Home Care U - How Robots Are Going to Change Your Job—And Why They Need To

Episode Date: July 2, 2023

A topic so important it merits a very nontraditional episode. We're bringing on Romi Gubes, CEO of Sensi.ai, to talk about why she feels so strongly that home care needs the help of artificial intelligence that she founded a company to make it happen.Enjoying the show? Send me a text and let me know!Learn more about Careswitch at: careswitch.comConnect with the host on LinkedIn: Miriam Allred This episode was produced by parkerkane.co

Hey, welcome to Home Care U, a podcast made by the team at Care Switch. Nobody went to school to learn how to run a home care agency, so we're bringing the education to you. Join our live audience by going to careswitch.com slash homecareu or listen on your own time wherever you get your podcasts. Home Care U is hosted by myself, Miriam Allred, and Connor Koons of Care Switch. Enjoy the session. Welcome to Home Care U is hosted by myself, Miriam Allred, and Connor Koons of CareSwitch. Enjoy the session. Welcome to Home Care U.

Thanks to those who are joining, I'm already looking here in the attendee list and seeing some familiar faces and some that are new, so I'm excited for this. Let me run through what today's Home Care U class will look like, and also for those who are new to Home Care U, what Home Care U is, how we do it, and why. So basically, Home Care U is a weekly Zoom class that is also a podcast. So if you join live, you can ask questions in the chat and Q&A. Depending on the question, we answer them either as we go or at the end. So please ask questions during today's fantastic interview that we're going to have. We'll introduce the guest in a minute here. And then we do also

publish it afterward as a podcast called Home Care U. You can find that wherever you get your podcasts. If you are being forwarded this or you are listening to it as the podcast, you can register for the weekly class at homecareu.careswitch.com. And every week we bring on a different expert or we may bring someone on for a couple of weeks to talk about different aspects of how to operate a home care agency or large scale home care company. So today's episode will be a little bit different than usual, and I'm kind of excited. So typically, we will bring on someone who is running an agency directly and kind of get to interview and interrogate them a little bit about some of their best practices in running their business. Today, we're going to zoom out just a little bit

and talk about some kind of higher level opportunities for the home care industry in context of one very interesting company specifically. So if you've been following CareSwitch at all for the last few months, you know that we believe very strongly in the potential of artificial intelligence to shape and change home care in some really exciting ways. We're already seeing some fantastic things happen. We've built software that can help prevent no-call, no-shows, help to reduce the overhead in agencies, make them more efficient, help staff to be able to focus more on people and less on software. But there's so much more that it can do. So today's guest is the CEO of Sensi AI, and they are doing some really cool complementary

things to what CareSwitch has done and have been some of the biggest pioneers in helping the rest of us to catch the vision of what artificial intelligence can do in home care. And so today, what we'll do is if you're familiar at all with the NPR podcast, How I Built This, it's a podcast where they take entrepreneurs and ask them the stories of how they built their companies, what they've learned and why they built them. That's essentially what today's episode is going to be with Romy, the CEO of Sensi AI. So Romy, I'll give you a moment to introduce yourself and your background, and then I'll run through one or two more things, and then we'll go ahead and get rolling here. So thanks for joining us today. Yeah, thank you so much, Connor. Actually,

I'm very excited to be here. For me, it's always exciting, you know, to see guys like you and the rest of the KeraSwitch team that is taking all the knowledge that they gained and experience that they gained in the industry, you know, coming from really understanding the gaps in the industry, and seeing how they can leverage technology and how they can promote innovation within this industry that is really in need. We are in a very interesting time in, you know, in general,

where AI is revolutionizing almost any industry right now. And I don't think that the home care industry will stay behind. So I'm very excited to be here. And I'm very excited about this partnership. So as you said, I'm one of the co-founders of Sensei AI and the CEO. My name is Omi Gubes. I was born and raised in Israel. So English is my second language. And this is where the accent is coming from. I recently moved to the US, though.

I'm now based in Austin, Texas, which I was very surprised to discover that this is even more hot and humid than Tel Aviv. Yeah, very, very, I wasn't expecting that. But I moved here a year ago when the time came and the company grew its operation to a place where it makes more sense for me to be here rather than in Israel. I moved here with my husband and two daughters.

