The Group Dentistry Now Show: The Voice of the DSO Industry

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Welcome to The Group Dentistry Now Show: The Voice of the DSO Industry!

Understanding Dental Front Office AI with TrueLark & The Smilist

Phil Toh, Co-Founder & President of The Smilist & Eric Weeden, Head of Sales of TrueLark talk front office technology & AI:

Change management in the age of AI
Clearly defining front office AI
Real world AI implementation

To learn more about TrueLark visit – https://truelark.com/ to get a demo of what TrueLark can do for your dental group visit – https://truelark.com/demo/

You can connect with Eric Weeden of TrueLark via email – eric@truelark.com or you can find him on LinkedIn – https://www.linkedin.com/in/ericweeden/

You can also learn more about The Smilist here – https://thesmilist.com/ or connect with Phil Toh on LinkedIn here – https://www.linkedin.com/in/philiptoh/

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DSO Podcast – From Voicemail to Virtual Reception: How AI is Transforming Patient Engagement in Dentistry Podcast Transcript

Welcome to the Group Dentistry Now Show, the voice of the DSO industry. Join us as we talk with industry leaders about their challenges, successes, and the future of group dentistry. With over 200 episodes and listeners in over 100 countries, we’re proud to be ranked the number one DSO podcast. For the latest DSO news, analysis and events, and to subscribe to our DSO Weekly e-newsletter, visit GroupDentistryNow.com. We hope you enjoyed today’s show.

Bill Neumann: Hey, welcome everyone to the Group Dentistry Now show. I’m Bill Neumann, and always thank you for joining us, whether it’s watching us on YouTube or groupdentistrynow.com, or maybe you’re listening in. We really appreciate it. And returning guests and a new guest here today, we’re going to talk about understanding how AI is redefining the front office. Boy, we talk a lot about AI, and I think there is a little bit of AI overload. So we want to really kind of dig deep into what AI solutions are available now, and maybe even define what front desk AI is, because Gosh, it is pretty overwhelming. And we talk about it a lot. And I can imagine for somebody like Phil To, who’s the co-founder and president of The Smile List, you must be inundated with people trying to sell you AI. But good to see you, Phil.

Phil Toh: Good to be back. Excited to talk about our experiences and how we think about AI.

Bill Neumann: And for the first time, but if you’ve been to a DSO meeting recently, you have probably seen Eric Wieden, head of sales at Truelark speak, or at least you’ve seen him at one of the shows. I know I’ve seen you a couple of times, Eric. I think I saw you at DSO Tech Summit, Dykema, ADSO. So you’ve been really at a bunch of them. But head of sales at Truelark. And it’s great to have you on.

Eric Weeden: Yeah. Thanks for having me, Bill. I’m excited about the conversation today.

Bill Neumann: Why don’t we start with you, Eric, since you’re new to the show, a little bit about your background. And can you talk a little bit about Truelark?

Eric Weeden: Yeah, definitely. Thanks, Bill. Yeah, so my background has always been in SaaS software as a service in emerging technologies. Personally, I’ve been with TrueLark for about six years. TrueLark is an AI-first company that really was created to build a purpose-built AI platform for the dental industry. So my journey over the last six years has really been focused on helping dental practices and DSOs and variations of DSOs adopt AI to improve efficiency and elevate the patient experience. So very happy to participate today and share, you know, TrueArc’s vision and have a conversation with thought leaders like Phil and yourself.

Bill Neumann: Thanks, Hark. And so I’ve known Phil, I don’t know Phil, at least a decade now. It goes back, hearkens back to your days at Henry Schein and meeting you in Melville. But we had you on probably a couple of years back. It’s gotta be a couple of years now. So I think it’d be good for people to maybe get to know you a little bit and then also talk a little bit about where The Smilest is now in 2025.

