A
recent
legal
tech
funding
announcement
got
my
attention.
EvenUp,
which
provides
several
AI
tools
for
personal
injury
(PI)
plaintiffs’
lawyers,
announced
it
had
raised
$150
million
in
funding
from
Bessemer
Venture
Partners
and
REV,
among
others.
REV
is
the
venture
capital
arm
of
RELX
which
owns
LexisNexis.
With
this
funding,
EvenUp
now
has
a
$2
billion
valuation.
This
isn’t
just
another
big
funding
round.
It
signals
that
AI
for
plaintiffs’
lawyers
has
perhaps
reached
a
tipping
point
and
is
now
an
important
market.
What
Is
EvenUp?
EvenUp
provides
all
sorts
of
AI-driven
tools
to
help
PI
lawyers,
who
primarily
get
paid
on
a
contingency
fee
basis,
in
efficiently
drafting,
reviewing,
and
strategizing
across
the
entire
case
lifecycle,
according
to
the
press
release
announcing
the
funding.
It’s
trained
on
thousands
of
PI
cases
and
millions
of
medical
records
(more
on
this
below).
According
to
Rami
Karabibar,
CEO
and
co-founder
of
EvenUp,
“Legal
AI
is
no
longer
a
side
bet;
it’s
becoming
the
backbone
of
personal
injury
law.”
He’s
Right
About
That
I
think
Karabibar
is
right
about
that
for
several
reasons.
First,
AI
tools
enable
PI
lawyers
to
do
things
in
a
fraction
of
the
time
it
previously
took.
Since
they
spend
less
time
working
up
a
case,
their
profit
is
increased.
These
guys
don’t
bill
by
the
hour.
They
get
paid
based
on
the
result.
The
less
time
needed
to
get
to
the
result,
the
more
money
they
make.
Secondly,
because
they
can
do
things
with
EvenUp
in
less
time,
PI
lawyers
can
take
cases
that
would
not
have
previously
been
profitable
because
the
time
needed
to
work
up
the
case
would
exceed
the
foreseeable
recovery.
That
means
more
access
to
justice
for
folks
who
may
be
injured.
Raymond
Mieszaniec,
the
co-founder
of
EvenUp
and
its
COO,
puts
it
this
way,
“Our
mission
remains
simple:
give
every
victim
a
fair
shot
at
justice.”
Finally,
one
of
the
driving
needs
of
PI
lawyers
is
to
move
cases
to
resolution
as
quickly
as
they
can.
Why?
They
don’t
get
paid
unless
and
until
the
case
resolves.
The
EvenUp
team
understands
this
and
created
tools
to
get
work
done
faster
and
indirectly
lead
to
faster
resolutions.
So???
So,
what’s
the
big
deal?
Lots
of
big
funding
announcements
these
days.
Here’s
why
this
resonates
with
me
as
a
former
defense
lawyer.
I
first
came
across
EvenUp
at
the
ILTA
startup
alley
in
2023
and
wrote
about
the
company
then.
I
heard
a
young
guy
talking
from
the
startup
stage
about
a
tool
that
would
automate
the
drafting
of
demand
letters
for
PI
lawyers.
My
first
reaction
was
ho-hum,
that
doesn’t
sound
like
a
big
deal.
But
then
I
talked
to
him.
It
turns
out
that
the
young
guy
was
Mieszaniec.
He
was
driven
to
create
the
company
by
a
family
member’s
frustrating
experience
in
trying
to
recover
for
a
personal
injury
they
suffered.
That
experience
became
a
driving
force
and
passion
that
still
drives
a
lot
of
product
decisions.
What
Mieszaniec
and
EvenUp
were
doing
even
then
was
far
more
significant
and
a
harbinger
of
things
to
come:
they
were
using
AI
to
determine
valid
and
justifiable
demands.
It
worked
like
this:
a
lawyer
would
provide
EvenUp
with
all
the
relevant
facts
of
a
case
along
with
medical
and
employment
records,
and
any
other
important
information.
Using
AI
and
data
analytics,
EvenUp
would
compare
those
facts
to
verdicts
and
other
information.
(More
on
that
in
a
moment.)
The
tool
then
provided
a
realistic
demand
number
backed
by
data.
The
product
could
also
review
medical
records
and
other
materials
to
spot
inconsistencies
and
missing
information.