And in my background, I'm a software engineer. So I studied software engineering back in 2012 in Israel. And since then, I was working in Fortune 500 companies, Cisco, Dell EMC, and Vonage, both as a software engineer and as a product manager. It was an amazing boot camp, an amazing school for me to understand how to build products for scale. I worked on products that serves tens of millions of users daily. And I really was exposed to how well-oiled machines work. But I always knew that one day I will establish my own company and we will get to that soon. Prior to that, I've been an officer in the

Israeli Air Force for three years. And while I started my career in large organizations, as I said, I always knew that I will end up establishing my own company. It was a dream of mine. I always dreamt to build something from scratch that will really create an impact and will change an industry for the better. And this is what I'm doing for the past four years now. Very cool. Thanks for that. And thanks again for joining us. Glad to hear that you're liking things in Austin, even though, as you said, I mean, aren't they in like a heat wave there right now? I have friends in Texas who say it's been like 100 degrees. Yeah, you don't want to be without an air condition nearby,

for sure. Yeah, well, glad you're surviving. So yeah, like I said, this episode, we're going to learn about Sensi, but not in a, you know, here's why you all need to buy Sensi way, but more in a, let's learn about the development of Sensi in context of what is happening

with artificial intelligence. Why is it something that we in home care need to pay attention to? And how might it impact your day-to-day life as operators of agencies, both today and in the future? And so those are the things that we're hoping that you'll take away from this as we go. So I'll have questions here and there, but let's just go ahead and dive in. How did you get started? Why did you start it? Why this industry? Let's explore it. So I'll start with just sharing the motivation behind Sensei and why we started this company. So as I said, four years ago, I started Sensei and it was following an unfortunate experience

that I had with my daughter actually at daycare. When coming to think about that, this is the other side of the spectrum of people that are vulnerable and cannot speak for themselves. We discovered actually my husband and I, a really bad case of abuse in the daycare center, the staff towards the young kids. Everything is okay with her now, but you know, this is one of the things that when it happens to you, it really changes your life. It's one thing to hear it in the news, right, in a faraway city, and another thing to have it reaching your own baby. And this is where it got me to think that how we can leverage technology and specifically AI to help all people that cannot speak for themselves and to say what is the quality of care that is provided to them. The problem is relevant to everyone that is under the umbrella term vulnerable, right? It can be babies, young kids, people with disabilities, or of course, older adults.

And one of the things they did in order to understand where we want to start is exploring the different segments. And, you know, you mentioned before the podcast that are sharing entrepreneurial stories and lessons learned from successful companies. And this is what I did in parallel to working in those large organizations. I expanded my knowledge with how to build a successful company, how to do the first steps in order to build something from scratch. And I understood real quickly that I need to understand what is the best segment to focus on. And they started to dive into each and every one of the segments. And really quickly, I fell in love with the senior care and age tech ecosystem that was very new back then in 2019. I understood what all of the audience here

are living on a daily basis, that the need for care will always be on the rise, right? And the supply of caregivers is only getting worse. Older adults more often than not are not receiving the proper amount of care that they need. This is not a surprise to anyone here, I guess, which increases their risk, right, for all kinds of incidents, whether those are falls, declining or cognitive decline,

physical decline from whatever reason. And it makes it harder to manage their care eventually for home care agencies and can potentially harm their well-being. And this is where I understood that they want to build a technological solution that will remove the blind spot from the home and help all the different stakeholders, not only the home care agencies, but all the different stakeholders across the care continuum, whether those are caregivers, care managers, PTs, OTs, clinicians, etc., to get decisions that are actually based on data and not on short assessments or on the ability

and willingness of the older adult to articulate their needs, which we know that often they cannot do that or doesn't want to do that. And this is where we understood that AI is a must-have component within this very ambitious goal to create full transparency into the home in a way that will be very efficient in terms of like time efficient for the professionals who are using the data. We decided to start with focusing on learning the home care industry, understanding that they are the most critical and focal point across the care continuum. They are the ones seeing the seniors from pretty early on in their aging journey and having the most holistic view on their day-to-day understanding their well-being clinical and care needs the best making long story short and just to give you some understanding of of where we are today as a

company so as i said we started building the company four years ago and we we developed what we call the first of its kind virtual care agent that allows agencies, actually for the first time ever, to remove the blind spots from the care environment, from the home, and get decisions that are based on process data, and ultimately reduce the risk and hospitalizations, and allow seniors to age in the comfort of their own homes for as long as possible. We operate today in 37 different states in the US. We raised until today $30 million from top tier investors. And we have 60 employees, both in the US and in Israel, where we have our R&D team.