Phil Toh: Yeah, no, a lot has happened since since we’ve met and even, you know, since the last time I was on the show. So Smilus, you know, a bit about the Smilus. We started in our first practice was in 2014. And so we’re just about 11 years old now. And since then, we’ve grown from, you know, we started on Long Island, New York, where we bought our first practice. just to now we are across seven states from Delaware up to Massachusetts, and we have 115 locations. So we’ve kind of grown a lot, primarily kind of through acquisition. And so with a lot of growth, you know, comes with, you know, our model is really to integrate and how do we leverage technology. And so that’s why, you know, I’m excited to kind of speak here because when we talk about AI, You know, I think probably oftentimes people think it’s about kind of diagnostic, you know, AI, but really kind of AI has lots of different applications and we’ve been able to use it in different areas and helping us to make our rapid growth sustainable as well as scalable. So very excited.

Bill Neumann: And your practices are, the practice profile is pretty unique, I would say. You have some larger practices. What would you say, if you had to guess the average operatory’s count is?

Phil Toh: I would say probably a little over 12. Yeah. So we have as large as I think we have some that are over 25, but the average is 12. So we do like a large format office. It allows us to, we talk frequently about how do we become the dental home for our patients. And so that a lot of that means like, you know, how do we provide, you know, the GP services as well as specialty services, as well as, you know, the convenience of, you know, whether it be parking, availability, online booking, things like that. So. So, yeah, so we tend to have a larger box than than the typical average dental practice in the US.

Bill Neumann: great. Thanks, Phil. Eric, why don’t we kick things off? I talked a little bit about this with a little bit of AI overload in the industry. And I think maybe we get back to basics and Phil touched on diagnostic AI and that seemed to be the first thing AI that came into the dental industry. So a lot of times we think about solutions like that. Do you have a good definition for what front office AI is? And we’ll start with there, just with the definition.

Eric Weeden: Yeah, I think in a real simple, clear, concise definition of it, front office AI through the lens of TrueLark is a virtual front desk managed by an AI control center that takes patient inquiries across multiple channels. And that’s an important point. In schedules appointments, and engages leads automatically. And when I talk about scheduling appointments and engaging leads, I’m not talking about task awareness, but task completion. And so that’s another main point that I’d like to make. All while the outcomes are freeing up staff for patient care, with improving efficiency and revenue, all while delivering a fantastic patient experience. So that’s really what we’re getting at when we talk about patient or AI for the front office.

Bill Neumann: And Phil, would you say a lot of your peers, a lot of the DSO leaders out there, do they have an understanding of what front desk AI is?

Phil Toh: I think they’re learning about it very quickly. I would say probably a common theme across kind of all DSOs, you know, doesn’t matter where you are in the country. It’s just, it’s very difficult to staff, right, to staff and train. you know, the front desk staff. And so as a result, I think many of us are forced to, you know, look for and explore and implement new technologies that can help address that. You know, it could be, you know, a call center. That’s probably, you know, fairly common, particularly as you get to a certain size. But I think there’s a lot of kind of AI technologies out there, you know, like TrueLark, that are getting, you know, a lot more kind of airtime with DSOs on how to, you know, whatever, do all the front desk operations that aren’t being done, you know, because there’s just not enough, you know, staff to be hired.

Bill Neumann: So Phil, from an impact standpoint, you’ve got the impact for the front desk staff. So there’s that impact. And of course, I guess for the staff in general, there’s also your impact, right, at the DSO. And then, of course, the patient impact. Can you talk a little bit about how that’s been working with TrueLark and implementing front desk AI or front office AI?

Phil Toh: So we’ve been working with TrueLark for, I don’t know, maybe like three years now. And it stemmed from exactly what I said, you know, the difficulty in terms of hiring staff. And, you know, and as a result of that, you know, many more phone calls kind of missed than we would like, you know, there’s kind of various industry kind of stats. And I would say we were kind of within that range of, you know, let’s say, 25% to a third of calls that are being missed. That’s a tremendous amount of, you know, opportunity for the practice, but also kind of, I’ll say, a failed, you know, patient experience, you know, and then, you know, you’re always going to get told some story of, oh, well, they called back and this and that. And ultimately, we got them appointed. But that’s not the bar. The bar is when somebody calls, we want to be able to pick up the phone and then be able to offer them an appointment. And so we get kind of pitched all sorts of different solutions and, oh, well, they can book online and this and that. But the reality is, the, you know, we want to be able to support patient interactions the way they want to interact with us. And that can be, you know, over the phone, it could be online, it could be after hours. And so, So in working with TrueLike, it really helped us to address those things. So it could be interacting via text. You know, we’re working with them recently in terms of, you know, more of the AI voice kind of technologies. They’re able to book online. And, you know, because it’s kind of text based, can operate kind of any hour, you know, hey, I just remembered I need to go make my you know, my appointment at, you know, 1130 last night, that we should not, you know, preclude them from interacting with us when it comes up. You know, it’s hard enough to kind of get patients to come to the dentist. Let’s not put up additional barriers in which, you know, they can find ways to make an appointment.

