Your Practice Needs a Clearer View of Its Money

Chris Hutchins: Welcome back to The Signal Room. I'm Chris Hutchins. Quick thing before we start: I wrote a book. It's called Beneath the Signal, and it's about the human work behind trusted data and responsible AI in healthcare. Search Beneath the Signal on Amazon now and pick up your copy. Okay, here's our episode. I am very excited for this episode. We're going to talk about another angle that we haven't discussed recently on the podcast. We've got some experts who are going to talk to us a little bit about that this morning. These guys have a passion like I've never seen anybody have when it comes to dealing with finance. I'm so happy that you guys are coming on.

Erez Lankri: Pleasure being here, Chris.

Chris Hutchins: Well, why don't we get started with a little bit about your background? I mean, who are you guys? Tell us about yourselves, but kind of how did you end up getting into the accounting space? And, you know, really cool that you're doing some AI. I mean, that's the topic of the day, and you guys seem to be well on your way with that technology.

Erez Lankri: Yeah, so we're really serial entrepreneurs, Tomer and myself. We've built multiple businesses in the past. And this time around, we really identified AI as the key trend. That was a couple of years ago already, when we knew that it was what was going to disrupt the market. And we wanted to choose a field that we feel both comfortable in and that we can deliver a hundred X better results in. And so we found ourselves finding our way into the medical space. Really, we started out very broad, just building financial platforms in the US. We have clients of all sizes and sorts, in fintech and in real estate. But really we found that the medical clients were the best clients for us, just because we really understood how to build a portfolio of services for them that answers what they need as a medical practice, and we identified the key pain points that they really need us to help them with. And so we found that refocusing the entire company around health and medical practices became our core focus. And that's what we do today. We help medical practices with their financials in the back office.

Chris Hutchins: Well, I think of any industry I've ever been around, healthcare probably needs that kind of help. How do you measure no margin? Is the question I have, probably. Tomer, I understand that you bring an engineering side to this as well. How is it for you in the finance space? I mean, obviously you have that same passion, but engineering is a little bit different from my perspective.

Tomer Lankri: Yeah, definitely. When me and Erez entered this space, it took us a while to really understand that. But coming from the background that we came from, we're both brothers and sons to CPAs, and we grew up building and supporting the technology of our parents' CPA office. So we saw the structure of how everything went before AI, and what AI can bring into the accounting side, bringing finances into the 21st century, really, instead of having really late books and everything on your forecast updated late, and trying to even understand if you're going to make payroll next week. So using technology for that has been major for us, yeah.

Erez Lankri: With the title being real-time financials, really we moved from a place where, I guess, traditional accountants do everything manually and it takes months to actually deliver results, to a point where we deliver platforms on every part of the services that we do in the business. Aside from bringing the best professionals who can actually deliver results and grow the business, we also have the best technology in terms of bookkeeping support, CFO support, cash flow management. And so we bring both worlds into a real-time experience for the medical practice.

Chris Hutchins: Well, that kind of gets to the big question on my mind, and I'm sure this will be very relevant for the listeners as well. What about practice finances, and what about this particular point in time, is what you guys really dialed in on? Because I know I mentioned margin half joking, but in the US in particular, the market is under pressure constantly, being challenged to do things cheaper. Bring down the cost of healthcare. So what I mean is, I heard 100X, and I'm sure a lot of people tuned in because you said that. So talk about what you see as the opportunity and what motivates you guys to jump into the healthcare space right now.

Erez Lankri: 100%. So I guess honing down on the pain points that medical practice owners, or many times their doctors themselves, actually experience was our approach from day one. And I guess the core one that everything revolves around is the fact that doctors are trained to treat patients, not run a business. Med school doesn't really prepare them for running a business and the financials and everything that happens around it. And so many times we find clients coming in that really had poor financial management over years and years, and they come to us to save them from a very messy point. The other pain is that money is really scattered across processors, vendors, payroll and entities. So there is a very messy operation happening on the back end that sucks the doctor's time, or the medical practice owner's time, when they really want to spend their time treating patients, dealing with procedures, bringing innovation maybe into the practice and growing the business. They find themselves stuck in the nitty-gritty of actually managing the financials. So that's the second pain point. I guess the third would be that the books arrive months late, and months is being very kind in many of the businesses that come our way. What we see is that they bring in books that are not reconciled, for years, sometimes. Tomer can expand on that later. The reason being that there is a lot of traffic happening, and it's hard to get the right attention from a CPA who understands the space and has the right type of technology to support the level of financial clarity they're looking for in the business. That's something we see over and over again. And I guess the fourth thing is just a compounding effect of all three of the latter points: because the data is fragmented, doctors are making real-time business calls on a gut feeling instead of building on financial information. They review what they feel, and based on that they make decisions which, of course, are not the best decisions for the business, but they do what they can with what they have. And so what we bring to cover for that is clarity. Clarity and speed, to allow them to manage the business in a way that supports the growth and puts everything in place. I guess it makes sense to review what good looks like in that regard. A good level of financial support and services is where the owner knows the cash obligations any day, so not just at tax time, but they have an ability to look at their business. I'm sure you're familiar with it yourself as a business owner as well.

