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Every Friday, join us as we dive into the latest in real estate multifamily with David Moghavem, Head of East Coast Acquisitions at Trion Properties. David invites top experts who know the ins, outs, and trends shaping the real estate multifamily market across the nation!
Whether you’re a seasoned investor or just curious about where the next big opportunity might be, Deal Flow Friday brings you the weekly inside scoop on what’s hot, what’s not, and what to watch for in today’s ever-evolving real estate scene.
David Moghavem (01:46)
All right, welcome to another episode of Deal Flow Friday. I'm your host David Moghavum and today we got Jacob Kosior, of Elise AI. Jacob, great to have you on. How you doing?
Jacob Kosior (01:58)
I'm doing well, thanks for having me today David.
David Moghavem (02:00)
Well, know, this started first of all by a shout out on our pod, on a previous pod. ⁓ Elise AI has been shout out a few times now on the pod. So one of the first ones was with Max, managing partner at Tryon, where we're talking through ops and we're just nonstop talking about Elise AI, to the point where it almost turned into a commercial. And you guys reposted it and one of my friends, shout out to Daniel Matute, he actually...
Jacob Kosior (02:04)
Yes, it did. It did.
David Moghavem (02:28)
sent me a screenshot of your guys' Slack saying, dude, you're going viral on my Slack right now. ⁓ So that was fun. the shout out heard around the world, now you're here. Now you're on the pod. And so we had to make this happen.
Jacob Kosior (02:31)
Yeah.
Yes, yes, we had some listeners to
that. And so got a full circle moment here to be able to chat with you directly. Yeah.
David Moghavem (02:46)
This is a full circle moment and you actually
got shouted out a few other times after that. We did some other PropTech ones and Elise AI is like the poster child right now of PropTech. little tidbit of Elise AI, leading multifamily technology platform, redefining leasing and operations through conversational and agentic AI, a buzzword you hear all the time.
which we'll get into and Elise I just closed a $250 million series impressive led by a 16 Z and you guys are now at a 300 plus employee head count and you're generating over a hundred million in annual recurring revenue. So really impressive. One of the fastest growing companies in multifamily technology and prop tech and Jacob, it's really an honor to have you on.
Jacob Kosior (03:37)
Excited to be here. Yeah, we're doing a lot right now. So it's exciting to kind of talk about everything we're doing, especially as y'all have given us shout outs in the past about kind of hopefully the real world impact that it's having too, not just for operators, but even renters who are increasingly frustrated with the housing environment because it has not kept pace with consumer behaviors or consumer preferences that we're hoping to address with new ⁓ AI native tools.
David Moghavem (04:00)
Yes, and with that, I want to jump in because it's true that I think with renters, they have been feeling pain points and it looks like Elise AI has been addressing that. So I guess to start it off, how is AI really redefining and reshaping multifamily operations today?
Jacob Kosior (04:17)
Yeah, well, in part, it's been, you know, our ratios and multifamily housing have not changed in decades. We've all operated. I'm saying this as a former operator myself, a Elise, I client myself before I joined the team of we'd always budget and ratio and plan for staffing where it's one person to every hundred units. And even as new technology has been layered on in years past, nobody has been able to move that metric. And now it's because of AI tools being able to both using conversational AI to converse with prospects and residents.
and agentic AI to do some of these tasks that were previously manual, we're freeing up operators to rethink like what actually has to be done on site in an apartment community. Where could those onsite team members better focus their efforts for the human experience on site, knowing that now we have the freedom to move a lot of those administrative tasks off site. And that's where we're seeing this really interesting convergence right now of centralization in the multifamily housing industry that's been a bubbling topic for five or so years now, at least among third party operators.
is meeting this powerful new technology of AI and agentic AI that's allowing them to even take a more holistic view of what is their operating model, what work needs to be done, and where's the best place for that work to be done.
David Moghavem (05:30)
Yeah, so I guess maybe let's start with a few examples of what Elise has been able to accomplish now. Maybe start on the conversational side, because that's one of the products that we've actually just started onboarding onto our properties. ⁓ Maybe give a little bit of a conversation or example on some of those products that you guys have been unveiling.