Bill Neumann: From your perspective and maybe your staff’s perspective, was there any hesitancy in implementing AI? I mean, did you get any pushback? What’s that been like?

Phil Toh: Oh yeah, no, absolutely. Everybody that says no, I think is lying. So yeah, I like to tell the story because sometimes you just get these unexpected results. So when we first implemented TrueLark, there was some anxiety of, oh, is AI going to replace whatever my job type of thing? And so we had to overcome that. But once we got people comfortable, you know, and say, hey, we’re piloting and kind of getting them used to actually using the software, we start getting feedback of you know, I guess the stat and the feedback were telling two different stories. So the stats were, wow, you know, look at, you know, we’re now addressing many more missed calls. We were booking appointments, we were answering questions. And we saw that patients who wanted to interact with us via text, and kind of that, you know, 24 seven, you know, around, around the clock. And so we were like, the stats are telling this wonderful story that we’re doing a great job. And then, but the feedback from the offices were like, oh, this is like a terrible system. It’s creating so much more work for us. And we’re like, well, how is that possible? Because, you know, look, we’re seeing it’s it’s booking appointments. It’s answering questions. And, you know, we even have the volume of calls. And then the staff goes, well, I’m embarrassed to tell you, say this, but because let’s say in the past we got ten, ten missed phone calls. maybe one or two would leave a voicemail. And then now I would call that one or two. But now Truelark is addressing all 10 missed calls. And let’s say makes an appointment for five of them. He goes, now there’s five calls I need to make back. You know, and so their call volume or kind of callback volume went from one to five, and that’s how they were feeling the impact of AI. Now, they understood, and that’s why they said, you know, they were embarrassed to tell me the story, because they understood that that was what’s good for the patient and good for the practice. But it really kind of changed the dynamic on, you know, how the office work because they were just so accustomed to, OK, I checked, you know, the voicemail. I only got so many voicemails and those are the ones I’m calling back. So when when AI or kind of it doesn’t have to be any new technology gets implemented, I think it’s very important to kind of go through. You know, I think it’s pretty standard. Everybody does the pilots. but to kind of be able to discover these kind of unintended consequences, both positive and negative, so that, you know, so that you’re able to roll it out and set the expectations and communicate it, you know, more appropriately to the team so that there’s less anxiety and less fear on, you know, what this technology is going to, you know, impact them.

Bill Neumann: Yeah, there’s definitely this fear factor. Go ahead, Arik. You’re going to probably agree.

Eric Weeden: Yeah, I was just going to chime in on that. When you think of one of the main challenges to implementing AI and you think about some of these stats that we hear out there about the high percentage of AI projects that aren’t successful, To me, a lot of it boils down to exactly what Phil was talking about, what we’re on this topic of, is that the challenge rarely is technical. Usually, it’s not a technical blocker. There’s an answer for that, but it’s change management. It’s a lack of buy-in at the staff or provider level. Even when the leadership understands the value of TrueLark AI, But as a result, you know, adoption can be very slow. It can get kind of torpedoed, as I like to say, because the providers just don’t have the confidence in the system to feel like, you know, it will adapt to maybe the way they do things. And sometimes there’s fear that, you know, might be replacing, you know, the role or like diminishing their value. And on the flip side, when projects go really well is when someone is there that is managing the project, not only from a technical perspective, but one from a change management. And that’s one of the things that stood out when working with Phil at The Smile List, is that Phil, you really took it an extra mile to communicate the why behind the project. What are we doing? Why are we doing this? what does good look like? Let’s, you know, look at it from an objective data-driven perspective, but also not lose qualitative, you know, feel of it in terms of, you know, what the staff impact is, what the patient impact is. And so as a result, while there aren’t challenges in every, you know, adoption of a new technology from change management, the SMILEST did much better. And I credit Phil and his communication style and his group leadership that made it, you know, more successful. than others that I’ve seen out there.

