a one-on-one once a week, maybe twice a week at best. But can you monitor performance daily? And if you are seeing different pieces of performance daily, how are you tweaking based off of what you're seeing? How are you testing new things? So one of the schools that we talked to at ASUGSV, that's more on the more innovative side, they said they wanted to run not just 50 experiments this year, they wanted to run 500 experiments. So, how are you going to run A B tests in a call center with let's say a male voice versus a female voice at a different time of day? That's a very simple common A B test. You could do it with humans, you could do it with digital workers. With us, we will actually help you test 20 voices, a hundred voices at a time. And actually Like you said about the learning, the digital worker can pick up the platform what is the best uh performance that you're trying to achieve, and then recommend this is what we should do tomorrow or the next day. And then again, it's not just about the digital workers and being proactive and being outbound, it's how do we upridge the relationship to the humans and that that speed to meaningful conversation. Like Timor said, a lot of the schools back in the day, when they first were thinking about call centers and and the speed to lead, it was all about how fast can a human get to somebody on the phone that goes out, you know, abcuniversity.edu slash apply, right? Right now, humans don't have to do that anymore. The digital worker can respond right away, say, hi Eloy, this is Ruben, your digital worker. I see you spoke with Timor yesterday. How are you doing? Great. If T More is available, cool, I could transfer you. So now my humans are talking to people that are ready all day versus people that you're not sure if they're ready. That's why whole lead qualification things are thing. So we're able to essentially differentiate ourselves that way. Most companies and platforms right now are just creating these digital workers that take a long time and we can we can be live in two weeks and that performance and that skill and also compliance, which is a very, very important thing. Is is we can suggest the best practices of what we've seen across the board for schools. So whenever you're getting into proactive land, it's not just about technology, it's about following the rules and doing things the right way and being respectful about things, not just for your school and FERTO, but for sit for states and cities and time zones and labor laws and all of that.

Making AI Work With Limited Resources

SPEAKER_02 23:40

Right. Timor, you you obviously come across universities as Ruben mentioned, that are sort of way out there on the innovation side. They're very comfortable with innovation. I mean, you've got the ASUs of the world, the Western Governors University of the world, uh places like that that are very comfortable and have a culture of innovation. So they they're more uh prone to be thinking about different ways to apply the use cases that you just mentioned. And they have internal processes to help them manage that innovation. How do you talk to the colleges and universities that are nowhere near that kind of uh level of sophistication, but are hungry for solutions that may help them do a better job of reaching learners, do a better job of lowering the cost of education? What does that conversation look like? And and what advice do you give those those leaders?

SPEAKER_01 24:39

It's a great question. I think when we were, it all comes down to like when we were designing and architecting uh Outrival's platform, there's a few decisions that we made for like not just this kind of visionary like AI reality, but like what's actually happening on the ground. Like the leaders that we speak with, one of their first kind of objections that they'll share is like they'll tell us that your AI use case sounds great, but we don't have our knowledge base up to date. Right. Right. Your use case sounds great, but we use maybe an Oracle SAS system, and um, we can give you access, but our IT staff is uh six months backed up, right? So those are when we were kind of giving given our domain expertise, when we were designing how does a digital worker join your team as an intern and could be up and running in two weeks, we needed to account for the reality of the everyday kind of admissions team or um student services team, that all of these pieces may not be in place. And so as a result, now uh I could share one of our customers that we're working with, like Miami Date College, right? They're a community college that's so mission-driven that is serving hundreds of thousands of students, right? And our expectation is not that uh they're just gonna take our platform and they're gonna just kind of run with it. We we design, we we could collaborate and we partner with them like true, um, kind of like a true extension of their team in order to make sure that we get every little piece right, right? So that's an example of just no matter how big or small your institution is, we bring a lot of that domain expertise that ensures that our digital workers are not just 80% there, they're 100% there. And there's someone on Outrival's team that's responsible for their performance. And they're also responsible for making sure that that kind of self-learning and self-improvement doesn't just happen on its own. There's a human that oversees and ensures that it complies with policies, complies with institutional requirements, and so on. So that's just a little bit of kind of a window into how these digital workers get created, managed, and deployed.