The
Key
Innovation:
Crowdsourced
Data
But
what
really
got
my
attention
was
that
Mieszaniec
convinced
a
number
of
plaintiffs’
lawyers
to
provide
EvenUp
with
access
to
actual
settlement
numbers
in
PI
cases
in
an
anonymized
way.
The
program
looked
not
only
at
actual
verdicts
in
cases
with
comparable
fact
patterns,
it
also
looked
at
settlements
in
cases
with
similar
fact
patterns. Since
most
cases,
then
and
now,
settle,
getting
that
information
in
that
way
was
truly
innovative
at
the
time.
I
saw
lots
of
value
that
could
come
from
the
tool
and
this
kind
of
thinking
not
only
for
plaintiffs’
lawyers
but
also
for
the
defense
side.
As
I
noted
at
the
time,
this
ability
could
enhance
settlements
since
it
would
give
both
sides
access
to
good
case
valuations.
It
would
enable
insurance
companies,
who
typically
insure
defendants
in
personal
injury
cases,
to
better
determine
reserves
for
the
exposures
presented
by
cases.
Insurance
companies’
business
model
is
based
on
the
ability
to
determine
exposures
accurately
and
then
reserve
the
funds
needed
to
pay
those
exposures.
So,
the
sooner
they
can
get
their
hands
on
the
information
to
set
that
reserve,
the
sooner
they
can
talk
settlement.
Because
the
EvenUp
analysis
was
based
on
real
data,
I
thought
it
would
provide
the
kind
of
accurate
demand
that
would
help
adjusters
set
reserves
and
would
lead
to
more
prompt
settlements,
which
benefits
all.
Mieszaniec
also
recognized
back
then
that
the
key
to
all
this
is
building
trust.
All
sides
have
to
know
that
the
EvenUp
number
is
a
good
one
and
well
supported.
I
concluded
from
talking
to
him
in
2023
that
“EvenUp
has
a
pretty
cool
idea.”
So,
How’d
That
Work
Out?
Not
surprisingly,
since
the
founders
obviously
well
understood
how
PI
cases
work
and
the
dynamics
leading
to
resolution,
EvenUp
has
grown
by
leaps
and
bounds.
It
now
offers
a
whole
slew
of
products
including
drafting
tools,
the
ability
to
create
expedited
demands,
medical
chronology
tools,
workflow
processes,
an
AI
assistant
to
answer
inquiries,
a
case
and
strategy
preparation
tool,
a
negotiation
preparation
tool,
a
settlement
repository
of
similar
matters
and
results,
and
even
a
tool
to
manage
firm
performance.
EvenUp
also
recently
announced
something
called
Mirror
Mode
which
allows
lawyers
to
create
documents
in
an
author’s
or
firm’s
previous
language,
style,
and
structure
by
mirroring
those
previously
created
documents.
As
Mieszaniec
puts
it,
“We
started
by
transforming
how
demands
were
built
—
today,
our
AI
spans
the
entire
case
lifecycle.”
The
Beauty
of
What
EvenUp
Is
Doing
EvenUp’s
approach
enhances
the
ability
for
individual
users,
who
are
often
with
small
firms,
to
tap
into
the
data
of
other
plaintiffs’
PI
lawyers.
That
enables
them
to
better
litigate
with
larger
firms
and
better
compete
with
the
very
large
national
plaintiffs’
firms.
It’s
also
a
good
example
of
what
can
happen
when
a
legal
tech
company
is
founded
by
people
with
passion
and
experience
in
an
area.
Yes,
the
founders
are
zealous
about
plaintiffs’
PI
work
and
the
lawyers
involved.
But
they
also
understand
the
need
to
get
these
cases
resolved
quickly
and
efficiently.
And
that
means
thinking
about
the
needs
not
only
of
plaintiffs
but
also
of
those
on
the
defense
side.
Of
course,
the
standard
concerns
with
AI
tools
remain:
algorithmic
bias,
data
privacy,
and
for
EvenUp,
whether
its
tools
will
further
gum
up
the
court
system.
But
for
now,
congrats
to
EvenUp
on
its
impressive
journey
from
startup
to
$2
billion
valuation.
Stephen
Embry
is
a
lawyer,
speaker,
blogger,
and
writer.
He
publishes TechLaw
Crossroads,
a
blog
devoted
to
the
examination
of
the
tension
between
technology,
the
law,
and
the
practice
of
law.