I can go back to our journey, Connor, if you wish me to do that or... Yeah, so I have a few questions here. First, before we do that, let's just make sure for those who may still be confused, can you explain a little bit more about what exactly CENSI does to help with these problems in the home? And then I have a couple of questions from the story so far. So CENSI is ultimately processing the data, audio data from the care environment and by our well-trained models that was developed by clinicians together with data scientists, are able to process all this data and produce both real-time and ongoing alerts and notifications and trends that will help home care agencies to get better decisions.

So, for example, the system knows to produce any event of care resistance. For example, when an older adult are resistant to any kind of care or having any kind of difficulty in performing tasks, like going up from bed or lying down or taking a shower, any kind of emergency detection, for example. This is another layer that we have in our product that really knows to detect falls, for helps ems activation physical anomaly that requires immediate attention this is another layer and on top of that we have insights that are

more this is an aggregated data that we turn into trend and can detect things as a uti for example in very early on or we even unfortunately discovered cancer early on a few weeks ago where we saw that the system produced ongoing pain management issues that required attention. So we really know to summarize the care needs of the older adult into a dashboard where the home care agency can log into, see all the data and take actions upon this data. What types of data points would need to be gathered or I guess are being gathered that would allow you to realize someone has cancer or UTI or something like that? That goes far beyond what I might have initially envisioned the software being able

to do it takes me back to the to the story but before going there so we're collecting on the audio as of today we tried to create a product that will be in the balance of privacy intrusion and the power of the data we figured out that audio would be the best so we didn't want to go into video because we felt it would be too inclusive for people to have video cameras in their you know living area in their bathroom in their bedroom at the end of the day it's not an office it's a home environment it's very private and intimate so we went into the audio field and and i will just share a little bit about like specifically about the cancer story let's say so the cancer story, the system detected ongoing pain complaints of the older adults. So he complained actually to himself when having no one in the home on specific back pains.

And he didn't share it with anyone. And it was then released to the dashboard. The agency was able to hear it for the first time and go speak to the to the older adult. And this is where he it was the first time when he openly talked about his recurring back pains. And they just recommended for him to go to see a doctor. And just by doing that, he was able to discover that pretty early on. So sometimes it's just a matter of knowing what's going on and just opening this line of communication. That's really on. So sometimes it's just a matter of knowing what's going on and just opening this line of communication. That's really interesting. So in this specific story,

I mean, let me make sure that I'm understanding. He, for whatever reason, was kind of reluctant, or at least wasn't really voicing these things he was feeling about his back pain. But he was, I mean, it sounds like he was okay with voicing it, understanding that Sensi devices were listening. Sounds like he was ultimately grateful kind of for the intervention there. So he was okay with what might be seen as like a privacy challenge there then. Yes. So the privacy is a balance, right? Where like today, all of us are using smartphones, although we know that they're listening to us for ed purposes, right?

But we're using it because it's comfortable. It's making our life easier. And at the end of the day, this is something we want to do. So also in the Sensi case, people are just thinking to themselves whether we want to keep our older adults safe at home and what it means in regards to their privacy. And we do get people that at the end of the day decide not to take the SANSI service

because of privacy reasons. And I can say that this is somewhere between five to seven percent for the people that are being offered with SANSI are declining the service out of privacy. That makes sense. And that's a pretty low percentage, which I think speaks to, you know, the fact that we all understand that there are balances to be locked there and that there are benefits to allowing certain types of data to be used in certain ways. So that makes sense. Kind of going back to the beginning here. So I think it's pretty interesting and inspiring the way that you started to recognize the need for this, even though it was very unfortunate circumstances that led you to that. So prior to having these experiences of recognizing abuse that was happening in your