Jacob Kosior (05:50)
Yeah, so we came to market in 2017, so this was five years before chat GPT and when most folks started to interact, right?
David Moghavem (05:55)
Yeah, you guys were AI before AI
was trendy.
Jacob Kosior (05:58)
AI
before AI was a thing. And at that point, it was just leasing AI. It's how can we deploy conversational AI to help prospects find an apartment? So moving beyond just that chat bot that would give you kind of simple answers or that pick and choose model to actually having conversations with you, that started to evolve more broadly on the resident side in 2022, where we started to expand with delinquency AI and renewals AI. As a former lease client, I got to work and be the first beta tester for delinquency AI with my
former
team and now we've expanded work in the maintenance side and started to develop more tools of what we call kind of agentic AI that's not just conversing and having conversations with a prospect or a resident, but actually doing some work that otherwise a human team member would be doing. So examples of those, we've got a lease file audit product now where the AI will scan a lease agreement and all the relevant addenda and then cross-check that against a ledger to make sure that all those charges are reflected accurately, including using the correct GL codes to hopefully make a
counting month end a little bit easier and things like...
David Moghavem (07:00)
And that's probably on
ops. then also probably when you're doing due diligence on a property and cross-referencing it with the rent roll to make sure the rent roll you're underwriting is ⁓ matching the leases on file, credit verifications, the way that it's being underwritten.
Jacob Kosior (07:04)
Yes.
Exactly.
Yeah, we can do it both with like a recurring offering for your current residence, your signing leases, or we offer it ⁓ for a due diligence process where you can even scan PDF documents that you might be provided from that former owner, a former management company. We also have tools for maintenance teams to do things like maintenance supervisor used to be there to assign work orders or call in that third party vendor who's doing work on site. Now the AI can take that on their behalf to auto assign work orders based on skill sets and availability, as well as reaching out to third party
vendors
to come into the space. So our goal is to expand ⁓ AI tools, both conversational and agentic, across the full spectrum of that resident life cycle. So we can always meet that prospector renter where they need on the channel that they want to communicate on. So we're hitting on those consumer preferences while also just bringing down the volume of work that on-site teams have to do to allow those management companies to rethink what work actually has to be done and where can they best utilize their on-site or centralized team members given what the AI is able to.
accomplish on its own.
David Moghavem (08:19)
Yeah. So we've been embracing some of these technologies, both with Elise AI and some of your other, I guess, competitors or predecessors. And what we found is it is extremely useful once implemented, but the once implemented is very important because implementing and implementation can be super painful for some of these onsites. Sometimes you see centralization actually cause
growing pains. How do you address those issues of growing pains and onsites kind of getting used to this new era where we're inevitably getting to, but you're seeing pain points and you actually see it on the bottom line sometimes where yes, maybe you're cutting some staff or you're getting efficiencies, but then you're also seeing some pain in the operations trying to get this implemented.
Jacob Kosior (09:14)
Yeah.
I mean, part of it's, you know, this sounds simple, but something that we've got to coach on now is like, it starts from the top. I'm very lucky that in my past role, my CEO would go on stage at our company conference and say, you are not going to be replaced by AI. You will be replaced by someone who's utilizing AI. Because just like using email instead of a fax machine, you're inherently more productive, right? And so a lot of the work we do is just, what's your centralization plan? We offer a full consulting team.
David Moghavem (09:33)
Right.
Jacob Kosior (09:45)
Elise AI to help our clients through this to say what is that plan? How are you communicating it? Just like you'd make a plan for your pilot rollout, you also need to make that plan for how are you communicating this within your organization and what are you communicating? Because what goes to a department head on the strategy for deploying AI or centralizing is very different than what you need to communicate to that on-site team member. And what got me really on board with Elise AI as a former client was just how the platform is
built to support that, where we have things like, you can go into the knowledge bank and see everything your AI knows about the community, and you can train it. You can give it additional information, just like you would train a new team member on site. So for that team member who's like fearful of how does the AI know what to say, I can do it better, it's not gonna answer this question right.
David Moghavem (10:27)
Right.
