As
artificial
intelligence
becomes
a
buzzword
in
nearly
every
healthcare
startup
pitch,
investors
are
finding
it
increasingly
challenging
to
distinguish
which
ones
are
actually
worth
the
hype.
That’s
why,
during
a
Thursday
panel
discussion
among
venture
capitalists
at
the
MedCity
INVEST
Digital
Health
conference
in
Dallas,
this
question
was
posed:
What
metrics
do
you
want
to
see
founders
highlighting
more
often
when
they’re
pitching,
and
what
is
one
red
flag
that
makes
you
question
the
validity
of
their
technology?
The
session
was
moderated
by
Neil
Patel,
head
of
ventures
at
Redesign
Health.
Here
is
what
they
had
to
say:
What
founders
should
be
highlighting
For
Maddie
Hilal,
investor
at
Oak
HC/FT,
it’s
important
that
startups
have
strong
net
revenue
retention,
which
measures
a
company’s
ability
to
retain
revenue
from
existing
customers.
“If
we
don’t
necessarily
have
visibility
into
those
hard
[profit
and
loss]
impact
proof
points,
but
your
existing
customer
base
is
growing
their
contracts,
clearly
they’re
excited,”
she
said.
“They’re
seeing
the
value.”
Another
investor
looks
for
companies
with
high
quality
data.
“If
you
have
better,
higher
quality
data,
you
can
solve
problems
in
a
much
better
fashion,
[with]
higher
predictability
of
models.
I
think
we
look
for
that.
What’s
that
proprietary
data
set?
What
are
you
trained
on?
Who
and
in
which
environment
has
this
been
deployed?”
said
Rohit
Nuwal,
partner
at
TELUS
Global
Ventures.
Vickram
Pradhan,
vice
president
of
Sopris
Capital,
wants
to
see
AI
startups
with
a
good
clinical
impact.
“People
are
asking
about
clinical
impact
in
a
way
that
they
weren’t
asking
maybe
five
years
ago,”
he
said
on
the
panel.
“I
think
the
reason
for
that
is
that
some
of
the
reimbursement
and
financial
and
payment
mechanisms
in
healthcare
are
a
bit
of
a
black
box.
…
But
if
you
know
what
you’re
doing
is
having
a
really
meaningful
clinical
impact,
that’s
a
pretty
good
foundation
to
know
that
that’s
going
to
have
value,
and
someone’s
going
to
want
to
pay
for
that.”
AI
red
flags
Many
healthcare
startups
will
use
the
AI
buzzwords
in
their
pitch
decks,
but
don’t
back
up
their
claims
with
strong
data
and
validating
metrics,
according
to
Hilal.
This
is
a
major
red
flag,
she
said.
Nuwal
echoed
Hilal’s
comments.
“I
think
there’s
a
lot
of
AI
being
thrown
around
where
it’s
essentially
largely
a
machine
learning
problem
that
people
are
trying
to
solve,”
he
said.
“I
don’t
blame
them,
founders
are
doing
a
tough
job
raising
money
in
this
environment,
so
you
need
to
play
the
game
a
little
bit.
But
I
think
just
being
authentic
about
what
problem
you’re
solving
goes
a
long
way.”
For
Pradhan,
a
red
flag
is
having
“squishy”
revenue
metrics.
It’s
important
for
companies
to
be
realistic
with
investors.
“I
think
it’s
very
common
to
see
today,
especially
with
some
of
these
AI
companies
that
are
doing
a
lot
of
pilots
talking
about,
‘We’ve
got
10
million
of
contracted
revenue.’
And
then
when
you
kind
of
go
a
layer
or
two
deeper,
it’s
like,
‘Oh
that’s
actually
what
it
will
look
like
in
year
three.’
…
It
just
makes
it
a
little
bit
more
challenging
to
arrive
at
a
sound
basis
of
truth,”
he
said.