Bill Neumann: Yeah, definitely. Change management’s a huge challenge. Anything else, Eric, that you’re seeing out there with other DSOs that you’re working with beyond that, other challenges or different scenarios that you might run into?

Eric Weeden: Yeah. I mean, a couple of things that stand out, you know, the I would say that every location is different. Everybody at least feels different, right? And also, there’s a lack of standardization. I mean, in some DSOs, there’s more standardization than not. The fact of the matter is, you know, you often have, you know, five different PMS platforms out there, array of tech stacks, different ways of scheduling as a result. And what our approach at TrueLark is not to force everybody to go out and get standardized. We know that’s not most is not going to happen. And so what we do is we take an approach where you don’t need to standardize to be successful, but you need a system that can accommodate that variation. And so a lot of people out there don’t really understand that that’s even possible. And so they don’t necessarily have an open mind that somebody could actually take their unique way of doing things and create a platform that can work around that. So I think that’s one of the challenges out there. And that’s just a matter of you know, kind of having an open mind, a growth mindset that, you know, hey, while we do things differently, you know, we can work with this team, work with this platform to configure it in such a way that it can actually provide value to us.

Phil Toh: Yeah, and I actually want to build on that, actually, because oftentimes, you know, people view technology, they get a bad rap in the sense that, oh, it’s this kind of cookie cutter. And, you know, it’s McDonald’s for everybody. But the reality of the way we think about it is how can we provide more of a personalized service to the patient? leveraging technology because they can, you know, have almost like an infinite amount of customization, you know, down to be a patient, it could be a staff, it could be an office, and to deliver it 100% of the time. So going back to what I said earlier about, you know, kind of shortage of staff, I think we all have stories in terms of, hey, you know, I should have followed up with this patient and I didn’t for X, Y, and Z reasons. But once you start leveraging technology, you’re able to address 100% of, you know, those needs. Now we have to spend time in terms of defining, you know, hey, these are the rules or kind of how we want to engage with the patient. But once you’re able to do that, you’re able to do it, you know, constantly and touch like many more of the patients and making sure that they get the treatment that they need. And that is, you know, very difficult to do when you’re trying to hire staff, train staff and, you know, and then inevitably just, you know, all the day to day requirements of working within an office. consumes their time. And so it’s, it’s, so to me, it’s the opposite is how do you use technology to provide, you know, a very customized service to 100% of all your patients. And an example I like to use is like if, if we were all to open up you know, Amazon in our browser now, it would look very different amongst, you know, the three of us. Right. And it’s because it’s understood like, hey, these are our purchasing patterns and what our preferences are so that it gives us a customized experience. And to me, that’s the power of technology and how it can be leveraged for the patient experience.

Bill Neumann: Eric, this really, thanks, Phil, because that actually ties into the question I had about a purpose-built or a purpose-driven AI platform. So TrueLark’s a little bit different that way. There are, you talked about Cookie Cutter, Phil. Talk a little bit, Eric, about TrueLark and how it’s truly purpose-built.