Jacob Kosior (10:35)
Elise offers the ability to log in and say, here's everything that your AI knows. If you want to tweak it, you can edit it. If you want to train it, you can give it some more information. And for operators who are growing portfolios or looking at how can I scale the size of my team or like my portfolio without adding all the head count that would otherwise be the case. They now have got control to say, how do we answer some of those sensitive questions like housing vouchers or emotional support animals or things that they might cringe to wait to see how an onsite team member answers it. They train the
AI tool once and it's set it and forget it from there. So we build in some features to help with that change management, but a lot of just coaching folks to say, this is technology that a lot of our onsite team members in particular have not experienced in their lifetime. ⁓ How can we best frame it to them so they see it as a support tool? Because I've yet to find a property management company that says, we have too many people on site. Most of them are struggling to hire people, right? So it's all about that framing of the tools.
David Moghavem (11:28)
Yeah, yeah. Exactly,
you definitely hear the, we don't have enough on site and we need help. And, but the goal is as many bodies as you're going to throw at us at a situation, at a property, it doesn't always help it. you need strategy, you need a clear workflows. And I think what Elise AI does is it brings those workflows to the front and the center.
Jacob Kosior (11:34)
Yeah.
David Moghavem (11:54)
in order to make things more efficient. And I think what you're finding too is you hit the nail on the head. I don't think AI is replacing people, but it's replacing the people who aren't using AI. And you're going to be beat out by someone who knows how to leverage this technology in order to be more productive and more efficient. And if you can leverage that technology, now the human capability can now go and talk to the resident and knock on that door because all the other tasks
are being automated already by Elise Ai.
Jacob Kosior (12:28)
Yeah, yeah, it's as simple as.
You know, I see this firsthand in my former life where, you know, David, you've got a touring appointment at three o'clock. You show up at three o'clock for the tour that you pre-booked, but that leasing agent's on the phone because calls are constantly coming in. Our focus is all over the place. So can AI answer that phone call so I can give you the attention for the tour that you just scheduled at three o'clock? It's things as simple as that that make the day easier for our on-site team members that make it better for that prospect to schedule their tour and to show enough
David Moghavem (12:44)
Yeah.
Jacob Kosior (13:00)
up
on time. And by the way, that person who called on the phone, now they can speak to the AI in 70 different languages, right? To be able to communicate in their preferred language. So we see opportunities like that across the board. It's just how our operators kind of putting together their stack of what's the balance of human and technology? Where does AI play a role? Where does HumanTaper play a role? And what's exciting for me as a former operator is every management company in the country will say, you know, we provide great customer service. We give white gloves service. But how many people actually have time to do that?
Our hope is that we're giving them that time back in the day so they can actually focus on the things that they market themselves around and that make a difference to the renters that they're supporting.
David Moghavem (13:39)
Yeah. So one thing I wanted to dive into is the difference between the generative AI, the LLMs that we're all used to when we hear AI, the chat GPTs versus this agentic AI. Talk to me a little bit about the difference and the shift of how we're getting away or maybe not away, but we're evolving from the generative AI to now the agentic AI where people are helping with automation and tasks.
Jacob Kosior (13:46)
Yeah.
Yeah, can you, I'm gonna ask you a question to self frame it like, what's your preferred platform if you're going on to like play with an AI tool?
David Moghavem (14:09)
Sure.
So I'd say my LLM is chat GPT. I've already, you know, first move, they had first mover advantage. They were the first LLM that was really like mass scale and I trained it. put my, I built my GPTs on it. So to switch now to a new LLM, like a brook rock or a Gemini, it's just, they've already hooked me. They already hooked me. So I'm already hooked on it.
Jacob Kosior (14:34)
Yeah, you're hooked in there, right? you log into,
yeah, you log into ChatGPT and it's like the Google homepage. What can I help you with today? Right? And so that's where all the...
David Moghavem (14:41)
Yep, it's already my homepage.
I already replaced it. Yeah. Yeah.
Jacob Kosior (14:43)
Yeah, you're one step ahead then.
yeah, that's we call that generative AI, right? Because you're going in and you're giving it a prompt and there's all the content in the world about how to write the best prompt to get that output. So I'd say think of that as that's generative AI. You're giving it a prompt and it is now generating content or an image or code in response to the prompt you gave. ⁓
David Moghavem (15:06)
And
Jacob, by the way, I don't even prompt it. I actually tell ChachiPT to write a prompt for me to prompt. Yeah, I'm prompting it to write a prompt. I'm like, write a good prompt for me to do this, and then I give it back to it, so.
