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Is there a single right way to run a home care agency? We sure don’t think so. That’s why we’re interviewing home care leaders across the industry and asking them tough questions about the strategies, operations, and decisions behind their success. Join host Miriam Allred, veteran home care podcaster known for Home Care U and Vision: The Home Care Leaders’ Podcast, as she puts high-growth home care agencies under the microscope to see what works, what doesn’t, and why. Get ready to listen, learn, and build the winning formula for your own success. In the Home Care Strategy Lab, you are the scientist.
Miriam Allred (00:02)
Welcome to the Home Care Strategy Lab. I am your host, Miriam Allred, and we are live at the Home Care Innovation Forum in Palm Springs, California. And I am here with my sponsor, Phoebe. We've got Corey Grissom, the head of sales at Phoebe. Corey, welcome to the show.
Corey Grissom (00:23)
Awesome. Thanks for having me this morning.
Miriam Allred (00:25)
I wanna just start. This is both of our first time at the conference. There's been a lot of talk of AI and we're gonna kinda have that conversation here live in real time. What have you been hearing? What's kind of sparked your own interest and how these leaders are thinking about AI?
Corey Grissom (00:38)
So it it it's super cool compared to some of the other shows that I've been to here in recent weeks. ⁓ of course it's kind of a different ⁓ a different type of attendee. We've got a lot of leaders at a lot of different innovative organizations here this week. I think the difference between what I've heard at previous shows where a lot of people are still in their exploration phase of AI, the leaders here at this show, they're out there applying AI in their businesses, in their everyday life.
And they're really sharing kind of some of those best in class kind of traits, whether they're out building it or buying it right now. You're hearing about all the different experiences, seeing lots of note-taking being taken very fast and attentive in a lot of the different sessions. So really cool to see where people are not just out there buying and exploring AI, but it's actually doing a a real life ⁓ outcome to their business.
Miriam Allred (01:30)
And like you said, we're we're hearing a lot of these large companies building it or buying it. I actually thought I would hear more building, but I'm surprised that more people are buying. Does that surprise you at this scale or no? ⁓
Corey Grissom (01:44)
Yes and no. ⁓ so in a in a previous life I worked in the travel nursing space where the builder buy conversation was always kind of forefront, similar to home care. There was lots of private equity movement and stuff like that. So to desire it lot of times to buy ⁓ was was something that a lot of people would wanna do. But I think with as fast as technology evolves and changes right now to
actually go out there and build it versus partnering with someone that's best in class to do it is a little bit more of a dangerous move right now. So I think a lot of people are moving more towards partnering with the labs and you know, unlocking the synergies of working with an anthropic or an open AI versus ⁓ going out there and just building on the context of their own data.
Miriam Allred (02:28)
You said
to me a minute ago there's already AI burnout. Have you felt that at this conference, that there's already this kind of like AI fatigue?
Corey Grissom (02:35)
⁓
I think so. I think if you were to ask any of the agency owners or any of the vendors, I think probably since Chat came out back in late twenty twenty two, twenty twenty three, we've all been kind of under every show, it's all about AI, it's all about technology and automation and things. where I think that real kind of like cross of the chasm has happened now is just the the concept of people actually using AI and seeing actual ROI from it now where
You know, very early on it was very much like theoretical where you're actually seeing it kind of in place. So yes, I think there's AI burnout and AI fatigue, but I also think we're all just at the very, very beginning of seeing practical application of AI. So it's probably just the beginning of the
Miriam Allred (03:21)
What are some of the practical applications that you heard have heard here? We've we've seen some people get up on stage and in just conversations we're hearing some of those those unique applications. What are a couple that you've heard?
Corey Grissom (03:33)
I think of I've I've heard a couple of really cool ones here. I think of course we sat through with the team yesterday that actually built their own LLM on top of their own clinical data. So they really focused on the clinical data and solving a different type of problem than what you typically see a lot of agencies trying to solve where
A lot of people are really focused on the back office automation. ⁓ I think there's been some really cool technologies here that are focusing on intake of new clients and how do you make that more of a f a frictionless process. At Phoebe, we're really focused on the scheduling part and really unlocking the scheduler to allow them to focus on being more human in a human driven business versus
Just kind of being a cog at the wheel, always doing kind of the laborious task of the calls and the emails. So ⁓ I think there's a lot of really interesting use cases that we heard here on stage from a lot of different groups. and I think a lot of them are really kind of on the money where AI is really starting to change what the org chart at a lot of different organizations look like, whether you're a small agency and SMB with three to five employees or you're a large agency with hundreds of native employees.
everyone's applying technology a little bit different right now within that use case. So super exciting to see them all kind of solve their different headaches with it.