Eric Weeden: Yeah, you know, we got our start back in 2018, which compared to a lot of the players in the space is, you know, many, many years ahead. And for a while, we were a little bit of the only ones out there doing what we do. And so by purpose built AI model, you know, our founders had PhD in machine learning. And so we went about creating our own model, we deployed it, you know, to the world and in the dental organizations that we’ve been working with, that model has been consuming data for years. So literally thousands and thousands of conversations across multiple channels, booking thousands and thousands of appointments. And as a result, one, it’s taught a lot about the various use cases that are most common that are coming into the model. It’s allowed us to innovate and develop and configure some pretty unique things around that. At the end of the day, really, what we’re comparing it against is a generic thought. The key differentiators there is the ability to handle real-time patient conversations to completion. Handle rate is something that we measure, booking request conversion rate is something that we measure, and we maintain very high percentages across those measurements as a result of it being purpose-built. And so out of that, we are able to integrate into multiple PMSs, manage a vast variety of scheduling, different types of scheduling, and scale across multiple locations. And again, we like to think of TrueLark as 1,000 configurations in a box. So it’s that ability to really configure to match each practice’s workflow. and support nuances of decision-making that really set a purpose-built AI model for dentistry aside from something that might just be leveraging a large LLM. Just maybe an example that we can identify with. Let’s take a peri-op practice where you have a patient that’s calling in, They’re calling in looking for an appointment. And the AI in this scenario has the ability to, one, understand, OK, this is a prior patient calling in. We’re going to determine if they’re new or existing. And the AI has the versatility to ask if they’re coming in with a referral and if that referral is a doctor in the network. If it is a doctor in the referral network, the AI has the ability to traffic that conversation differently as opposed to if they’re not. And so they might offer them priority scheduling. They might offer them a little bit of a different conversation and different workflow as opposed to somebody that’s calling in without a referral. So those are just little examples that you’re going to get from a highly configurable, dedicated platform to the dental registry.

Bill Neumann: So as we look at maybe the future of AI, Phil, are there a couple of things on your list that you’re hoping that Truelark implements? What are those couple of features that you might be interested in? Maybe Truelark’s already working on them.

Phil Toh: Yeah, so one of the things that I think, you know, is the future is right now, you know, largely many of the systems kind of operate somewhat independently, right? Or maybe at best kind of they connect to the PMS software. I think the future is more, you know, where do they start connecting to more and more pieces of all the systems, you know, that we have. And so I joke about how, you know, AI normally is like, you know, super smart because it knows everything. It’s kind of read everything and incorporated into their models. But in a dental office, typically, you know, front desk is actually smarter than AI because the front desk is able to navigate to all the different systems to get the the information and the context to be able to, you know, either schedule a patient or submit a claim and so forth. So to me, the future is one, how do you connect all these systems together so that whatever the purpose built system is, they’re able to leverage much more information to be able to enhance that patient engagement or patient interaction or even internally within staff. And then I would say the second piece is Right now, I think most systems are largely reactive, right? You know, I missed a phone call or I, you know, whatever I had, you know, a service was provided and then I submit a claim. But I think a future is more about how can it be more proactive? How can an AI system anticipate a patient’s need and be able to reach out? And so, you know, it could be scheduling related. It says, oh, I noticed that, you know, whatever, my wife and I are coming on different days. you know, and it would be able to suggest that we can come in on the same day. Or it notices that I have, you know, kids and the orthodontist is going to be in the office and to proactively offer ortho consults. So if you could connect to all these different things and then, you know, once you’re able to offer the appointment, you can also kind of be able to communicate and let them know, hey, here’s the, you know, the ortho benefits. you know, that you have under your, your dental insurance. So being able to, again, earlier, I mentioned about, you know, doing it, you know, at scale. So now imagine a much more personalized service, you know, earlier, I also use the example of like opening up Amazon. So now you have these basically AI systems that are able to communicate, knowing kind of everything and being able to not just know, but also be able to predict and anticipate what are your preferences and needs. And I think then it makes going to the dentist much more pleasant of an experience.

Bill Neumann: We have an audience, it’s a real mix, large DSOs, a lot of emerging groups out there as well. Phil, do you have any thoughts or suggestions for the leaders at these different groups as they’re trying to evaluate, like I said, a crowded, crowded marketplace? A lot of AI solutions, a lot of, you know, front office AI solutions out there. They’re not all the same. So how do you go about evaluating a solution like TrueLark that is really built for that long haul because there are a lot of startups out there too and so are they going to be around? Are they going to be solutions that are going to work for me as I scale up? What was your process really as you go evaluate not just front office AI but technology in general?