Jacob Kosior (15:13)
write a prompt for it. There you go. You were prompting it to write the best prompt possible.
Yeah, and that's
where because because that's how most consumers, especially those who kind of are in deep in the world, like maybe you and I are like, that's their exposure to it. And they see AI is OK. It's the the generative part that that result is only as good as the prompt that went into it. So you've got mixed experiences with it. ⁓
David Moghavem (15:30)
Yeah.
Jacob Kosior (15:43)
Obviously we've seen ChatGPT introduce their agent tool and what we're looking towards and what we're building with agentic AI is you don't have to give it a prompt. You are building out the workflow. What are the steps that it needs to follow? What are the points that it needs to cross check along the way as it's following that workflow?
to do work autonomously, to be able to do things like collect rent or follow up on a work order or follow up on a renewal offer without being prompted, without being told because it's following a set of workflows. And so what excites us is, you know, for an industry that is turning over more than 40 % of its workforce every year, we've got how many folks in corporate seats that all they do is train. They train team members only for them to leave and then they retrain their replacements and then things change and they have to retrain.
again. So we're looking to a future to say, where can all these trainers or we're just spinning our wheels all the time? Can those just become workflow designers that you're designing the workflow of here's what I want the agent to do. Here's the process I want it to follow. And then it just goes and it starts to work. And it's really that agentic AI to be able to work autonomously and follow those steps that are allowing operators to kind of move beyond just the conversations or what they're seeing as the outputs to now say, ⁓ there's, there's work that's being done. We're bringing down the volume.
of work. And that's becoming exciting as we're expanding into new tool sets that are taking over manual work those team members used to do on site, not just the conversations that the AI is having with prospects and residents.
David Moghavem (17:13)
Yeah, so is the agents also helping your creating agents just resident facing or are do you also have it client facing as well with your operators? Like is the agent and genetic tools that you guys are building both for residents and for your operating partners or just for residents?
Jacob Kosior (17:35)
Operating partners too. We look at things like what our maintenance app is able to do now that's auto assigning work orders or reaching out to third party vendors. An example of, hey, that's work that a maintenance supervisor used to have to do, or maybe somebody's on the facilities team would oversee that now you just kind of give the AI those contacts. These are our pre-approved vendors that are in the space so that it knows, all right, if you need that third party vendor in to come in and clean the carpet, it can tag in the vendor that you've previously identified so it can help do that.
Now there's tons of opportunities about where we can go from there, but it's both the resident facing side. So things like our resident AI used to just communicate with a resident about their renewal offer. Now we're able to generate Blue Moon lease agreements too. So we're taking that one step further, not just conversing, but actually generating the lease agreement in real time. So we're servicing that customer when they communicate that they're ready to renew, but also for the management side, because it's really taking over some of those manual tasks that are filling their day.
David Moghavem (18:21)
Yep.
Jacob Kosior (18:35)
right now that are keeping them from either being able to scale their workforce, to become more efficient with their workforce, or to just focus on things beyond what they're doing in front of a computer.
David Moghavem (18:44)
how do you think operators should measure the ROI with this AI? Because we talk about in broad strokes, we're becoming more efficient because of it. We're able to reduce tasks and like, how do you measure that in a way where it's like, hey, this is yielding X amount of productivity because of this new AI hire?
Jacob Kosior (19:08)
Yeah.
Two buckets are I'd say the first bucket is new insights on like KPIs or performance metrics that we didn't have before right? I could always go to my PMS and pull a report That's like here's what all my agents did for the day How many emails do they send me phone calls, right? But missing from that is like well how much time how much time did Jacob spend making five phone calls versus David like there's no efficiency kind of like baseline metric there for us to measure that so our goal and reporting is not just kind of what
work
is being done, but how is it being done and how efficiently is it being done? That's where we're able to look at things like, hey, if you've got an asset that is not leasing well, we can go look at how much time is your team spending on leasing tasks related to rent collection or renewals or maintenance.