child's daycare, you really weren't thinking about starting a company in the care space, correct? I mean, this was kind of this new concept for you. Right. So I didn't know what I would do. I just knew that I want to establish a company that will be meaningful for society. And one of the things I needed to do from the start is actually going very deep or understanding really deeply the for hundreds of assessments in the field with agencies to see how it looks like and to really understand their challenges. That makes sense. And I thought it was interesting what you said about kind of choosing the home care industry as a place to land because of its kind of central position in the care continuum and the ways that it affects seniors lives in so many directions, I guess. Is there any more that you want to say to kind of speak to that? I think that's very resonant with people listening to this. We started to build a product and we understood how powerful audio is and how many different insights it can generate. And we wanted to provide as many insights as possible. So we looked for, as I said, for the most critical and focal point in the life of the,

or in the journey of the older adult that will be able to leverage this data and to really make a change in their life. Where clinicians have a specific point of view, PTs and OTs have specific point of views about the older adults. We believe that home care agencies have the most comprehensive approach, and this is why they can leverage most of the data. Love that. And I think that ties in with something that's being widely realized, not just in the home care industry, but across the care continuum, which is the role of home care as a form of healthcare, you know, both preventatively and for its ability to make changes in someone's just day-to-day quality of life. So I think that was a very wise observation. So yeah, let's kind of go on the story. So you kind of chose what you wanted to do. You recognize what could be done to help it. You did hundreds of, well, went along for hundreds of assessments to understand the best way to make an impact here. solution. We didn't always know that audio would be the perfect solution. And we explored

multiple directions. And one of the things that really enlightened us is that we went for one of the nursing homes, the largest nursing homes in Israel. And we set to speak with their CEO. And we asked her what is keeping her up at night and she said that one of the things that she's trying to to be better at constantly is understanding what's going on in the rooms where no one is there just because just in order to prevent things from happening and not to be reactive but rather proactive with the care that they provide and one of the things she did was to to put cameras across like in in the chain, they had cameras covering all the facilities. And she put a team that is working 24-7 watching those cameras and then, you know, passing the data to the care teams in order to become proactive. And she said, while I invested so much money in that, and it's working, and it is providing us with some level of knowledge, I know that there are things I still don't know,

things like softer things, as I said, as care resistance, as complaints of the older adults, as any kinds of difficulties that are not visualized, they cannot be seen. And I know that if I have an audio piece over there, it will make me much smarter. And this is where we decided to, we started with just, you know,

taking small microphones and small processing units, put them, glue them together, literally myself and my co-founder, glue them together and put them into the socket in her nursing homes. founder, glue them together and put them into the socket in the in in her nursing homes. And we just programmed that in a way that they streamed the audio to the cloud. And we were able to go back to the office, sit down and listen to what's going on

in in the in the rooms, just to understand whether the audio is powerful enough, as she said, to really understand what's going on. And it was a very, very interesting experience. We sat down and we listened to everything for two weeks. And what we did at the beginning is we started to put together an Excel sheet with all the specific audio snippets that we found interesting. We didn't know anything back then on how she operates, how the nursing home operates, just common sense

of you know things that we thought that might be interesting uh for her to look into and this was the first product of sense in excel sheet that myself and my co-founders sat down and put together every two weeks we sent it to her and we got her feedback and it was like uh we did a few iterations like that somewhere around half a year to really understand if there is patterns and parameters that with enough data can train AI models to figure it out automatically. And this is how we also created our first data set of sensing. This is also maybe something that's worth mentioning. When you're building an AI solution,

the most critical thing is the data that you train your models on. There is a very common phrase in the data science world, garbage in, garbage out. If you're training your AI models with data that is not relevant, you won't get any results at the end of the day that will be relevant to you. We'll get a very low accuracy rate. And we understand that we need to have diverse but yet specific set of data from real care environments that will reflect the specific acoustic parameters that care environments have. So, for example, when you and I speak right now, an anomaly will be a shout, right? If one of us will start to shout, it will be perceived as an anomaly an anomaly where in older adults homes when when the caregiver is is getting into the home and maybe speak uh in a higher volume because the older adults have any kinds of hearing disabilities it's not necessarily an anomaly that's worth mentioning um so we

understood that we need to collect as much data as the fastest as possible in order to create some kind of model and we understood that there is no such data to purchase from any place. It will be first-of-its-kind data set that we will need to collect on our own. So we started to collect this data. We started to train the models with this data. And it actually took us a few years until we were able to really release a product that will be automatic enough to be served at scale. Today we have trained our models on over 10 million care interactions already and we're constantly improving it and retraining it but it was a very hard task so so once once we we finished with

