Editor
in
Chief
Sarah
Wheeler
sat
down
with
Diane
Yu,
co-founder
and
CEO
of

TidalWave,
to
talk
about
the
benefits
of
building
an

AI-first
company
in
today’s
business
environment.

Yu
founded
and
sold
ad
tech
platform

FreeWheel
to

Comcast
in
2014,
and
she
served
as
chief
technology
officer
at

Better.com
from
2021-2022.

This
interview
has
been
edited
for
length
and
clarity.

Sarah
Wheeler:
What’s
the
advantage
to
building
a
company
from
the
ground
up
as
AI-first?

Diane
Yu:
It’s
very
fortunate
that
we
started
TidalWave
at
the
right
time
—
where
the
tech
model
for
digitization
in
the
industry
just
started
to
pick
up
and
at
the
same
time,
generative
AI
really
came
to
the
surface.
As
a
technologist
and
as
an
engineer,
I
have
been
following
that
trend
for
a
long
time
and
then
realized
this
could
be
the
very
last
piece
of
the
puzzle.

Now
we
can
build
something
unique
from
scratch
—
an
AI-powered
co-pilot
engine
—
without
the
burden
others
have
of
legacy
software
they
have
to
adapt
to.
We
were
able
to
move
so
fast
and
so
quick
that
coming
out
of
stealth
we
were
able
to
get
approved
for
integration
from

Fannie
Mae
and

Freddie
Mac.

SW:
What
differentiates
your
technology?

DY:
In
order
to
apply

generative
AI
to
the
mortgage
industry,
it
has
to
be
100%
accurate
—
no
hallucinating.
And
this
is
the
reason
why
we
chose
to
purposely
build
an
AI
engine,
not
using
any
type
of
ChatGPT
wrapper.
A
lot
of
companies
are
saying
they
have
something
similar,
but they
were
building
a
wrapper,
and
that
wouldn’t
work,
because
there’s
no
way
you
can
stop
the
hallucinating
problem.
So,
that’s
No.
1.
We
chose
a
harder
path,
but
eventually
we
will
come
out
winning,
because
we
purposely
built
a
co-pilot
engine.

No.
2,
it
has
to
be
transparent
—
I
typically
say
it’s
a
white
box.
I
also
use
the
terminology
of
a
reasoning
traceability.
That’s
a
key
criteria
for
us,
because
you
have
to
make
sure
it’s
super
clear
to
all
of
those
lenders
how
you
come
to
the
conclusion,
how
you
create
the
reasoning
based
on
your
interaction
with
the
borrower,
so
that
lenders
can
go
back
and
trace
back
100%
how
everything’s
being
evaluated
based
on
their
standard.

The
last
thing
that
differentiates
our
technology
is
how
we
protect
consumers’
personal
financial
data.
Many
companies,
when
they
say
they
are
utilizing
generative
AI,
OK,
if
they
send
consumers’
personal
financial
data
out
to

OpenAI,
that’s
not
going
to
work.
That’s
why
we
purposely
built
our
own
library
and
our
decision
engine
so
that
we
can
safeguard
that
information,
and
then
prevent
any
type
of
leakage
by
utilizing
a
generated
AI
portion
out
there.

SW:
How
are
you
leveraging
AI
differently
than
some
legacy
companies?

DY:
Our
AI
co-pilot
Solo
is
working
with
the
consumer
via
the
conversation,
interacting
with
the
consumer,
so
that
we
understand
the
purpose
of
the
consumer
interaction
and
also
get
permission
to
access
their
data.
When
the
consumer
allows
us
to
have
access
to
their
information
—
as
an
example,
for
the

credit
report
—
we
would
use
our
AI
engine
in
the
background
to
evaluate
the
individual’s
credit
report
data.

We
would
identify
the
items
from
their
credit
report
data
that
require
further
information
based
on
the
underwriting
pipeline.
So,
we
would
ask
the
consumer
to
provide
those
additional
documents,
knowing
that
once
the
consumer
started
a
mortgage
application
an
underwriter
will
have
to
ask
those
questions
anyway.
We’re
also
calculating
everything,
like
their
income,
and
we’re
also
gaining
permission
to
access
their
financial
information
about
their
income.

That’s
the
big
difference
compared
to
a
lot
of
legacy
lender
technology,
which
just
collects
documents
to
send
off
to
different
departments.
We
use
our
AI
capability
to
interact
with
the
consumer
already,
so
once
it
gets
to
the

underwriting
department
of
our
customers,
they
can
review
and
check,
check,
check
—
everything’s
good.