How is their time being spent? Not just what are they doing, but at a high level for ROI, we typically see it in three stages. Number one, it's what are the areas of asset improvement that we could point to? So are you collecting more rent than you would otherwise with delinquency AI? Are you collecting it faster than you would otherwise? Are you collecting more from past residents before you pass that file off to a third party collections firm than you would otherwise? ⁓ So what are those existing kind of asset level KPIs that we hope to improve across
leasing and collections and renewals and work orders. Typical KPIs. Yeah.
David Moghavem (20:29)
your typical KPIs that you otherwise would have. Yeah, exactly. And
then you were saying that there's some other ways to.
Jacob Kosior (20:37)
Yeah, and then
second from there is...
our industry is full of point solutions that were kind of layered on top to do various things, then now AI can do that. So that second stage that we typically see is tech stack consolidation. Like, do you need to be paying a mystery shopper to call your agents once every quarter to give them a score? If instead the AI is already listening to every phone call that they have and can score them against a rubric. Do you need to survey your residents about whether they're happy when we can tell the sentiment from the conversation it's already having with the AI and the words and
and
the verbiage that it's using. Yeah, do you need that point solution for these various things when we already have all these insights from the conversations, we just have historically haven't been able to extract all that to get the data. And so really tech stack consolidation is that kind of second phase of ROI. And then the third, and the one that we always work towards is centralization. To be able to say, you don't have enough team members today, hence all the vacant roles on site. For third party owners, you're always asking your
David Moghavem (21:30)
Mm-hmm.
Jacob Kosior (21:39)
management
companies to do more with less and now you have these tools that allow you to do both to work with a leaner staffing model and to do more with fewer people and hopefully fewer technology tools too. So it's really that kind of third goal of centralization that a lot of folks are are moving towards right now even those that said you know centralization isn't our model once they start to see what the AI can do and they get feedback from their team members of
My day is more open than it was before. It allows them to rethink, well, what work are you doing? And how do I rethink my staffing now as we've got new technology that we didn't have even as recent as a couple years ago.
David Moghavem (22:16)
Right, right. And we already touched upon the centralization part of it and the implementation of it. I think the tech stack ROI is really, really critical because you're starting to see, I mean, there's so much prop tech out there now. And the easy solution as operators is, yeah, this is a value add. Let's just allocate it per unit to our portfolio. And then you start looking at the financial statement and you're
Jacob Kosior (22:26)
Yeah.
David Moghavem (22:42)
can't afford all this PropTech stuff. Like no matter what the benefit is, like the GNA is just getting out of hand. And you're seeing it on other properties too, as we're underwriting, we're like, why is there GNA a thousand a unit right now? It's like, well they have 50 PropTech ⁓ allocations. And I like what you said of consolidating the tech stack of making sure that you're able to have
Jacob Kosior (22:43)
Yeah.
David Moghavem (23:10)
you know, a tool like Elise AI, calculate and perform on multiple parts to make it more efficient rather than hiring 50 different tech companies to solve 50 different tasks.
Jacob Kosior (23:22)
Yeah, I mean this thing's as simple as I've been guilty this for
My past decade in multifamily was my PMS platforms were built to be email first. I often worked in student housing where we needed to be text message first, because that's how our demographic of renter was communicating. So I had to go get point solutions for mass texting just because my PMS was not built for that. ⁓ Now we're in an age and this is kind of Elise's goal is why do we have inconsistent customer experiences, whether it's email, text message, phone or chat? All of our tools are built to be on
channel across all of those, including being able to do mass text messages too. So yes, you've got the AI there that can verse with all of your current residents, but you can also do a mass text message to all of your future or your current residents through that same phone number. So easy solutions like that to say you've layered on these tools in the past because the legacy platforms were not built for modern operations. And that's where we see opportunities for an AI native platform that is just doing work differently, really aligned with how our customers are expecting to be served.
David Moghavem (24:26)
Yeah, and what you find also is the different point solutions that you've hired, they don't integrate with one another, right? If you're using Yardi instead of AppFoly or vice versa, you can only use these type of tech tools versus this. my question, guess, is with Elise, how have you guys been able to kind of integrate with some of the bigger tech platforms, accounting software, the Yardies of the world, ⁓ to be able to integrate with them and make sure that it's a seamless process, which
ends up showing to the residents.
