August 7, 2025 • 11 mins
I spoke with Jim Sullivan and Tom Palladino, the Founder and President, respectively, at eDiscovery AI, which leverages artificial intelligence for document review, privacy response, investigations, and litigation. We discussed how legal professionals should prepare for and adapt to an AI-centric e-discovery landscape, the value of early case intelligence, and the biggest opportunity for legal teams to improve outcomes by embracing AI.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
Welcome to Reinventing Professionals,a podcast hosted by industry analyst
Ari Kaplan, which shares ideas,guidance, and perspectives from market
leaders shaping the next generationof legal and professional services.
This is Ari Kaplan, and I'm speaking todaywith Jim Sullivan and Tom Palladino, the
(00:24):
Founder and President, respectively, ateDiscovery AI, which leverages artificial
intelligence for document review, privacyresponse, investigations, and litigation.
Jim, Tom, great to see you.
Thanks for having us.
Jim, tell us about your backgroundand the genesis of e-Discovery ai.
(00:45):
I'm a computer nerd at heart.
But I'm also an attorney.
I've been in the discovery space forabout 10 years, and I really was that
traditional predictive coding nerd,consulting on predictive coding using
technology to solve eDiscovery problems.
And this came from my experienceworking with e-discovery cases, using
analytics, using predictive coding, andseeing a lot of the shortcomings and
problems that we struggled to solve 10years ago, five years ago, and, really
(01:09):
understanding how well AI is at solvinga lot of those problems, solving the new
things that we couldn't even touch beforethat there just wasn't a solution for.
So, a lot of what we're doing is reallyjust working on building solutions to
problems that we've had for a long timethat we can now solve that we couldn't
before, as well as trying to move the in anew direction and really taking advantage
of generative AI to change things overalland to make the entire process better.
(01:33):
Tom, tell us about your backgroundand how your experience in the
legal industry has helped shape thevision for applying AI to discovery.
I was one of the co-founders withAndrea Wallack of NightOwl Global.
We got acquired in 2020 by HaystackID,and I stayed with Haystack for
two years, which was great.
And then I was out of the industry for ayear and I kept going to Legalweek just
(01:56):
because it's, I see a lot of friendsthere and it's always interesting
and I was really asking about ai.
I was very interested, you know, I wasthinking about how it might change the
industry and I was introduced to Jim.
Through a mutual friend and I wasabsolutely blown away by what he had
already built, what he was doing.
I wanted to be part of it immediately.
In the year and a half that I've beenworking with Jim, I just see more and
(02:16):
more potential for this on, in the future.
Jim, what should legal professionalsbe doing today to prepare for and adapt
to an AI centric eDiscovery landscape?
Use it.
Just use it.
Use it for fun.
Use it for work.
Use it for whatever itis that you're doing.
(02:37):
Generative AI is incredibly powerful.
Most people have access to somethingsimple like ChatGPT to help
brainstorm ideas, answer questions.
One of my primary ways of using it earlyon was I used to work with my daughter.
She used to like drawing pictures.
So we would just describethings and AI would draw it.
And she would come up with another thing.
An AI would draw and it would bea cat riding a unicorn, jumping
(02:59):
over a rainbow, and we'd makecoloring books and things like that.
You just get experience from using it,seeing how it works, how it answers
some questions, what things it's goodat, what things it's not good at.
And then just to take that a step furtheris, use it in your job, use it, with.
What we're trying to accomplish.
One thing I saw too often with predictivecoding, and we're seeing a little
bit now, but luckily not nearly asmuch, is people that are pushed into
(03:21):
a situation where their first useof technology is out of necessity or
panic, where, they don't have time.
They have to use a technologysolution because there's
no other options available.
They're using it for the first timeon the biggest projects of their life.
The number of times where we saw someoneuse predictive coding for the first time
(03:42):
on the massive second request where theyhad no other choices, don't do that.
Test it out on small projects.
Use it on small matters.