SPEAKER_02 27:02

And for example, uh, a college university who begins to work with you, and let's just take Miami Days as an example. Great college, one of the really the better colleges, community colleges in the nation, as they grow capacity and understanding of how to deploy a gentic solutions, how do you change the dynamic between you and your clients uh as they want to take on more responsibility? Do you have a way to do that as they get trained up, as they add capacity, as their IT teams become more familiar with the technology? What would that look like for uh for a Miami Date over, say, uh a five-year period?

SPEAKER_01 27:42

So we look at it as a true partnership with uh a lot of our customers uh and academic partners doing the heavy lifting of sharing their strategies, their ideas, the areas that they want to do. And then outrival becomes another tool, right? And they're toolbox. And initially we partner with them. So our institutions use uh outrival just to make sure that um the ROI is there. Like people are being helped, people are persisting, they're retaining, they're coming back. And once we prove out the kind of we validate the core premise of using digital worker to help, then the second uh phase is then we roll out our platform and train their team on being able to do it in a way where they're it shouldn't feel like they're driving a Formula One car. If you know if you like that manaphor, it should feel like they're driving your like Ford SUV, and um, you can take it on highways, you can take it on roads, you have airbags, and so on. That's kind of our vision. Where in the beginning it's all about performance, but eventually we want our customers to be creative with how this tool could be used. And um one analogy I'll make is over time, like institutions adopted email tools. Every institution today runs email campaigns, right? Right, two thousands, if not millions, of uh emails and reaching millions of students each day, right? So those tools and at some point were very foreign and it was new to the institution. However, now they've fully adopted it, they integrate with their systems and so on. And so on a five-year horizon, we feel that a digital worker is gonna be just like another two like email campaigns. That's gonna be much more intelligent. Uh, it will require a lot less guidance and like drafting a five-paragraph email, you can just speak into kind of the platform and say, hey, I'm looking to re-engage this segment of students, and the AI will do the heavy lifting for them. So that's our longer vision for the roadmap in terms of where this where things will evolve to.

The New Normal Podcast Series

SPEAKER_02 30:05

That sounds great. Uh, Ruben, let me ask you this. I know you recently were telling me about an opportunity that you all are investing in to highlight innovation throughout the country and uh put a focus on leaders in colleges and universities who are actually driving innovation, who are actually doing it at scale, deploying um new technology solutions, and and really leading the country in terms of what is possible. Tell us about that uh effort that you guys are investing in and tell us about where you want to go with this uh uh, I guess you would call it a video series.

SPEAKER_00 30:46

Yeah, so I mean, Timo and I lived in San Francisco for about eight years before we moved to Miami, and we've been in Miami for the last five years. So we are big fans of all of the podcasts coming out of Silicon Valley, whether it's Dwarakesh, whether it's acquired, whether it's by Combinator, we did what I combinated, we did all that. And what we learn is a lot of these shows are rightfully sharing and shining light on AI vendors and the investors that are picking to invest in these AI companies that you were talking about earlier, and then sharing their philosophies and their vision about where the world is going. So, similar to like your question about like differentiation, those types of podcasts are dime a dozen, you hear them all day. What you're not hearing that much or at all, from my perspective, is people shining light on organizations that are actually using AI and production at scale, a way that's driving meaningful impact. And so T1 and I are launching a new show that's called The New Normal, where we interview the leaders that have all actually made the decision to implement AI and production, but are also getting results. It's almost like the the current shows are like people talking about shovels and then interviewing the people that are like taking those shovels and like digging for gold and then sharing the gold because we're in a special time where, again, going back to what I said before, I empathize with leaders. They know they have to do something with AI, similar to the internet, similar to apps with mobile, right? They know they have to do something, but they have the luxury of being able to say, not do anything. They say, hey, I'm gonna do something with AI this year. And part of the reason why they're not doing anything is they don't know how and they don't know what their peers are doing. Because every time we speak with our customers, they're always asking us, what are the other customers doing? So by hearing the stories of other leaders that are doing awesome things to improve the lives of students and employees, not only will that help other people not only take that AI strategy and put it into production, but also to start introducing a new model for our higher institutions that need to modernize to prepare the future leaders of the world. So I'm very excited to share that show. We are about 11 episodes scheduled deep. Uh, we're gonna be dropping uh over 30 this year and many more. So stay tuned. So appreciate that.

SPEAKER_02 33:23

All right. So the podcast series is called The New Normal. And so it'll be out sometime, what, this summer?