Chris Hutchins: Can you talk about what you're doing with the AI, and what the first few months are like from a development and implementation standpoint?

Erez Lankri: Tomer?

Tomer Lankri: Yeah, so it's all about actually getting the full picture of the data. Right now, one of the main problems you see with every doctor's office is that the patient management usually isn't connected to the books. So the real quotes, and how much are we planning to invoice to the clients, and what are we really going to be getting into the bank account next week, and how much of the invoices will actually ever be paid. Sometimes the insurance doesn't cover the second part of it. And then you have to feed that whole picture into the agent, or agents, or AI models that will help you get a clear forecast of your business. That way you'd know ahead of time, and not on payroll day, that you're not going to make payroll. So once you have that clear picture, and given that whole data structure, then you can have the correct book structure, you can have the correct accounting structure, you can plan for taxes much better. But if that's all disconnected and fragmented, then you'll never have that, you know.

Chris Hutchins: Yeah, that's been one of the biggest challenges. It doesn't seem like there's any area in the healthcare space where the data is in pristine shape, with the mergers and acquisitions that are going on. I mean, the most basic things get really, really complicated. I think the bookkeeping side of it is probably the thing that I know the least about. But maybe talk a little bit about what it's like from that standpoint when you're going and working with a medical practice. What is this technology doing that handles some of the pain points? They're considered to be pretty messy. I know there are a lot of inputs that human beings still have to make, especially when you come to seasonality and tracking weird events. I remember there was a nightclub fire in the Northeast when I was working at Mass General that put a whole bunch of data in our models that had to be neutralized, because we don't want to plan for disasters to happen like that. But I'm sure there are a lot of new ones. How do you guys deal with that?

Erez Lankri: Amazing. So, one, I would say, just before Tomer jumps in to give all the technical and engineering magic of the AI that we do, right up front, what we made sure of was that the level of service and the level of professionals that work with each and every one of the clients is above and beyond what they're getting in the market. And that, I guess, is key to how we do business in the medical space, because we understand that doctors and medical practice owners are extremely busy. And that way we basically built a model that is extremely proactive in the level of service and our ability to reach them. It's important to outline that, because our professionals are reviewing and are in charge of each and every point of the process. And so it's not like you have some AI bot managing everything unilaterally in the background. I just wanted to make that very, very clear. But Tomer, you can jump in and explain something about some of the structure.

Tomer Lankri: Sure. So it's a mix and match of having the right financial knowledge and having the tools and capacity to actually identify it. For example, we had one client come in and he was very determined to sell his practice this year. And we opened the books and started looking through them, and when you open the books, you start seeing that between the entities you have the incorrect structure. If you had known that in advance, and the CPA managing that case had the capacity to check that, he could have avoided the situation where on the books there is a liability of two million dollars between the entities, making the sale impossible, basically. Because it needs a couple of years of debt to actually, like, compromise over the debt that the owner needs to get back to actually make the sale. So you'd need to have all of the infrastructure that allows the capacity to check the books, and the knowledge around it, to build it in a way that avoids these kinds of things. Yeah, that's the idea.

Chris Hutchins: Like right now, for example, there's a lot of conversation around whether we should be regulating AI at the state level versus the federal level. I mean, my assertion is it doesn't matter what level we're talking about, we've got to be able to figure out how to respond to either one. But there are modeling types of things that you constantly have to be looking at, just to simulate certain things to answer those. What if it's this, or what if it's that? These are, unfortunately, probably more of an issue in some of the places like healthcare than they may be in a lot of other industries.

Erez Lankri: Yes. That's a terrific point. I think that when discussing AI, when actually incorporating it with real businesses, the best way to approach it is keeping a human in the loop, which is what we did at the business. So, making sure there is some feedback from a professional who is in charge of the books. That is the same advice I give to any medical practice that comes our way: they should always make sure that they have someone who is the owner of the results. That's the first thing, I guess. Secondly, I think it's a long way before AI would entirely replace any field that requires regulatory oversight. Taxes is one of them. The reason being that there is a big complexity and differentiation between businesses in regards to all kinds of financial activities happening in the background. Tomer can discuss more on it, but anything regarding collections, anything regarding the different structures of chart of accounts and bookkeeping and matching them to invoices, those are things that AI cannot do perfectly alone yet. And so matching it with the right professional is the way to deliver results.