SW:
How
does
TidalWave
fit
into
the
next
iteration
of
the
mortgage
industry
where
there
are
fewer
people?

DY:
Lenders
have
already

cut
to
the
bone,
and
they’re
still

losing
money.
And
when
the
interest
rate
comes
around,
when
volume
comes
back,
the
lenders
have
two
choices.
One
is
to
hire
all
those
people
as
quickly
as
possible
and
bring
them
back,
and
then
train
them
on
the
process
that
people
aren’t
familiar
with.
So,
you
originate
with
a
lot
of
problems,
a
lot
of
errors.

Or
you’re
utilizing
a
new
capability
and
helping
your
existing
staff
members
be
a
lot
more
productive
—
they
can
just
focus
on
things
that
they’re
so
specialized
in
and
so
good
at
doing.
And
then
you
can
handle
the
volume
when
it’s
low,
and
you
can
chase
the

additional
volume
when
it
comes
back.

SW:
How
do
you
think
about

security?

DY:
Coming
from
the
background
of
building
a
technology
platform,
and
then
at
FreeWheel,
my
first
company,
the
type
of
company
utilizing
FreeWheel’s
technology
is
a
company
like

NBC
and

CNN,
global
media
companies.
So,
we
understand
100%
how
important
it
is
for
the
platform
to
be
highly
secure.

We
take
the
same
approach
at
TidalWave,
because
we
understand
that
bringing
on
customers
that
handle
personal
financial
data,
it
could
make
or
break
a
company
if
you
do
it
wrong.
So,
we
pay
attention
to
the
security
from
day
one.
As
an
example,
even
at
this
stage,
we
encrypt
everything
so
that
you
don’t
have
to
worry
about
being
hacked
and
then
having
consumers’
information
being
leaked
out.

SW:
What
keeps
you
up
at
night?

DY:
 My
worry
is
that
volume
is
going
to
come
back
and
a
lot
of
lenders
will
have
no
choice
but
to
run
out
and
hire
a
lot
of
people,
and
basically
go
through
that
nightmare
of
the
industry
again
of
hire/fire.
So,
as
a
small
startup,
we’ve
run
super
fast
because
we
want
to
make
sure
that
we
can
help
as
many
lenders
as
possible
so
that
they
don’t
have
to
go
through
this
nightmare.

SW:
What
does
your
team
look
like?

DY:
We
are
a
team
of
15
and
growing.
Half
of
the
folks
are
in
New
York,
so
we
come
to
the
office
like
four
days
a
week.
And
for
a
small
startup,
I
have
to
say
that
face
to
face
is
so
important,
especially
because
we’re
evolving
so
quickly.

This
is
my
second
company
and
I
am
so
fortunate,
especially
from
an
engineering
talent
perspective.
I’ve
been
able
to
bring
the
best
team
with
me.
 My
core
co-founding
team
are
the
ones
who
built
the
first
company
with
me
from
scratch.
They
followed
me
into
my
time
at
Better
and
then
followed
me
out
of
Better,
so
that
team
has
the
benefit
of
working
with
each
other
for,
like,
15
to
20
years.

And
then
the
other
half
of
the
team
is
the
members
that
I
had
the
opportunity
to
get
to
know
during
my
Better
days.
I
also
have
people
with
20-plus
years
of
mortgage
origination
and
loan
officer
experience
working
with
us.
The
benefit
of
a
small
team
with
the
right
level
of
expertise
is
that
we’re
working
together
for
the
same
common
goal.

SW:
As
a
startup,
how
do
you
deal
with
the
pace
of
change,
especially
in
AI?

DY:
You
need
to
make
sure
you
focus
on
what
you
specialize
in.
So,
we
focus
on
underwriting,
and
we
fully
focus
on
the
mortgage
origination
knowledge
that
we
know
no
one
else
will
be
out
there
building.
Now
we
see
a
lot
of
companies
building
multiple

large
language
models,
which
is
a
good
thing,
because
we
can
utilize
all
of
them,
and
then
whichever
one
is
the
winner,
we’ll
do
a
deeper
integration
with
them.

I
think
of
that

famous
quote
about
software
eating
the
world,
and
now
AI
is
eating
software.
And
we
truly
see
that
right
in
front
of
us.
Using
AI
capability,
it
can
gradually
take
away,
piece
by
piece,
all
the
existing
legacy
software
capabilities.

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