Miriam Allred (04:56)
One of the
interesting questions that I heard, I think you were in that session as well. Someone asked about are we creating AI generalists or AI specialists as we as we reconfigure the org chart, the role and responsibilities of the scheduler of everyone in the office is kind of changing. And as we remove some of the manual tasks, the manual burden, that is like kind of fundamentally changing these roles. And so because they have more time.
Are they becoming more generalist in that they're doing more a variety of tasks because we're taking away the manual burden? So what's your take on that? Are we creating more generalist office roles?
Corey Grissom (05:37)
So I think it goes back to the the humans being more human role. I think right now I don't think that anyone out there has fully unlocked a a scheduler where they do not schedule anymore. but where we're seeing where we're seeing people get unlocked is the ability to, you know, not do the dead end phone calls, not do the dead end text messages. They're less worried about
you know, a ball dropping because they didn't follow up with a client to close the loop on a change schedule. They're more focused on, you know, talking to more clients around intake, talking to new caregivers, getting them acclimated to a new case and things like that versus the back and forth of nailing a call out and things like that. So I think it allows them to be more more broad, but to actually I wouldn't
I would say to be more experienced and more skilled in what it is that they're doing versus it just being a quick transactional touch. It can actually be more of value-based care where they're actually spending a lot more time focused on the caregiver experience or the client experience versus just a fire drill that a lot of agencies deal with from the moment a call out comes into the morning to, you know, the time that they're now looking to catch up at the end of the day because
You know, they spent a lot of their time just backfilling for what they thought they already had.
Miriam Allred (07:00)
Yeah. So let's talk about a couple of Phoebe use cases. I wanna talk about some of the most common scenarios that we see in a home care office w regarding scheduling. One though that you told me yesterday that I thought was interesting, an agency and see going from zero to one scheduler. Totally. And the ability this is a this is an operator that has experience in home care. Yep. And so she knows she knows the ropes, but she also and she's also tech forward and like innovative and so she, this operator specifically, is
started her business and thought like can I bring an AI before a scheduler? And she's already having success with that, so can you explain a little bit more about how that's possible?
Corey Grissom (07:39)
Totally, totally. So it it's kinda it kinda comes down to like
You know, kind of the business model within a lot of franchises or small businesses. You're an owner operator at at the beginning, you're scheduling, you're doing client intake, you're doing, you're doing HR, you're doing payroll, you're doing it all, right? ⁓ and it's kind of understanding when you take off those hats, when you put on those hats. It's kind of the juggling trick to kind of get over, let's call it that 500 hours a week mark. ⁓ historically, when we first kicked off Phoebe, we were really focused on agency owners that were going from one to two.
You know, they were around that 1,500 hours mark and they were really trying to make the decision on what to scale look like past this. ⁓ and that's really where we thought the sweet spot was ⁓ early on as we were going to market. What we found here recently within the last three months, and it's a lot with how the technology's evolved and just how we're getting content directly from caregivers is we are able to hit that sweet, that, that kind of before the sweet spot, and it really is that that zero to one moment right now.
where we're working with owner and operators that are wearing every bit, every every one of the hats, but now Phoebe is going out and and going out and creating a suggested care list of caregivers matching against the client's needs, their specialties.
⁓ what the preferences are of the caregivers themselves, aligns that, does mass outreach via text, does mass outreach via voice, and now the owner and the operator only has to come in and manage the Phoebe platform when hu what human is ⁓ required, whether that be to approve a message, approve a caregiver back into the schedule. ⁓ but it'll really allow the owner to essentially be in thirty five to a hundred places at once where
In the old school game of smiling and dialing, you can only call one person at times. and it really helps remove the operational bottlenecks of just running a call out. Like we talk to most agency owners, they'll tell tell us that a call out will take them 45 minutes to an hour to solve just on that direct level. But then there's the fallout of the things that they didn't do during that time. we're seeing right now that Phoebe can text to
run the full length of an average call out in about 12 minutes and find an eligible caregiver to do that role. So we're literally just handing time right back to those small owner and operators so they can focus on value-based service, quality of quick quality of care, and then also focus on grow growth and new business development versus being stuck on the phone or replying back to a text, telling somebody where the directions are or where the gate code is.
Phoebe can handle a lot of those different things on their behalf and allow them to operate on their business.
Miriam Allred (10:29)
And call outs is like the urgent need that everyone's trying to solve, but also
Just think of open shifts in general. I I've talked to even some of your customers and it's common in in home care for there to be for schedulers to be thinking of like kind of a a seven to fourteen day schedule, you know, filling shifts and getting the calendar in a solid place for kind of seven to fourteen days. But now with the ability to fill shifts being so seamless and easy, a lot of these schedulers are already looking, you know, thirty days out. And what home care company doesn't want to have a thirty day schedule that is accurate.
and steady and consistent, that's good for the clients and the caregivers and the office staff. And so now this ability to get out of reactive mode and just be focused on like seven to fourteen days, it's like, let's build schedules out, you know, a month in advance. And of course there will be call-outs, of course there will be flux, but having that kind of base of 30 days is huge.