like the poc with it with this nursing home we went ahead and started to explore this is where we started to explore the home care industry in the u.s so we understood that we need to really dive into their operations and to their day-to-day in order to build a product that will be a fit for their operations it's very different from nursing homes facilities from any kind and all kinds of long-term providers and this is where we started to to create our dashboard and until today you know we're constantly learning and evolving and improving but at the end of the day I wanted to touch upon like you asked about how ai can can impact the industry in general so first of all i think that in-home monitoring um snc does and you

know there are also all kinds of solutions of in-home monitoring this is one aspect that can really help home care agencies not only to provide better care, but also to provide a comprehensive care, a hybrid solution between the caregivers that are coming into the home that are not always easy to find, together with some level of safety net that AI and technology can provide. This is one aspect. But then again, AI can change the entire operation of home care agency. And I think that this is, Connor, what you guys are dealing with on a daily basis and how you can leverage

the AI to really help them do scheduling better, to automate some of their tasks, to become automatic and not rely on manpower or rely on manpower for different things yeah lots to talk about in there and i totally agree that the first thing you said that was really interesting to me in there was about data and the value of data within how we use artificial intelligence i think this is maybe something that's not understood as much because especially the last, you know, six months or whatever, most of us, we think artificial intelligence, we think chat GPT, you know, and being able to like type in a simple prompt and then it just, you know, tells me an answer. And that is a big part of it. I mean, like we're using that in the CareSearch platform. But it's, it goes much beyond that, where part of the value of artificial intelligence,

a key part of it, is its fact to synthesize so many more data points than a human brain could and make connections that we couldn't. And so it just enhances our decision-making abilities with its ability to gather and find connections between thousands or millions or billions of data points. To kind of your point about all the different ways that it can change home care and change the day-to-day life of an agency operator, on the CareSwitch side of it, we've demonstrated what can happen when scheduling is assisted by artificial intelligence and when client and caregiver matching is assisted by the ability to gather data points that artificial intelligence has. We're seeing some super, super cool things there.

And so it's very interesting to me hearing what Sensei is doing, how you're gathering the data to be able to start identifying to pull takeaways out of the giant database of data that you have. So do you have any more stories or experiences or examples of things agencies have learned or known to do to help clients based off of insights from Sensi? So we have tones, really tones, which is very, very, you know, I always say that I feel privileged to always get those stories and to know that I'm a part of a company that, you know, is so impactful. One of the stories that I think the audience will find interesting is and i guess most of the most of the people here that are running or a part of the home care

agency will relate to this story um we had a client one of the first clients of sensei actually that started the service of a home care agency that had a caregiver walking in for three hours in the morning. And she fell three times in one in the first month of the service. And it was very frustrating to everyone, you know, for the family, for the older adults, for the older adults, for sure, but for the home care agency, and no one really understood why she's falling. And then they decided to put Sensi in the home. home although you know this this lady needed 24 7 care but of course couldn't afford that so she like they gave her only three hours a day um they put sense in the home in order to really try and understand what's going on there and one of the things the system discovered is while while they did the assessment they came to to assess the

the lady and to to build the right care plan her. She mentioned that she's waking up every morning at 7 a.m. And they had nothing to do rather than, you know, believe her and build the care plan according to what she's saying. But then when they put Sensi, they realized that actually she's waking up every day at 5 a.m. And when she's waking up, she's in bed. She cannot get up from bed. She's waiting for the caregiver to come. And she needs to use the bathroom. And she's starting bed, she cannot get up from bed, she's waiting for the caregiver to come, and she needs to use the bathroom, and she's starting to scream, like she's starting to ask for help, and she understands that there is no one there, she's starting to scream,

and then she goes to bedroom in bed, and she's trying to get up, because she's not comfortable anymore, she's trying to get up, and she falls. And this was a trend that happened a few times. And they assumed that this is why the lady fell three times. And the caregiver, whenever she walked in, she saw the lady on the floor. Just by realizing that, the agency was able to go back to the family, share the data with the family, and say that they need to do a change in care plan and to have two more hours in the morning and a few more hours in the evening to put her to bed in order to stop the falls from happening.