Jacob Kosior (24:57)
Yeah, we're lucky to have good partnerships with all the large PMSs. We do have some limitations on what can we push and pull. ⁓ So there are slight differences between the platforms on what we have access to or what we can push and pull between the platforms. We're also realizing too that, you know,
We're sitting on an increasing amount of data and insights about customers. And sometimes we can't push those back into platforms. Like our leasing AI might know from a conversation with you, David, like, Hey, what's your pet's name? Or what's your birthday? Or what's your favorite kind of cuisine that you shared as to why you're looking around the area? That's data that we could house somewhere and utilize, but there aren't data fields in legacy platforms for us to push that detailed information in because they weren't built for the types of conversations that we're actually having in practice.
So
we're lucky to be able to integrate with them on tools. We also see the value of having our own CRM. That's why we launched Elise CRM. And for other integrations, we're looking at what's really going to enhance the resident experience of the prospect experience there. So we've announced two recent integrations with Flex for flexible rent payments. So if delinquency AI is reaching out to you about your rent payment, but we know that you're on the Flex payment plan because of that integration, we can stop the AI from following up with you.
flexible rent payment. We're also integrating with built as well to be able to highlight built as a rewards platform and help make that a more seamless experience for current residents who are either paying via built or utilizing the built reward so we can enhance that experience while also freeing up the onsite team to having to answer questions about those platforms or how they function or push the signups.
David Moghavem (26:18)
Nice.
That's great. mean, that's huge that you guys are integrating now with Flex, ⁓ especially in a time in the market where delinquency is just becoming the pain point with all these deals. think nationally people are starting to feel the stretch. I think you're finding renters by necessity throughout the country and they need Flex. They need Flex payment. And so to have Alisa.ai integrate with that and be able to work with residents and
create a better resident experience by, instead of some AI tool bombarding you every day. And it's like, I'm on flex, like relax, all right? So I think it's important. I think that's very important. Jacob, I guess one question is a lot of our industry, real estate, we're laggards, we're slower movers.
Jacob Kosior (27:13)
Yeah, yeah.
David Moghavem (27:31)
but we're seeing that that's starting to shift, that's starting to change. What's your advice to multifamily operators on how to embrace AI technologies and how to think strategically about implementing AI into their processes? How should they be thinking about their processes in ways where they're like, this is a good candidate to automate or improve that workflow?
Jacob Kosior (27:56)
Yeah, it usually takes some prep work, I think.
For operators who are just looking to layer AI on top of their existing operations, it's going to identify some inefficiencies. It's going to identify some inaccuracies in your single sources of truth out there. And those are the people who often get frustrated, who are like, all right, I'm just going to let my human team members do this. We'd see that as a former operator myself, I'd say that's short-sighted because while you're stopping, consumer expectations are continuing to move forward. So for those who are going to be the most comprehensive change,
to
really leverage the technology with the opportunities that exist today. It's let's implement the AI, let's see what we learn from it, and then let's take a step back and say, all right, what do we need to change now as a result of it? Or how can we integrate it so that we're not just layering on top of existing inefficiencies, but really working to fix the inefficiencies that it's introduced today? I'd say for those, we'll still hear from folks that are saying, we don't want to be test cases for this. We want to see it's
kind of proven out for others, ⁓ we think we're past that point at this point. We recently did a survey that showed vast majority of people are already implementing or are past the implementation phase, and now they're moving on to optimizing, whether that's staffing or rethinking their policies and processes as they exist today to be able to leverage AI, all with the goal of of speeding things up, making it easier for the renter, making it easier for their team members. And I'm very much of the mindset that...
David Moghavem (29:04)
Right.
Jacob Kosior (29:27)
Consumer expectations are just going to fly off the charts here in the next couple of years. I just saw that even chat GPT is launching. So you can make purchases with your chat GPT agent. I think it's through Etsy first and then Shopify coming after that. So if shopping habits are becoming that quick where I can just tell my AI agent go and buy me this thing, why does it take me seven days to apply for and be approved for an apartment? It's going to be, you those are the expectations that we look at to say it's only going to get tougher
David Moghavem (29:37)
Yeah.