Chris Hutchins: Think about how an owner is operating. So the AI CFO, for example. Let's assume that we've AI'd the CFO function. AI is being used as a verb. I've heard that lately, so I just wanted to use it for fun. You're dealing with things like forecasting, KPIs, cash flow, and all that kind of stuff. What is it that you guys are doing? Obviously, I don't need the secret sauce, I wouldn't understand it anyway. But what do you guys use the technology for that helps to really dial that in a little bit better? Because I'm assuming one of the things you're able to get to is something that you can really lean on and trust a bit more than you've been able to before. And I'm sure we'll definitely want to get into the trust and accuracy kind of stuff too.

Erez Lankri: Hundred percent. So I guess the main principle that guides us is being able to do much of the groundwork and prepare it, and set it up with rules with the appropriate CPA who is in charge of the case, in a way that allows us to move faster. So, for example, in regards to bookkeeping, we do much of the categorization through rules. There's more to it, but that's a very big oversimplification. Tomer can speak on that in a second. In each one of the platforms that we have to cover each one of the modules, we have advanced AI features that do a lot of the groundwork for the CPA to come through at the end and give the strategy and attention that the account needs, and not the kind of hard labor that goes behind doing the nitty-gritty there. I guess in regards to CFO services, we have one of the most advanced cash flow management systems in the market. It has a lot of features, but on a very basic level it knows how to do actuals versus forecasts and financials. It knows how to show you the hiring plan in correspondence to that. It knows how to do scenario planning, it knows how to manage multiple entities in one, it knows how to do consolidated reporting between entities. All of these are extremely advanced features, and most tech companies that develop only platforms built their entire company around them. That is just one platform that we own today and deliver included, free of charge, as part of our CFO support package, where in other businesses they would need to buy that separately and it would cost more than the CFO sometimes. And over that, we've built a level of AI that allows us to orchestrate over the financials. So we're able to manage the platform data and the financials for each and every one of the clients in a way that sees the entire picture, and not in a very specific way for each and every one of the transactions, if that makes sense.

Chris Hutchins: But I mean, how do you get the Excel wizard comfortable with what you're building? What's that been like for you in the healthcare space?

Erez Lankri: Sure. So we get two situations there. One situation is where the medical practice already has some financial professional in-house, sometimes a bookkeeper, sometimes an actual CFO. When that comes into play, what they usually want is the platform and our ability to support them with real-time reporting. Because creating reporting for, for example, a multi-entity structure is not something that is super simple to do as a solo CFO without the technology. So we provide them the platform to be able to achieve that in the first place, as well as the actual support to be able to deliver on forecasts and reports on a day-to-day, week-to-week basis. So on a very basic level, that's what we do. Tomer, do you want to expand more on that?

Tomer Lankri: Yeah, I think that's super valuable. Having the ability to look at multiple entities in one P&L is virtually impossible for a single CFO, because it needs to reconcile a lot of things. But besides that, getting them to leave Excel was never really a problem for us. It was quite easy, because they're happy that it's managed and all the data is fresh. Imagine anyone who has ever done a forecast, whether it's for a bank loan or to try to raise money for anything: the second you finish doing the forecast and you wake up the next morning, the data is stale. Now you need to re-pull everything and update all the forecasts, because what happened last month wasn't exactly as projected, and you can't do budgets versus actuals. You need to rework all of that. So that's what we give out of the books.

Chris Hutchins: Is there an example of a client that you've worked with where there was a lot of resistance at first, but they would be the first in line to tell you that this works?

Erez Lankri: So I guess the thing I lead with is that what we do is a managed service. We keep track of everything related to the management of the financials, so they don't have to. No medical practice owner wants to deal with financial platforms or financial systems. They want to alleviate that concern. And so the platforms and everything else we do, we do for that benefit. We do it for the doctor or the medical practice owner who just wants to save their time, money and attention to deal with the actual care of patients and not with the financial management. And so we give them the ability to access all the platforms that we have. It's for them. They have the accounts on there. But many times they wouldn't even go on the platforms, because we use them on a day-to-day basis with them to deliver results. What they're more interested in is just relaying whatever data they have internally, and we deliver the results that are actually relevant for their business. So, in terms of resistance, sometimes it comes up as a question, because what they think in their mind is that now they need to learn this whole new platform and how to implement it in their business, and it's going to create all these hurdles. And we moved away from that approach into an approach that says our objective is to deliver value, and the platforms are just a stepping stone or a tool we use towards delivering that value. So we have multiple platforms, but the real value they see is instant, constant communication with a team that is responsive to them, that delivers phenomenally fast in a way that they weren't used to, that is proactive and actually chases them for information so they don't need to chase an accountant, and is able to deliver financial reports and data that were just inaccessible to them in the past. So that's really the end result they see.

