October 12, 2025 • 11 mins
Domenic Donato, CEO and Co-Founder of Attuned Intelligence, discusses his company’s innovative platform designed to help operations leaders optimize their AI agents. He shares insights on managing high-pressure situations, mitigating risk, and ensuring accuracy in high-stakes decision-making environments.
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Episode Transcript
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(00:00):
This is Laura Dierda with the Becker's Healthcare
Podcast. I'm thrilled today to be joined by
Dominic Donato, cofounder and CEO of Attuned Intelligence.
Dominic, it's a pleasure to have you on
the podcast today.
Yeah. Thank you, Laura, for having me.
Absolutely.
Now I I'm really excited to speak with
you because you've had some exciting news with
Attuned. Recently, you've announced raising the seed funding
(00:22):
of $13,000,000
led by Radical Ventures and Threshold Ventures,
which is a really exciting milestone for the
company. So I'm looking forward to talking through
that and what's ahead. But first and foremost,
can you tell us a little bit more
about yourself and the idea behind the tune?
Yeah. I'd be happy to.
Try and keep this short. It it it
it did start about fifteen years ago.
(00:45):
So I was introduced to AI way back
when in grad school, neural networks in particular.
And when I saw them, I just felt
like they would change the world, and so
really made it my mission to just be
a part of that. It brought me to
do a PhD, join Google, and then eventually
DeepMind.
And it was at DeepMind that I had
(01:06):
the idea of applying AI to health care
because they had, an applied health care
arm there. And so the idea was to
learn, about this foundational
AI technology and then use it to, you
know, make the world, a better place for
all of us. That was part of their
mission, mission, and I shared that vision with
them.
And so that planted the seed, but it
(01:26):
wasn't until after leaving there, going to AssemblyAI
to really
lead the the speech to text kinda revolution
in AI,
that I saw the exact
use case that could be impactful for health
care, which was really taking the burden off
of these influx of calls that hospitals and
(01:47):
health care systems get
every single day,
that go unanswered,
but are critical for providing care,
to those who need it. And that's really
what inspired me to found TUNED.
That's amazing to hear. And, you know, what
a great story and,
mission behind the company to really, support better,
(02:10):
health care. So that's amazing to hear. And
I'm curious. Could you talk a little bit
more about, you know, what's inspiring you to
focus on solving some of the patient access
issues in hospital call centers with AI,
especially today? I know, you know, so many
conversations we have with health care executives and
leaders are talking about throughput and patient access
as being critical challenges that they're trying to
(02:30):
solve for. So we'd love to hear,
just what continues to to be top of
mind for you around those issues.
Yeah. Thank you.
So the
the main,
issue here is that with these large health
systems,
you usually end up with a call center,
either centralized or sometimes,
decentralized.
(02:52):
And you get just a massive influx of
calls for all sorts of reasons. And so
you have a a real issue with,
staffing because,
as you can imagine,
hospitals are very intricate. There's a lot of
departments, a lot of specialties. There's insurance questions.
There's scheduling these questions, refills. There's all a
massive
variety of things that someone could be calling
(03:14):
about, and you have to get that call
to the right human,
in order to help the patient with their
specific need or question.
And you may not have someone trained,
in that specific area. And so there's a
constant,
essentially, shortage of people to handle these phone
calls.
And given that this is the the way
that, you know, all of us communicate with
(03:36):
hospitals, phone calls is is, like, 80% of
the way that people get access to care.
There's a real shortage. Most hospitals will say
that they're operating with 60% of the staff
that they need, and that continues to to
go down. So
having an AI that is able to answer
every single one of those calls and have
the skills necessary to
(03:58):
handle many of them or to route them
to the appropriate person who does have those
skills is immensely,
helpful in in relieving this issue.
Absolutely. I can imagine it makes life easier
for so many and it really improves the
efficiency,
of the call center and makes patients happier
as well. How does Attune's
(04:21):
supervised
AI ensure that safety and accuracy
in these urgent high stakes calls? What's really,
you know, helps hospitals feel that you can
trust them in in some of these high
pressure situations?
Yeah. So we specifically,
built our company around hospital and health system
(04:41):
main lines. So from the very beginning, we
knew we wanted to handle all the calls
coming into a large,
a large health system.
And we knew that we would be getting,
some very critical and sensitive calls, mixed in
with the, you know, normal calls that you
would get. And so from the very beginning,
just built in safety and supervision,
into the platform. Also, having a pretty deep
(05:02):
background in AI, I also knew that these
AIs would make mistakes.
That is just a fact.