At the end of the day, doing a change in care guessing game is really causing you know first of all the the family to to to be more comfortable with the with the advice they're getting from the agency then the agency to know that you know they're doing the right thing and at the end of the day it reduces the the hospitalization and reduces the risk and help the lady and their family to pay less for caring to the senior. Very cool. I think that's exactly the kind of story that helps to illustrate why this is not just some train we're telling people to jump on board, but why it's one that they need to jump on board because it has the capacity to help businesses

and to influence and even change and save lives. I don't say that just, you know, Sensi specifically, but artificial intelligence as a whole, there's so much that can be done here. There's so much that it can change. One thing that we've kind of started to preach at CareSwitch is the shift that's happening. Every time the underlying tools that are being used to run a home care agency know, in around like the late 2000s, like 2010 is when everyone

was starting to switch to software and that didn't change the care itself in some ways, but it instantly changed agency's ability to run the businesses more effectively, to coordinate things, to communicate, everything like that. And so it raised the bar across the board for the standard of care overnight as agencies started to adopt software that was designed to run the care process. And what we are seeing and what we're kind of preaching as a company is that that is happening again with you know we're leaving just like the purely software era and we're entering like the artificial intelligence assisted era where we not only have software that's helping to run agencies

but we have the assistance of artificial intelligence to gather data, to make better decisions and make connections that we didn't have before. And so we can run the care processes more intelligently than ever before. That's very exciting to us. And that's very exciting to people that are starting to catch the vision of that. So I guess my question for you, having said all that, I know that from the CareSwitch perspective, we still see plenty of the whole spectrum of concerns about bringing artificial intelligence into the care process in any way for various reasons, whether it's privacy or jobs or concerns about new technology that we may not fully understand yet.

What is your reply to agencies that are concerned about how artificial intelligence might change things for the worse, I guess? I think it's a case-by-case thing. I don't think that AI is suitable for every use case, for everything we want to do. We really need the people that are operating the machine to really be mindful to what we're doing with that and where it's helping us to become better and where it's a power of ours and where it gets us to be less maybe personalized, less, you know, less looking into the nuances. And I think that, you know, one of the things I would constantly think of as a company is the phase of the assessment that is so crucial for the success of the care plan, right? People like the nurse or the care manager is walking into the home and trying to build a care plan based on maybe an hour-long assessment, but all that they

are seeing in this specific home. And at the end of the day, as you said, a model, a trained model that did millions of assessments will probably know to analyze the situation, maybe not better, but at least the same as a human that is coming into the home. And I think that the combination of the two, the person that is coming with, you know, seeing the older adult, feeling the older adult, together with being based on the data from millions of assessments of an AI model

that is being trained, well-trained, can provide this, you know, better result at the end of the day and really empower home care agencies and care staff. So we really need to think, you know, where there is a room for improvement and we can leverage the technology and where it can be, as you said, harmful. That makes sense. Before I get to my next question, do you have any more examples of ways that you and your team have recognized challenges

or risks with AI and then the steps you've taken to avoid or mitigate those risks? Not yet, but we're very mindful to that. We know that it's around the corner, not yet. Yeah, and I guess the question for you, maybe it's more applicable to ask about the privacy concerns, which from what I've seen just by scanning your website, you've already taken what I would call extensive steps to make sure that that's thought about and safe. Is that correct? Yeah. So we are implementing all the HIPAA measures as of today.

And one of the things we're doing, and it's part of the HIPAA guidelines, is we are disconnecting it happens, they cannot combine between what is being said and the audio itself and to who it is connected to. So it's totally anonymized in that sense. This is just one of the measures. We're taking many more, but this is part of being HIPAA compliant. And then also, you know, we're constantly saying that we are a company that is devoted to provide better care. This is our mission. We want to help companies to provide better care and older adults to age better at home for as long as possible. We're not doing anything with the data that is not for this specific mission. And it's not true, you know, to other companies that are using the data for

advertising purposes and all kinds of things. We will never, you know, share the data with any external party or whatever. So this is another thing that is very important to know that, you know, Sensi's Senior Care is an HDEC company that is focusing only on that. That makes sense. Yeah, that makes sense. Thanks for sharing that. I think like something I want to share for listeners on our side of it, kind of seeing our perspective, the perceived risks of embracing what can be done with artificial intelligence and home care, but then why we're not worried about it is, you know, I think one thing that we hear a lot is like, is AI going to take jobs, you know, things like that. And I can't speak to that at like the broad, like macro level, like, is it