Corey Grissom (11:21)
Yeah, and being able to manage that exception is just going back to the example of the human a lot being able to be more human. They're now being proactive where, hey, the Phoebe platform has already gone out and found a caregiver for the next six weeks for this particular case. They're no longer worrying about that unless there's an issue. ⁓ and then at that point, Phoebe will go in and backfill any of those shifts as they come in.
monitor their c miss clock ins and clock outs as well so they're not sitting on their Axis care or well sky environment waiting for so a c waiting for a caregiver's name to turn red to find out that they may potentially have, you know, a gap in a gap in coverage or a potential call out. So it's really crazy to give back the schedulers and give back the care coordinators even that bit of sanity where they don't feel like they're just constantly monitoring for a bat for a bat signal when something goes wrong.
Okay.
Miriam Allred (12:17)
So we kind of talked about like zero schedulers to one scheduler. You mentioned there's all these transition points, one scheduler to two schedulers. That's where we see a lot of agencies struggle. Like they're at that fifteen hundred to two thousand hours and they've got one scheduler and they they want to bring in another one, but then like how do they bring in another when anticipating hours? What does that mean for the existing scheduler? Like the one to two is really tricky. ⁓ talk about I guess a little bit more of what you've seen with agencies going from one scheduler to two.
or going from one scheduler with Phoebe then to two, like that threshold, what are you seeing?
Corey Grissom (12:50)
So it's it's super interesting because of course in this case there's also also an incumbent scheduler that's already there, that's already, you know
fundamental to the way that they're running their business right now. ⁓ We found at Phoebe that a big part of it is the change order as well. It's not just the technology. Being able to mass text, max call and get all that data back seamlessly is great. But you really need buy buy-in at the desk level to really make it ⁓ really make it something awesome. So to your point, we've spoken to agency owners that are at that point and they're either thinking about additional hire or they're
wondering, hey, can we get more out of the current person and where is their, where is their potential kind of burnout point, which you never want to push past that that certain point. So we've seen very interesting use cases where agency owners have also been in just absolute hyper growth mode.
and decided to bring on a Phoebe versus bringing on a ⁓ bringing on a second scheduler as they're going through their growth mode. we've got an example of a franchise owner that owns four locations just south of me in southwest Florida. They were in this situation where they were thinking about do they bring on a second person. They had just purchased the rights to two additional territories. So they were going from two offices to four offices.
And we're trying to decide is do we hire a scheduler that's gonna run these two new offices and they just start their notebook? Does our current scheduler put some of their bandwidth into these two new locations? What they decided to do was bet on their rock star, bet on their their person that was really good at systems, had a lot of the tribal knowledge up top on
you know, the availabilities of caregivers, their preferences, where they would want to go. We partnered that really strong scheduler with One Phoebe environment. They have now ⁓ I think they're close to three Xing their total business from the time in which they first started with us back in November of twenty twenty five. They're looking at bringing on a second scheduler now, but they're doing this at more of that point in which
You're normally at two or three schedulers and you're thinking about bringing on your you know your fourth or fifth, they're doing that at a much different time at a much different rate. And they've done that at, you know, the the cost of, you know, half the cost of a normal OT in most areas.
Miriam Allred (15:17)
I think the thing that gets me most excited is the memory component. And so second to probably the caregivers, the the second highest turnover is in the scheduler role. And so inevitably you're gonna lose good schedulers and bad schedulers and they walk out the door with a ton of
information, qualitative information that lives in their brains about the clients and the caregivers, but with Phoebe, everything is coming through text and phone. There's all of this information, ambiguous availability, matching preferences, schedules, like all of that information is coming through these different like channels. But now with AI we're able to capture all of that and then AI can store that memory. And so even when you lose a scheduler, I I talked to an agency that said, you know
they had a scheduler, they were gonna replace a scheduler and the new scheduler was gonna walk in and have access to all of the memory from Phoebe and that is where this gets really powerful and that when you have people leave that all of that information doesn't walk out the door with them. It's all stored and AI has the ability to store all of this memory.
Corey Grissom (16:20)
Totally. And and the way that we've designed ours, it's it's not a black box experience where you're wondering like, hey, what context is is Phoebe like recommending off of? Where's this context coming from? With our system, you can go in there, you could see the context and the assumptions that Phoebe's made around caregivers based on their their confirmations of shifts, how responsive are they, ⁓ but down to things like their allergies, ⁓ different things they like to do on their shift and they may not like to do on their shift. Let's say
they're tired and they're not wanting to do a lot of heavy lifting, they can tell Phoebe that and Phoebe will find a job out there where they're not doing transfers or not having to do a Hoyer lift on that day. But it's real like to your point, it's it's really cool how fast that memory builds on itself.