Phil Toh: Yeah, so many of the things that you said, I mean, certainly viability of the company, it certainly crosses our mind. And I want to build on a bit of what Eric said earlier. Generally speaking, I would say that, you know, the technology is there or whatever, if you have some unique requirements, they can generally be enhanced to whatever to meet your needs. I think the piece that’s not kind of focused on enough is both the change management as well as the, you know, whatever the the customer service relationship aspect of it, you know, because oftentimes, you know, just as I said, the front desk is stretched, I would say in general, you know, any practice or a DSO, they’re going to be stretched for resources. And anytime you’re implementing kind of big technology products, it requires a lot of people to to be engaged and, you know, and we can’t manufacture time, you know, out of nowhere. Generally speaking, I would say, you know, people are very busy and stretched. And so we will oftentimes lean on our partner to kind of assist us with that implementation. We certainly have to do our part to be the internal champion, but, you know, we need their engagement, whether, and I’m not talking about, oh, it’s just like the, you know, we’re going to have a kickoff meeting and a weekly meeting, but how are they engaging with the staff? Can they relate with the staff or is it, Hey, you know, whatever, I’m this kind of brilliant engineer that I have no concept in terms of how dental office works and and how to engage with that dental office and to speak their language. All of that stuff is important because, as Eric said, the change management component is a huge lift. And when we don’t have partners that can assist with that and that we trust, Because look, at the end of the day, if the offices kind of say to us, like, hey, you know, you guys are are idiots. Like, why did you pick this partner? They’re terrible. They don’t understand the business that the solution doesn’t work, then that’s egg on our face. And so we’re kind of in this together. Um, and so it’s so important to really understand like, hey, what, not just, you know, what is the smallest process, but what is the true large process, and the teams and the people underneath that they have to support that to deliver a successful implementation. We’re, you know, we consider ourselves pretty tech forward, and we like to adopt technology and toy around with it to understand what works and what doesn’t. So we’ve done a lot of these. And, and that’s a lot of, you know, our conclusion that we’ve come to, you know, we weren’t perfect at the beginning, I’ll say we were wowed by the features and benefits. And we didn’t focus enough on the team on their side and their ability to influence and motivate change on our side. And I think that’s super important.

Bill Neumann: Well, I guess, Eric, I’ll put you a little bit on the hot seat now. So in order to ensure that Phil doesn’t have egg on his face, what are you doing really to ensure that Truelark really keeps up with these growing DSOs and can scale with them?

Eric Weeden: Yeah, I think it really falls into four cornerstones of a good platform and the platform that we’ve been working on. And it’s going to be, you know, one configurable. So we’ll continue to make sure that standardization is not something required for success and that we have the ability to configure the platform in such a way that it can accommodate various use cases, various nuances. Everybody schedules differently from one practice to another, different workflows. Second, I would say comprehensive, ensuring that the patient journey doesn’t have to follow a single path. And that really gets back to our approach to being multi-channel, multi-modal. So we invention, you know, a comprehensive platform where, you know, a conversation may begin with outbound, you know, communication that is initiated by AI that transfers from voice to text and back and forth. The other thing is automation. So just again, not task awareness, but task completion. And so automating the vast majority of conversations that come in across these different channels from A to Z so that we can, again, buy back time for staff so that they can focus on higher value activities and scale faster. And then I think the last one, and we were talking about this at various points, is extensibility. which is often overlooked. And so we’ve architected a platform that is extensible so that we’re not pigeonholed into just meeting today’s needs and use cases, but are able to extend the platform to take on new use cases as they come. And so the idea there is that we build once and scale fast. And so, you know, with new channels that have come on in recent years, like voice layering that on top of, um, you know, text with chat kind of being the glue between the two without having to configure each one individually and distinctly. So I think, um, those, those four areas, extensibility, automation, comprehensive and configurable are something that are always going to be on our mind and that we’re going to be pushing the platforms, you know, to, uh, to be on, you know, the, the cutting edge in each of those categories.

Bill Neumann: So as we wrap up the podcast here, great conversation. Do you think it’s a critical time to be looking at front office AI or do you think, well, I can wait another year and hopefully things will get better and different and easier and my staff will be more accepting of this type of change? I’d love to get your feedback, both of you. Maybe Phil, we start with you.