Chris Hutchins: When you're talking about AI now getting involved, what are some of the things that you think about and that you've used to help people get comfortable? What's that process look like? Are the models similar to what you would have done prior to AI, or are there some differences that really help people get comfortable and confident sooner?

Tomer Lankri: That's a good question. I think the way I look at AI generally is you need to make it work like you think. So it doesn't matter if you're using it to write your emails or to do your finances. Eventually you need to make it work the same way we have our logic on doing stuff. So if I'm basing a new assumption on my financial records, and I want to check where this transaction came from and actually match it, I can't let the AI just try to work on it and throw it into the cloud and hope it's going to work. It has to have the correct base for it. So once we have the correct base for it, and we actually justify and make sure the AI cannot reply without having the justification, what's called grounding in technical jargon, then you can provide access to that data and access to change that data. And that is what we also show whenever a client comes in with a question, or asks about this or that number. It's always grounded like that, because the systems we've built, and anyone else building any kind of similar system, need to build that according to that kind of grounding. It gives that clarification, which makes it much easier to trust. You're looking at the number, you're looking at the invoice, you can't really argue with that.

Erez Lankri: I guess something important to say on that point, just to expand, is that when you're looking at any AI service or product, the thing to compare it to is the human level of service or delivery. And human error is so prevalent. All the time we're getting clients who are coming from traditional accountants who do very bad work in terms of the accounting and just keeping the books. And so we need to clean up years of unreconciled, uncategorized or poorly categorized books. What we see more often than not is that the platforms and workflows and processes we have allow us to literally deliver a hundred times better results in terms of the actual bottom-line delivery, and bring our clients, who usually come with a very, very poor level of books, let's say it's two out of ten, very quickly to nine or ten out of ten. So I would say that, phenomenally and predominantly, the AI platforms allow you to deliver better results and avoid error. And it's very few and far between where there are errors that go uncaught or unnoticed by the CPA who is in charge of the account.

Chris Hutchins: I love what you're saying there, because I think the challenge I had frequently early in the budget process when we were rolling them out, I actually built the systems and ran the deployments when I was at Mass General Hospital years and years ago. One of the challenges I always got, I plugged a growth percentage in there. And that got challenged year after year after year. And the only way around it, eventually I figured out how to just embed some of the facts and figures in there from prior years. Because they always argue with it. If you're telling them there's going to be growth, they're telling you no. So I imagine having that kind of evidence-based approach as you're building these things makes a big difference there. Because it's a tough area when you're trying to get somebody to admit there's going to be growth. They've done it year over year, but they say, look, you're not letting me add staff, I'm not adding hours, but magically it happens. See, I've got to be able to defend that in the process. I mean, any big wins that come to mind where you guys have identified something like that that people were really a little skittish of?

Erez Lankri: I mean, it happens all the time. Literally, probably every client we did big work with came back astounded and with raving compliments. And Tomer, do you want to share something specific, some specific client that we came through?

Tomer Lankri: Yeah, I think one of the easiest wins was missing tax credits. We had a client come in who had been working with other accountants for years, the same accountant working with him for a very long time. We decided eventually to move to someone who's very specialized in healthcare. And a couple of weeks in, we identified a very big tax credit, north of $50K, that he could claim for this year, and we got it for him. Yeah.

Chris Hutchins: No one was unhappy with that, I'm sure. It's nice to get a good surprise when you deal with finance.

Erez Lankri: For sure. I guess it's important to outline, since Tomer mentioned tax credits, that one of the things we do differently is that we don't only do bookkeeping. It's not only the fact that we bring the AI and the professionals in place, but we also have tax support and CFO support, including the cash flow management. And we also have tax credit studies that we do, which allow us to uncover any R&D activities for R&D tax credits and rebates, tens of thousands of dollars really for every business that comes through. And the model that we built was built in such a way that they don't need to put any money up front to do it. So we assume all the cost of preparing the study. And if and when we get, and we're very good at it, so I'm always assuming we're going to be able to get something. So if and when we are able to get money back, they get to keep the lion's share. They keep, I think, 85 percent, and we basically cover our costs with 15 percent of it. So we built the model in a way that would make it accessible to virtually any medical practice.