But you can
mitigate that risk by having multiple AIs in
the same conversation and also having great escalation
to actual humans,
when something does need their attention. And that's
basically what we built from the beginning, and
(05:23):
I kinda joke to but our
AI handled, calls
actually have more AI and human supervision than
most, human phone calls today.
Oh, wow. That's amazing to hear. And, you
know, really a fascinating look at how the
technology is already making a big difference within
the field. What have you learned from scaling
(05:44):
this platform across some of the community health
centers as well as large health systems? Can
you tell us a little bit about that
over time?
Yeah. So we really learned that you need
to be able to,
help them, quickly. So it's not just the
call centers that are, short of staff. Right?
It's it's the entire,
hospital systems today, unfortunately,
(06:06):
in in The US.
And we're trying to help out the specific
area, of of patient access, but the IT
departments are also, you know, not staffed,
as much as they would like them to
be. So we needed a way to get
started quickly. And so we have this,
no integration starting point, essentially, where you just
forward your, main hospital line to the AI
(06:28):
agent that has been created for you, and
it will take care of some of the
basic quest things that that the patient access
struggles with, which is like routing to departments.
So large hospital systems might have a dedicated
team
just to route calls. And then it gets
even more difficult because,
we focus
on all all hospitals,
both, you know, private health systems as well
(06:49):
as fairly qualified
community
hospitals.
And there you have a a a large
diverse multilingual
population. And so even for routing calls, you
may need to call in an interpreter.
So what we've learned is just by being
able to get started quickly with this low
integration
starting point and handle the call in
(07:11):
the language of the patient
can offer immediate release, relief.
And then we continue on to go deeper
with,
EHR integrations
to take more of these calls end to
end for scheduling and refills, etcetera. But that
was, I would say, the biggest lesson early
on was you needed to be able to
provide relief immediately because, the help is any
(07:31):
help is is greatly appreciated.
Absolutely. I can imagine, you know, being able
to have that type of integration within the
EHR in other spaces,
you know, speeds up the time, as you
mentioned, for whatever,
initial assistance that's needed on the call and
to get patients the care they needed quickly.
(07:51):
From your experience, how has the technology impacted
both patient experience as well as the frontline
call center staff? What can you share with
us about the feedback you've heard there?
Yeah. So we build a a platform,
specifically for operations leaders.
So, essentially, it's a it's an entire holistic
platform that lets them, create, test,
(08:13):
deploy, monitor, and optimize their AI agents.
And
the response has been really positive because they
love the transparency and control. Like, they get
to see every single call. Right? They get
to see why the AI said what it
did, what it did,
what it thought about before doing so, and
it and and everything is kind of transparent.
(08:33):
This is where that oversight comes from. So
that would be the operations leaders, feedback. And
then the staff themselves, like I said, like,
they're they're they're overworked, in many in many
cases because the need is so great.
And so, usually,
we get feedback that there's, this sense of,
like, relief is the word that that is
(08:53):
used.
Less pressure on the call center because that,
you know, that that those calls that are
being deflected or automated kind of lower the
load,
for everybody.
And and so that's, like, the next, thing
we we get when we go live. And
then the patients, you know, they they get
faster handling times, which is appreciated, especially those
(09:14):
who are speaking, say, Spanish or Portuguese or
another language.
Usually, they would have to wait for an
interpreter to be brought in on that conversation
with a person who didn't speak that language.
Instead, they get to speak directly in their
language and get help much faster. So
it's kind of a win win win, situation,
and we're really grateful that the technology is
(09:35):
makes this possible.
Absolutely. That's that's fantastic to hear.
Before we wrap up, I'm curious. What's the
next path forward towards, safely handling 100% of
patient communications?
Where do you see the technology evolving?
Yeah. So we have a, multi,
multiple AIs in every conversation. We have ones
(09:57):
that are dedicated to speaking and understanding. We
also have ones that are dedicated to interacting
with the electronic health system
records, basically. So, like, Epic, etcetera.
We see that the automation
percentage increases as the AIs get more intelligent
and as we get better at using them
in concert together. And so, right now, you
(10:19):
know, you can handle, scheduling and refills and,
routing.
Specialty scheduling, for example, is still something that
we would have a human handle, but that
eventually also could be handled by AI. So
So there's a very, like, I would say,
multiyear
approach here
where as it is safe to do so,
we'll continue to,
automate more and more.
(10:40):
And, you know, the long term vision really
is to
transform
the way that,
patients communicate with their providers.
We want it to be very,
smooth and customized
and also relieve the pressure on the provider
themselves so they can focus more on delivering
care. So the vision is to transform
(11:02):
the way that,
patient access is is done in The US.