Phil Toh: Yeah, so I totally agree that if you waited, it would get whatever, bigger, better, faster. At least our view on it is, you know, like we say a lot internally, don’t let kind of perfect stand in the way of good. And so we believe that there’s a lot of value in learning how to adopt technology, to implement technology, and just to be kind of part of our DNA. And so we’re constantly like looking to try new things because we think we, you know, it’s not just the technology kind of getting better and faster, but it’s like, we need to get better and faster as well, you know, as an organization. And I can certainly see that to be the case over the last, you know, four or five years as we’ve implemented new technologies within the organization. So, So I always think, you know, the best time is today. And, you know, and so for us, it’s more around, how do we prioritize and, you know, making sure that we’re implementing things that, you know, have have the most kind of benefit within the organization. But we we do not have that wait and see approach because we want to get better at it. Because if you don’t do it, we learn from doing and if we don’t do it, then we’re just going to keep falling behind.

Bill Neumann: I think that’s, that’s a great point. And, you know, it’s, if you wait for perfect, you’ll be waiting next year and the year after. And so that is, that’s, that’s a great point. Eric, from your perspective, I mean, we fall far enough along as an industry, and you as an organization, and where the The solution is developed enough where, you know, it’s this is something that can be used every day and something that you’ll see benefit with right away.

Eric Weeden: Yeah, definitely. I agree with Phil. Perfection is the enemy of execution. There’s a lot of low-hanging fruit out there now. You might look at it and say, well, we miss on average 300 conversations a month at a given dental office. Maybe 67% of those will be scheduling related. let’s say that your handle rate today on those is 65%, maybe in a year or two, that might be 70%, 75%. So yeah, you could wait and have a higher handle rate. But the reality is, by waiting, you’re still missing on average, about 30 appointments that can be booked through AI, half of those being new patients, which we all understand. LTV on 15, 20 new patients is considerable for any practice. So yeah, now’s the time. The technology’s there. And especially with recent economic environment, a lot of people are focused on same-store growth. And AI has a lot to offer in being able to realize, you know, a healthy same store growth. And so I wouldn’t, you know, my advice would be don’t delay, you know, pick a company that has built a platform that is extensible, that is configurable, that is, you know, comprehensive. And then, you know, get in there, work with them and, you know, optimize the platform for your unique needs. And that’s only going to continue to get better. But I think it’s about diving in and creating those partnerships and, and, um, taking what is good now and only, you know, taking it further to be excellent.

Bill Neumann: And I think, you know, the wait-and-see attitude is, things aren’t changing with recruitment and retention, right? So we have challenges when it comes to finding front-office staff, free them up to do the things, the ones that you have there. free them up to do the things that are really challenging, free them up to be with the patients that are there now, maybe to handle some of the insurance issues. But yeah, you’re right. I mean, I don’t think waiting is the right answer. And I think we’re at a point where AI is developed enough and I think can really benefit DSOs today. So it was kind of maybe I’ll ask for final thoughts, and then if you wouldn’t mind, how do they learn more about TrueLark, Eric, and contact information? And then, Phil, for the audience, how do they get in touch with you? And if somebody is with an emerging group, maybe wants to partner up with Smilest, how do they learn more about Smilest? So, Eric, maybe we start with you and finish with Phil.

Eric Weeden: Yes, certainly. Yeah, if you’re interested in exploring TrueLark, you can go to our website. It’s simply www.TrueLark.com. There’s plenty of information on there. If you’re interested in a demo, you can click demo and that’ll route you to a calendar and you can Choose the time at your own convenience. If you’re interested in reaching out to me personally, my email is very straightforward. It’s eric at trulark.com. So feel free to. You know, ask any question, happy to help and, and, uh, see if we can be of some value to you.

Bill Neumann: Yeah, thank you, Arik. And we’ll drop your email address and website, the demo link, all that good stuff. We’ve got a couple of articles from TrueLark here as well on the groupdentistrynow.com website. We’ll link to those in the show notes. Phil, how do folks get in touch with you and learn more about The Smile List?

Phil Toh: Yeah, you know, you could reach me at, like Eric’s simple email, philathesmiles.com. And yeah, happy to kind of share our experiences, both kind of in terms of partnering up with The Smiles, as well as our experiences in implementing various technology. You know, my advice earlier is do it today, do it now, you know, because it really does change the, you know, the economics of how a practice is run. And it’s one of those things where you don’t want to be left behind.

Bill Neumann: Great way to finish things off. Well, thank you both so much. And thank you, everybody, for listening in or watching us today. Until next time, this is the Group Dentistry Now Show.

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