Yeah.
Right?
Jacob Kosior (29:57)
satisfy the renter so those that are kind of sitting on the sidelines waiting to see it kind of proven out I'd say it's already been proven out and just by sitting on the sidelines you're pretty far behind the competition at this point.
David Moghavem (30:07)
Yeah,
once Agentic is now having the ability to make purchasing power decisions, that's when it gets a little dangerous. But I think back to your previous point, before I think operators didn't want to be the guinea pig. They didn't want to be the lab rat with ⁓ some of these tools. I think that's shifting now. I think now operators are looking for an edge, or at least the smart operators are looking for an edge where they're like, yeah, you know what?
Jacob Kosior (30:16)
Yes, yeah.
David Moghavem (30:37)
I'd like to beta test this. I'll oversee it, make sure the pain points doesn't hurt operations. But how can I become more efficient? How can I be a better operator? How can I find alpha through my ops? And especially a group like us that we self-manage, we kind of look for those opportunities in the sense of trying to embrace some of these tools in order to, yeah, we're not the lab rat. Instead, we're trying to be the first mover. We're trying to make the resident experience better. We're trying to...
see how we can improve operations so that we can implement that and scale that through different acquisitions, through different properties, and be able to get better returns for that regard.
Jacob Kosior (31:18)
Yeah.
Yeah, it's folks like you that are kind of moving the needle faster than it would be otherwise. Cause whether it's acquiring that due deal and how can we do this better than we have in the past, or you're looking for a change in management. And we work with a couple of different operators right now who are proactively saying, how can we work our AI strategy into our RFPs or into our pitch materials to be able to say, this is how we're differentiating ourselves in the space. This is where we're saving the time for our human team members to improve that customer experience on site. And this is where we're leveraging AI tools.
to be better at collecting rent, faster at signing leases, faster at getting renewal offers. that's really caught fire, seemingly here in just the past two quarters, about management companies saying this could be a competitive advantage in their markets or with smaller operators being able to compete with some of the larger operators even on how can we deploy these tools, how can we be on the cutting edge, and how can you kind of do things differently than you were in the past to achieve better results.
David Moghavem (32:16)
And I guess one of the ways that you guys are kind of growing now with your series E funding of $250 million, what's the goal of that funding? What are you guys trying to get done? I'm sure it's more than just raising money. There's a plan with that money. So give a little bit of a sense of what that money is gonna be used for.
Jacob Kosior (32:36)
Yeah, it's primarily focused on hiring. We've grown to over 300 team members right now. We're trying to go to over 500 team members by the end of the year. And if you see our CEO, Mina, she recently posted on LinkedIn about our hiring numbers because that's what we see is our biggest challenge right now. How can we get the number of team members that we need to continue to grow the product suite on the engineering side, continue to develop the product suite on the product side? We've also built out an entire strategy team that is just there to help operators with
business transformation. So great, you've got the AI tools. Now you've also got access to our strategy team to help you implement and optimize those AI tools or help you centralize if that's the goal too. So a bulk of those funds are being put towards hiring just so we can build the team that we need to continue to deliver for our clients.
David Moghavem (33:25)
All right, great, you heard it here first. Elisei is hiring. ⁓ Yes.
Jacob Kosior (33:29)
Check out our careers page. There
is a role for everybody. If you are talented and hungry and ready to move fast to disrupt things, we want to talk to you.
David Moghavem (33:37)
Awesome. And I'll put in the show notes ways to get in touch with Jacob Kosior And Jacob, it's been a pleasure and an honor having you on. Really appreciate it. And looking forward to see what Elise AI is able to do next.
Jacob Kosior (33:53)
Me too. Thanks for having me, David. Thank you for all the shout outs that led me to be here. We're happy to chat anytime.
David Moghavem (33:57)
Yes,
of course. They're genuine shout outs. mean, we're not paid to make those shout outs. At least not yet. We'll see. So those are genuine shout outs. You guys have a great tool.
Jacob Kosior (34:01)
Yeah. ⁓
Yeah
David Moghavem (34:11)
and get it going throughout our portfolio. So thanks again.
Jacob Kosior (34:14)
Appreciate it. Thanks David.