I love it. Dominic, thank you so much
for joining us on the podcast today. This
has been a a really fun conversation, and
likewise.
This is Laura Dierda with the Becker's Healthcare
Podcast. I'm thrilled today to be joined by
Dominic Donato, cofounder and CEO of Attuned Intelligence.
Dominic, it's a pleasure to have you on
the podcast today.
Yeah. Thank you, Laura, for having me.
Absolutely.
Now I I'm really excited to speak with
you because you've had some exciting news with
Attuned. Recently, you've announced raising the seed funding
(00:22):
of $13,000,000
led by Radical Ventures and Threshold Ventures,
which is a really exciting milestone for the
company. So I'm looking forward to talking through
that and what's ahead. But first and foremost,
can you tell us a little bit more
about yourself and the idea behind the tune?
Yeah. I'd be happy to.
Try and keep this short. It it it
it did start about fifteen years ago.
(00:45):
So I was introduced to AI way back
when in grad school, neural networks in particular.
And when I saw them, I just felt
like they would change the world, and so
really made it my mission to just be
a part of that. It brought me to
do a PhD, join Google, and then eventually
DeepMind.
And it was at DeepMind that I had
(01:06):
the idea of applying AI to health care
because they had, an applied health care
arm there. And so the idea was to
learn, about this foundational
AI technology and then use it to, you
know, make the world, a better place for
all of us. That was part of their
mission, mission, and I shared that vision with
them.
And so that planted the seed, but it
(01:26):
wasn't until after leaving there, going to AssemblyAI
to really
lead the the speech to text kinda revolution
in AI,
that I saw the exact
use case that could be impactful for health
care, which was really taking the burden off
of these influx of calls that hospitals and
(01:47):
health care systems get
every single day,
that go unanswered,
but are critical for providing care,
to those who need it. And that's really
what inspired me to found TUNED.
That's amazing to hear. And, you know, what
a great story and,
mission behind the company to really, support better,
(02:10):
health care. So that's amazing to hear. And
I'm curious. Could you talk a little bit
more about, you know, what's inspiring you to
focus on solving some of the patient access
issues in hospital call centers with AI,
especially today? I know, you know, so many
conversations we have with health care executives and
leaders are talking about throughput and patient access
as being critical challenges that they're trying to
(02:30):
solve for. So we'd love to hear,
just what continues to to be top of
mind for you around those issues.
Yeah. Thank you.
So the
the main,
issue here is that with these large health
systems,
you usually end up with a call center,
either centralized or sometimes,
decentralized.
(02:52):
And you get just a massive influx of
calls for all sorts of reasons. And so
you have a a real issue with,
staffing because,
as you can imagine,
hospitals are very intricate. There's a lot of
departments, a lot of specialties. There's insurance questions.
There's scheduling these questions, refills. There's all a
massive
variety of things that someone could be calling
(03:14):
about, and you have to get that call
to the right human,
in order to help the patient with their
specific need or question.
And you may not have someone trained,
in that specific area. And so there's a
constant,
essentially, shortage of people to handle these phone
calls.
And given that this is the the way
that, you know, all of us communicate with
(03:36):
hospitals, phone calls is is, like, 80% of
the way that people get access to care.
There's a real shortage. Most hospitals will say
that they're operating with 60% of the staff
that they need, and that continues to to
go down. So
having an AI that is able to answer
every single one of those calls and have
the skills necessary to
(03:58):
handle many of them or to route them
to the appropriate person who does have those
skills is immensely,
helpful in in relieving this issue.
Absolutely. I can imagine it makes life easier
for so many and it really improves the
efficiency,
of the call center and makes patients happier
as well. How does Attune's
(04:21):
supervised
AI ensure that safety and accuracy
in these urgent high stakes calls? What's really,
you know, helps hospitals feel that you can
trust them in in some of these high
pressure situations?
Yeah. So we specifically,
built our company around hospital and health system
(04:41):
main lines. So from the very beginning, we
knew we wanted to handle all the calls
coming into a large,
a large health system.
And we knew that we would be getting,
some very critical and sensitive calls, mixed in
with the, you know, normal calls that you
would get. And so from the very beginning,
just built in safety and supervision,
into the platform. Also, having a pretty deep
(05:02):
background in AI, I also knew that these
AIs would make mistakes.
That is just a fact.
But you can
mitigate that risk by having multiple AIs in
the same conversation and also having great escalation
to actual humans,
when something does need their attention. And that's
basically what we built from the beginning, and
(05:23):
I kinda joke to but our
AI handled, calls
actually have more AI and human supervision than
most, human phone calls today.