Chris Hutchins: No, I love that. This kind of touches on the concern that people get stuck on more than anything when they're looking at any kind of tool they're going to deal with for accounting or budgeting, which is the compliance and the regulatory stuff. Now, you guys have built some things into your products that manage a lot of that. You're basically maintaining a rules engine. As far as I know, and there are probably people who will email me after this, I've not seen a very robust tool that actually has any of this really baked into it, to a point where the starting point is reasonably comfortable for somebody. That's a big difference. The rules are changing constantly. They can come at the eleventh hour, and you've got to scramble for it.

Erez Lankri: Yes, a hundred percent. So I guess the way we built our business is we made sure that each and every one of the services that we provide, we provide with a premium level of service and a very affordable starting point. So we have a dynamic model that is based on the expenses of the business. It means that if you're a big business, we charge you something reasonable for that size. But if you're a smaller practice, we charge you very little. The jumps between the tiers are small, but that allows us to adjust, because even small adjustments can be big for a medical practice just trying to start out. We also keep a very deliberate, small margin on the actual operation, which makes it very easy to adopt a new approach to accounting. Because I truly believe that any medical practice that uses Lucid would never go back to using traditional accounting, because it's such a radical difference in terms of the level of support and care you're getting, as well as the speed and the ability to get the type of reports and plans that we provide. It's just something else altogether. And creating a way for them to get in on each and every one of the modules with an affordable starting point was something we obviously wanted to do, just because we wanted to make it accessible for all medical practices. We look at it as some sort of a mission, I guess, with disrupting accounting and reinventing it to the next level. One more thing that is important to touch on is that on each and every one of the modules that we work on, we do almost 50 percent off, just on the first full year. So it makes everything even more accessible. We were very bullish on making sure that the starting point with getting to us would be as easy as possible, to get access to the level of services that we think every medical practice is entitled to.

Chris Hutchins: But first, what's the first thing you would tell a practice leader they should be getting right before getting AI into their finances?

Erez Lankri: So, what is the thing we do to prepare them for switching to AI? I guess what we try to do is alleviate the concerns that come up, imagining that what we do here is a no-touch platform that they would need to learn. And we make sure that they know, and they're confident that they know, there are people here who are actually accountable for what is happening in their financials and in their books. Because essentially in any business, it's about the people and being able to communicate with the person on the other end to deliver what you need to deliver. We use AI to the benefit of our clients, but it's not becoming a barrier between us and them. So I guess that's the thing we try to communicate more than anything else.

Chris Hutchins: What are some things that you think you're seeing, and where do you think we're headed from a technology standpoint? Is it going to get easier?

Tomer Lankri: I think it's going to get easier for whoever actively decides to adopt it. Because the tools right now are insane. If you use Claude, if you use the new ChatGPT model, they're really, really strong. But it depends on whether you give in to it and you really decide that it's going to be a part of your regular working workflow. And more than anything, I think the models right now are very strong, but the biggest significant step forward for every business is building the correct data architecture, an architecture for the models to actually thrive. So if everything I'm doing is super messy and the data is not there and the way I want the system to operate is not there, then nothing is going to work. The model won't have the actual capacity to make any progress for my business.

Chris Hutchins: I'll just kick it over to you, Erez. What are some of your last thoughts? What's your message to folks who are trying to figure out what they should be doing in the next few months, because they know that they've got to do better with AI and that they need whatever support they can get to get more accuracy and find more margin?

Erez Lankri: 100%. So what we do really is make AI accessible for medical practices for the financial back office. It means the bookkeeping, it means the taxes, it means the CFO services, it means that we do tax work and tax credits. They don't need to figure it out themselves. You know, Tomer and I have engineering degrees in computer science. We come from a family of accountants. That's literally the reason we've built the business for over three years and are delivering now the highest level of AI to the back office of each and every medical practice in the US. If they think that is something that can be interesting for them, they should go ahead to lucid.now and just press Get Started. They can schedule a call with me directly, and I'd be happy to walk them through it. It's very simple and much easier than people are imagining. We keep it simple. We just deliver better results for more affordable prices.

Chris Hutchins: This has been a blast for me. To the listeners, I'm going to make sure you have all the information in the show notes to be able to reach out to these guys. I can't thank you guys enough for coming on.

Erez Lankri: Thank you as well, Chris. Thank you for getting us here.

Tomer Lankri: Thanks, Chris.

Chris Hutchins: Thank you. You all have a great day, and to listeners, I will see you next time on The Signal Room.