⁓ we have agencies that are setting up our our overnight inbound call agent right now and they're doing that within a month to with a month to two months of going live on the Phoebe platform because the memory can build on itself so quickly now, where six months ago that would have just been a wild idea to have essentially a machine answering all of your phone calls, doing triage in real time.
But it's reducing your need to have an an on-call service. It's reducing your need to to bring on like say an additional staff member that's only focused on call outs and stuff during the day because
Phoebe not only learns from the information that's in the HR, but is also, to your point, learning from what does Sally and Jim tell Phoebe on the phone. And Phoebe remembers that just like your your top-notch scheduler that's building rapport, that remembers anniversaries, that remembers school graduations and things like that, and is constantly balancing all of that chaos. Phoebe does that in the background along with a scheduler. ⁓ and it really kind of leans into our ethos where we believe Phoebe is
is an optimizer and a multiplier of people, not a replacement of people. We're very much in the people industry. And we believe that the Phoebe platform is built to allow a scheduler or a care coordinator to really become an orchestrator and operator at the desk level versus just being replaced by a machine in this case.
Miriam Allred (18:38)
And I think a lot of owners are excited about AI and optimistic and and the stickiness where this gets challenging is actually the implementation with the office team and so schedulers, care coordinators, have you found resistance once you once you get through the owner and then you're actually working with these office teams, like do you feel like there's resistance from that demographic or
Corey Grissom (19:02)
100%. And I think that's where we're where we're doing a really good job on the success level is although we are an AI and agentic company, we onboard and support all of our products with real live people who have experience in the industry, have experience in software that support all of our clients with a very white glove approach from the time that they're onboarded all the way through just how they give us feedback.
on the product. ⁓ Me and our head of growth, Dave, always joke that anytime we're showing Phoebe, it's the ugliest Phoebe is ever going to be from a memory context, from the generative AI of Phoebe's voice to the features in the platform, like literally when we're showing it to prospects and clients, there's normally something new almost every day to show, which is super exciting. ⁓ But in that same world, if you're not keeping everyone in loop that's touching it and they don't know
What are all the new things that are coming out to help them? ⁓ then adoption is gonna be the thing that gets you turned off at the end of the day. So showing the value, showing how much time we're returning back to a scheduler, how many placements did Phoebe successfully place for them in the last 24 hours in the last week? Those are the the little wins that you prop up for the schedulers so they can realize, yeah, this is my little AI assistant just over in the corner, just rocking out for me. and it's been really
Really cool, like the resistance a few months ago is was a lot higher than it is today, and it's slowly gotten better and better. I think on the caregiver side, that's probably the most alarming thing for me is I think AI has been around enough that it's not a massive education curve with schedulers. ⁓ but on caregiver side, I've been blown away by how receptive people are to speak to Phoebe.
our data is showing us on average that the average caregiver will ask two to three more questions of Phoebe than they will their normal scheduler. ⁓ it's part of it's because we don't hide that it's an AI. We partner with the agency on how they should communicate out to the caregivers, let them know that hey, Phoebe is all knowing of the care plan, directions on how to get there. If you need to add more hours, drop drop hours, you can do this all through Phoebe. So almost like a genie, you may not get three wishes, but all
All-knowing in that regard. So ⁓ so we see caregivers spending additional time asking more questions about the care plans, which result in less last-minute cancellations because Phoebe will always confirm with the caregiver that they understand the care plan, they know how to get there, and these various things where a scheduler through the pace of the day may rush them off a call or they may not ask all the questions they would necessarily ask of a robot, if you will. So
I've been blown away by just how many conversations and how much context is actually driven from those calls because of
Miriam Allred (21:57)
I honestly love to hear it. I think of, you know, the bell curve and there's the early adopters. AI like we're in the mainstream. You know, they're
Six months ago, a year ago, two years ago, there was a lot of resistance, there was a lot of fear, there was a lot of anxiety. People are still skeptical of getting out in front of their caregivers, even out in front of their clients and families, but like it's to the point where it's in the mainstream. Every app, every device has got AI baked in right in your face. And so the resistance is just like dropping very quickly and that gets me excited because it's like, okay, we can really start to unlock.
so much more value and opportunities when that resistance has dropped and so we're we're basically getting there. So I ⁓ I'm picky and I'm big on market validation and I only hear good things about Phoebe. Obviously you guys are still building and still early stage and this is all just taking taking flight but
I think people are on the boat and they're excited and they're utilizing this technology and this is just the beginning and it's really exciting to see where it's going. So Corey, thanks for joining me. This has been a great conversation. If people want to learn more about Phoebe, they're an open book on what they're building and how they're thinking about things and it's great to just bounce ideas off of of of these technology companies. So I highly recommend that. So thanks, Corey. ⁓ Absolutely. Perfect.
Corey Grissom (23:08)
Thank you for having us today.