going to take my job? I don't think so, but maybe who knows. But when it comes to like the context I'm familiar with, which is what something like CareSwitch can do in a home care agency, like the answer is kind of two things, which is first of all, you know, as you're using the same software that powers ChatGPT to get stuff done in your home care management system, which is how we do it, does that make efficiencies that especially in a large scale organization, would give you the chance to reduce overhead and potentially get more done with the same or fewer employees? Yes, it does. That being said, however, trying to reduce the number of employees in a home care agency or company at the admin level isn't the goal or really how we see

it being used. What we preach is that what it does is enhance the abilities of what I'll call the human employees in the agency to focus more on the humans, on the clients and the caregivers themselves, because it does more of the everyday menial grunt work within the software that distracts from the true work, which is focusing on humans. And you go to our site and it says like, care is human for everything else. There's CareSwitch. And the point there, not just specific to CareSwitch is that done properly, artificial intelligence can help us make home care more human to human and do that more effectively. I totally agree on that.

And I think that, as you said, like the, the making it, like thinking about the revolution that we went through, the industry went through in 2010 and until 2015, where they, they have been digitalized in a way, right? We saw all the world skies, then ClearCare penetrating more and more deeply and agencies are starting to integrate it. It just changed the daily routine of the care managers from focusing on really scheduling and putting all the excels together and doing all kinds of manual work into doing other things as operating the machine right operating the software and focusing on the human at the end so it's not i i don't

believe that software or ai will take our jobs but rather change our jobs to where we will do less of the operational side and focus more on the strategic side, decision making, and things that are a bit more maybe complicated for an AI to do. I love that. I truly believe that with AI here to help in home care, it'll make home care more human to human and better quality of care. We have a couple interesting questions here in the chat. Before I get to those really fast, I have one final question, which is having spoken about the risks or like the perceived risks of AI and home care and the different tools that have been invented like CareSwitch and Sensi to help with that.

I think there's a lot of agencies that kind of take this like sit back and wait approach of like, I'm going to see how it goes for other people and then kind of decide whether I should use it in my agency. And there's this kind of delayed hesitance to embrace AI, what would you say to agencies that potentially see the value of artificial intelligence and the tools that have been made to use it for home care, but are hesitant to get started with it? So I think that first of all, change is not made in one night, right? Change is a process. And we always see that if you're thinking about startup companies and companies that are really changing industries, you always see this trend of early adopters, companies that are more open to innovation

and seek for innovation. And then you see the mass majority and the latecomers. And I think that we're in a stage in terms of AI where we see mostly still early adopters joining. We're not yet in the mass market and the late comers. But my advice will be one thing we did as a company in order to help agencies to feel more comfortable jumping on this train

is we built a very comprehensive customer group that will do the handling for agencies to make sure that they're able to integrate it into their daily routine. So our customer group as of today is built out of AEs, people that are coming on site to the home care agency to really help them do the first installations in the home, because we know that, you know, for people that are not working with hardware and technology every day can be very intimidating. So they're coming on site.

They're going with them to do the first installations, to explain about Sensi, to show them the dashboard. There is something in this personal touch that can really help them be more open to the idea and ask all the questions and really spend a few days with the care managers and the staff. Then we have our customer success managers that are facilitating the entire process and making sure that their questions are being answered all the time in a very high touch model, by the way. So we're not a company that will ship

the devices your way and we'll sit back and see what happened. We're working in a very high touch model with our clients. Just because what you said, just because we want to make sure that they're successful with the product and not just purchasing it and then doing nothing with that. And then we have also our clinical advisors, people that are working constantly with the agency to analyze the data

and to help them build the right playbook for their agency on how to use the data. So going over it with them, sharing what other agencies are doing, what is working, what is not working, and helping them to integrate it into their daily routine. And then we have our support team for everything that is more tech problems. And we did that. It's not that common in startup companies to have such a comprehensive

customer group that is touching all the different aspects. We did that just because we understood that this revolution is big for the industry. It's not something that is so simple. We felt like it's needed at this point in time. This is something we explained. During the sales process, the people that are working with the agency are explaining to them that they won't be alone in this journey of adoption and onboarding. We will guide them, we will walk them through. And then at the end of the day, you know, it's not something you cannot, like, if it's something that doesn't work for your agency, it's not something you cannot go back from. It's not, you know, so just try it out, because it's out there, like, it's happening, It's changing the industry. And we're getting clients