Oh, wow. That's amazing to hear. And, you
know, really a fascinating look at how the
technology is already making a big difference within
the field. What have you learned from scaling
(05:44):
this platform across some of the community health
centers as well as large health systems? Can
you tell us a little bit about that
over time?
Yeah. So we really learned that you need
to be able to,
help them, quickly. So it's not just the
call centers that are, short of staff. Right?
It's it's the entire,
hospital systems today, unfortunately,
(06:06):
in in The US.
And we're trying to help out the specific
area, of of patient access, but the IT
departments are also, you know, not staffed,
as much as they would like them to
be. So we needed a way to get
started quickly. And so we have this,
no integration starting point, essentially, where you just
forward your, main hospital line to the AI
(06:28):
agent that has been created for you, and
it will take care of some of the
basic quest things that that the patient access
struggles with, which is like routing to departments.
So large hospital systems might have a dedicated
team
just to route calls. And then it gets
even more difficult because,
we focus
on all all hospitals,
both, you know, private health systems as well
(06:49):
as fairly qualified
community
hospitals.
And there you have a a a large
diverse multilingual
population. And so even for routing calls, you
may need to call in an interpreter.
So what we've learned is just by being
able to get started quickly with this low
integration
starting point and handle the call in
(07:11):
the language of the patient
can offer immediate release, relief.
And then we continue on to go deeper
with,
EHR integrations
to take more of these calls end to
end for scheduling and refills, etcetera. But that
was, I would say, the biggest lesson early
on was you needed to be able to
provide relief immediately because, the help is any
(07:31):
help is is greatly appreciated.
Absolutely. I can imagine, you know, being able
to have that type of integration within the
EHR in other spaces,
you know, speeds up the time, as you
mentioned, for whatever,
initial assistance that's needed on the call and
to get patients the care they needed quickly.
(07:51):
From your experience, how has the technology impacted
both patient experience as well as the frontline
call center staff? What can you share with
us about the feedback you've heard there?
Yeah. So we build a a platform,
specifically for operations leaders.
So, essentially, it's a it's an entire holistic
platform that lets them, create, test,
(08:13):
deploy, monitor, and optimize their AI agents.
And
the response has been really positive because they
love the transparency and control. Like, they get
to see every single call. Right? They get
to see why the AI said what it
did, what it did,
what it thought about before doing so, and
it and and everything is kind of transparent.
(08:33):
This is where that oversight comes from. So
that would be the operations leaders, feedback. And
then the staff themselves, like I said, like,
they're they're they're overworked, in many in many
cases because the need is so great.
And so, usually,
we get feedback that there's, this sense of,
like, relief is the word that that is
(08:53):
used.
Less pressure on the call center because that,
you know, that that those calls that are
being deflected or automated kind of lower the
load,
for everybody.
And and so that's, like, the next, thing
we we get when we go live. And
then the patients, you know, they they get
faster handling times, which is appreciated, especially those
(09:14):
who are speaking, say, Spanish or Portuguese or
another language.
Usually, they would have to wait for an
interpreter to be brought in on that conversation
with a person who didn't speak that language.
Instead, they get to speak directly in their
language and get help much faster. So
it's kind of a win win win, situation,
and we're really grateful that the technology is
(09:35):
makes this possible.
Absolutely. That's that's fantastic to hear.
Before we wrap up, I'm curious. What's the
next path forward towards, safely handling 100% of
patient communications?
Where do you see the technology evolving?
Yeah. So we have a, multi,
multiple AIs in every conversation. We have ones
(09:57):
that are dedicated to speaking and understanding. We
also have ones that are dedicated to interacting
with the electronic health system
records, basically. So, like, Epic, etcetera.
We see that the automation
percentage increases as the AIs get more intelligent
and as we get better at using them
in concert together. And so, right now, you
(10:19):
know, you can handle, scheduling and refills and,
routing.
Specialty scheduling, for example, is still something that
we would have a human handle, but that
eventually also could be handled by AI. So
So there's a very, like, I would say,
multiyear
approach here
where as it is safe to do so,
we'll continue to,
automate more and more.
(10:40):
And, you know, the long term vision really
is to
transform
the way that,
patients communicate with their providers.
We want it to be very,
smooth and customized
and also relieve the pressure on the provider
themselves so they can focus more on delivering
care. So the vision is to transform
(11:02):
the way that,
patient access is is done in The US.
I love it. Dominic, thank you so much
for joining us on the podcast today. This
has been a a really fun conversation, and
likewise.
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