Run it side by side withyour existing process.
Do it exactly like you're doingnow, but then do it the same
way with AI and see how AI worksand see how much better AI is.
So when you come across those bigprojects and you need to use it, you
(04:03):
already have the familiarity you needand understanding of how it works.
Tom, what is early case intelligenceand how does it affect the way legal
teams prepare for complex litigation?
I was an early tech adopterthroughout my career.
I really liked the ECAtools that had come out.
(04:23):
They were successively betterat what they were doing.
They really allowed people to addressdata sets and understand them more quickly
in ways that were more sophisticated.
Jim led many, advanced text analyticsoperations, for years and, and
was a real proponent of that.
When I started to understand what we coulddo with GenAI, I immediately thought of
(04:47):
that early part of the process, but Ididn't think early case assessment really
said it well, because while those toolscan get their arms around what the data
looks like and give you some concepts andcluster things, they couldn't give you
the insights that you could literally getright at the beginning of a case now, so I
do think that things are rapidly changing,and I think this is one of the areas
(05:07):
that will change the most is that withinthe first week, the amount of insights
that we can gain from a data set havingto do with a case, an investigation, a
possible litigation coming up, a breachmatter is amazing and I didn't think that
ECA was the right container for that.
I thought early caseintelligence made more sense.
(05:27):
And I really do think that this isthe beginnings of what's gonna be
a very sticky go forward processthat, and people use our tools, but
I think there'll be others as well.
That'll be really good.
But I just think the amount ofinformation that you're going to be
able to get from small and large datasets within three days, five days.
This is compressing what it took 12weeks to understand, in 2022 or 2023
(05:51):
I don't know what that ripple effectis to change, our industry on, maybe
it's just a time compressor rightnow and other things will come along.
But I do think if you're that early ina litigation and you understand so much
about your data that fast, what doesthat relationship look like now between
corporation, law firm, provider, software.
I think it's gonnareshuffle that a little bit.
Jim, how does servicing key documents,people, events before a document review
(06:17):
begins in power litigation support teams?
It just gives you more knowledge.
It gives you more insights into yourdata, so now you can move forward with
that information to make your processmore efficient, better, across the board.
We're always trying to find waysto give you information that helps
your case as early on as possiblewith as little effort as possible.
(06:37):
We don't want it to be that youhave to go through a tremendous,
number of hoops to jump through , toget pieces of information or,
have to do a ton of upfront work.
People really don't like goingthrough long drawn out processes
to try to train a model.
We're just trying to get you theinformation that you need as quickly as
you can with as little effort as possible.
So then when you face that firstcase and you're on your first week.
(07:00):
Whether you're starting to do adocument review in a traditional
fashion, whether you're gonna usetechnology in some way, having all
that information at your fingertipsreally makes it a smoother process.
I think we've all been in cases, at sometime, where we had a review, a protocol,
and we started working on a review witha team of people, and as we learned more
about that data, that protocol evolved.
(07:22):
We learned who the different partiesare, we learned what some of the
events are, what some things that wedidn't know upfront, and that changed
how the document review happened.
And it evolves over time.
And I think most human docreviews evolve over time.
So we're trying to just getyou that information before
you start so you already knoweverything that's gonna come in.
(07:42):
And now obviously some things arestill gonna pop up, but we can try
to minimize that as much as we can.
Tom, where do you see the mostsignificant opportunities for legal
teams to improve outcomes in e-discoveryand litigation by embracing AI?
In a risk assessment business, right?
In the end, if somebody's doing aninvestigation or somebody's responding
(08:04):
to, litigation, we are trying tounderstand where we sit in that,
what is the risk that they want?
Even the spends and the proportionality,all stems from that equation.
And AI is going to, acceleratethis risk assessment.
Am I investing in this case, knowingwhat I know now in two weeks.
Along with outside counsel who israpidly adapting to this shortened
(08:26):
timeframe and knowing so much, Ithink we're going to see things
move faster to conclusions with AI.