SPEAKER_00 33:32

Yeah, probably like June, July we'll start dropping.

SPEAKER_02 33:34

All right. Well, I'll make sure and include information about Outrival and where to where to find that uh video series, the podcast series in the notes section of this podcast, uh, so that everybody can stay tuned. And I look forward to to checking it out. So thanks for doing that.

SPEAKER_00 33:51

Won't just be video, it will be audio as well.

SPEAKER_02 33:53

Okay. Great. So so you can drop it in your in in your Spotify or uh Apple Podcasts, or you can tune into YouTube. There you go. All right. Well, not that uh the rant podcast needs any more competition, but we welcome it.

SPEAKER_00 34:11

That's all love. No.

SPEAKER_02 34:14

Well,

The Five-Year Vision For Personalization

SPEAKER_02 34:15

listen, let me ask you both one last question as we get begin to wrap up. And let's start with you, Ruben. Uh, given all of the changes that are happening, I mean, you guys co-founded Outrival, what, about two, two, three years ago? Somewhere in that range. So much has changed just in that small period of time. Um, where do you see Outrival and the technology over the next five years? Let's start with you.

SPEAKER_00 34:42

Yeah, so something that Timo and I talk about a lot is is something called personalization. And so when you're a large organization, Timor Bada, Mahmi Day College, or any school that has tens of thousands or hundreds of thousands of people coming to them all the time, even if you have a staff, a human staff in the thousands, historically it's been impossible to have a relationship with that individual throughout their whole life. I think that our is going to be able to help organizations have a personalized relationship with all current, historical, and future people that are interested in becoming students or customers of organizations throughout their entire life cycle. And even though you have this relationship with that digital worker, which is almost like the voice of your brand, that can also text, email, and leave voicemails and take actions on your behalf, that digital worker can always connect you to the right human at the right time. Going back to the human piece, humans don't stay at organizations forever. In higher ed, some of them do. They have been there for 30 years. But that's not always the case. So if I'm calling my school again to get in touch with some type of person, I that person might not be there. So, but the digital worker can always connect you with the right human at the right time. So I I pray, I hope I will work every single hour that I live and breathe to actually help organizations position themselves to have that personalized relationship with anybody that comes to them.

SPEAKER_01 36:22

All right. How about you, Timur? Yeah. What I'll add is uh a little bit about Ruben and I. So we're we're big into kind of manifestation and having a very clear picture, not on where we are now or where we'll be in like three years, but five years from now, how do we know if we succeeded? And personally, the way I will judge my success is if I um I don't know if you can see my screen. I'm pulling up my messages. Um, my vision is that I want the college, the university, the online school to have a real relationship with the student. So that student at any time could just text the school, or if they're behind on classes or they have questions about financial aid or a hold, the AI could reach out to them and have a meaningful conversation that's engaging. And someone actually feels that at any hour of the day, 24-7, they could have a meaningful conversation that knows about them, helps guide them. And that's like what once we start having our customers have kind of persistent interactions on their in their DMs, I would say that's how I know if we made it. Right.

SPEAKER_02 37:35

So well, that's great. I hope that we can get to that reality. And given the work that you two are doing, I'm sure you will help us get there. It's uh it's great to have you both on on the podcast and just thinking about how much work you put into this ecosystem, whether at Career Karma, now outrival. It's just great to see two entrepreneurs with your backgrounds who really care about the learner engaged in this, particularly at a time right now where AI is just dominating the entire conversation. So, Ruben and Timor, thank you both for your leadership and thank you for being on the Rant Podcast.

SPEAKER_00 38:16

Thank you for helping us, Shark. Thank you.

SPEAKER_02 38:19

All right.

Closing Thoughts And Subscribing

SPEAKER_02 38:20

Well, you've been listening to my conversation with Ruben Harris and Timor Meister, who are the co-founders of Outrival. I will make sure and put information about where to find Outrival in the notes section of this podcast. And also, uh, as soon as a link is available to the new podcast series, the new normal, which everybody should tune into, I'll make sure and put it in the uh notes section as well. Thanks for watching, everybody. If you're watching us on YouTube, hit subscribe, continue to follow us, and if you're listening to us on your favorite audio podcast platform, hit subscribe and download this episode and share it with everybody. The team in Out Rival is doing great work. So thanks for tuning in, everybody, and we will see you all soon.