that refuse to ask from at the beginning or declined our offer and then are coming back because they hear that their neighbor across the street is doing that and they're starting to win all the deals. It's there. It is helping to provide better care. And I just encourage you to try it out. Love that. That ties in with our questions here. So you've kind of already addressed this one, but you may have more to add. So someone says, how have seniors responded to having this tech in the home? What kind of messaging do you use? I think presumably to explain it to the seniors directly. Yeah. So as I said, first of all, we have our AEs coming on site and helping the agencies build their specific, their flow and how they feel comfortable

to go and introduce the system to their clients. And what we say is pretty similar to what I said at the beginning. So we're saying that this is another layer of safety for the older adults to make sure that also while he stay by himself or herself, they are safe and we find out what's going on. And if they need any immediate help, we will be there to provide them with that. And then we will

be able to manage the care in a better way that is based on data. So this is more or less what we're saying, but every agency has their own tweak and their own way of saying things. So we're working with them to find what is working for them specifically. Love that. That makes sense. That's a good segue into the next question here from Jill, which is, does it capture all sounds and conversations in the senior's home around the clock? It is streaming the audio around the clock but then we have a few stages in our data flow where in each stage other kind of data is being eliminated and at the end of the day we're making sure that the in the data flow where only things that are

care related are going on onto the dashboard of the agency we have our filter to start with where we're filtering all the back noise, the noises from any kind or anything that is not interesting. Then we have our environmental classifier and speech to text mechanism while we're reducing all kinds of, you know, TV, dog barking in the living room or whatever, until we reach a point where we're just analyzing the older adults specifically, saying specific things in specific tonality that the system believes that it's worth knowing for the agency.

All the other data is being deleted. I guess my last question for you to kind of put you on the spot a little bit here. So when we talk about what the home care industry will look like in, let's say, 10 years, are there problems that exist today that just might not even exist or not exist at the same level because of AI-driven technology, paint the picture for me. Like what does home care look like in 10 years? Thanks to artificial intelligence. I'll start and say that I'm humble enough to say that I don't know.

I have no idea how it will look like. I can just assume that things as, as I said, like assessments and care decisions will be based on a lot of data and the decisions that we will get will be much more educated. And I guess that most, if not all, of the operational aspect of the agency will be mainly done by software, by AI and software. And then we will get much better visibility into the home.

My assumption is that caregivers won't go anywhere. The personal touch will still remain a must-have in the home in regards to companionship and doing all kinds of ADLs together. So caregivers are, in my opinion, here to stay. I don't see robots or any kind of software replacing the personal touch. And the same, by the way, for care managers. They also provide personal touch at the end of the day to clients and their families. I totally agree. More human to human, less of the menial work that gets in between the people. So for someone who might be interested in learning more about Sensi, what should they do? Where should they go?

So just type Sensi AI on our website. You can book a demo over there and get the entire walkthrough on our product from our team. Okay. Sounds good. That is easy enough. And I mean, same here with CareSwitch as always. Well, thanks again for joining. Really interesting to talk to you. Are there any final thoughts that you want to leave everyone with? No, I think we touched on almost every aspect. I want to thank you for having us. And I want to wish you all the luck in doing what you're doing. It's a very ambitious mission.

Thank you. And same to you. I'm excited to see what our companies can do over the next few years. Thanks to everyone who joined today and everyone who's listening on the podcast. Just as a few reminders, it is both a weekly class and a podcast. If you want to register for the weekly class and ask your questions and join us live, you can go to homecareu.careswitch.com and sign up. It's free. Or you can listen to the podcast called Home Care You wherever you get your podcasts. It's all free. We try to the podcast called Home Care U wherever you get your podcasts. It's all free. We try to make it as useful as possible.

All that we ask is that you share it with whoever else might benefit from it. We can't get it out to everyone. I think there's value to so many more agencies than have discovered it yet. So please share it with whoever you can. Send it to your colleagues, fellow franchisees, your teams, put it in Facebook groups, whatever will help more people to get access to this education.

So thanks again and have a great rest of your day. That's a wrap. This podcast was made by the team at CareSwitch, the first AI-powered management software for home care agencies. If you want to automate away the menial of your day-to-day with AI so that you and your team can focus on giving great care, check us out at careswitch.com.