I think that's good for everybody.
There's a growing mountain ofdata that can only be managed
by tools like this today.
We can't use older methods to dothis and by the way, it's interesting
because I'm talking about morecriminal matters than I ever have.
My career has only been civillitigation for 25 years.
(08:48):
But criminals also buried under a mountainof data that they can't get through.
They don't have the budgetsto get through, and it just
gets left behind a lot.
And I think these tools aregoing to accelerate that
process, make it more manageable.
I think they're playing fieldlevelers in a way because plaintiffs
can use this as well as defensecan now to get through data.
So I do think that, this is goingto change how this plays out.
(09:10):
I don't think big productions andlong, case cycles are necessarily
going to be an advantage anymore.
I do think there's gonna be someshifts, but with what the effect
that AI has on, what happens inthis whole risk assessment cycle.
Jim, how do you see e-discovery evolving?
I think we're gonna be able to identifyrisks earlier on and, hopefully, at
(09:32):
a point where we can identify risksbefore they become litigation, identify
the issues before they become civilcases, identify the problems before
they become bigger issues to helpthose corporations save a lot of the
money associated with those risks.
So if we could identify a risk earlieron there's just a lot of advantages
to how that can save time and money.
And shrinking the impact of the discoveryphase or the review phase, in a case
(09:57):
where it's now gonna be a lot easier,it's gonna be a lot faster, it's
gonna be a lot cheaper to get to theinformation you need to get to so you
can focus on the other parts of thecase that matter and hopefully being
addressing, what we wanna know is,are we gonna win or lose that case as
quickly as possible so we can determineis this something that we wanna settle?
Is this something we need to work out?
A lot of that case strategycomes from the knowledge and the
(10:18):
information that we can gain.
This is gonna give us knowledge andinformation earlier, faster, better, and
going to only improve to a point whereat some point we're gonna know nearly
everything at the tip of our fingers.
This is Ari Kaplan speaking with JimSullivan and Tom Paladino, the founder and
(10:39):
president respectively at eDiscovery ai,which leverages artificial intelligence
for document review, privacy response,investigations, and litigation.
Jim, Tom, thanks so very much.
Thanks.
Thank you.
Thank you for listening to theReinventing Professionals Podcast.
Visit reinventing professionals.com orari kaplan advisors.com to learn more.
Welcome to Reinventing Professionals,a podcast hosted by industry analyst
Ari Kaplan, which shares ideas,guidance, and perspectives from market
leaders shaping the next generationof legal and professional services.
This is Ari Kaplan, and I'm speaking todaywith Jim Sullivan and Tom Palladino, the
(00:24):
Founder and President, respectively, ateDiscovery AI, which leverages artificial
intelligence for document review, privacyresponse, investigations, and litigation.
Jim, Tom, great to see you.
Thanks for having us.
Jim, tell us about your backgroundand the genesis of e-Discovery ai.
(00:45):
I'm a computer nerd at heart.
But I'm also an attorney.
I've been in the discovery space forabout 10 years, and I really was that
traditional predictive coding nerd,consulting on predictive coding using
technology to solve eDiscovery problems.
And this came from my experienceworking with e-discovery cases, using
analytics, using predictive coding, andseeing a lot of the shortcomings and
problems that we struggled to solve 10years ago, five years ago, and, really
(01:09):
understanding how well AI is at solvinga lot of those problems, solving the new
things that we couldn't even touch beforethat there just wasn't a solution for.
So, a lot of what we're doing is reallyjust working on building solutions to
problems that we've had for a long timethat we can now solve that we couldn't
before, as well as trying to move the in anew direction and really taking advantage
of generative AI to change things overalland to make the entire process better.
(01:33):
Tom, tell us about your backgroundand how your experience in the
legal industry has helped shape thevision for applying AI to discovery.
I was one of the co-founders withAndrea Wallack of NightOwl Global.
We got acquired in 2020 by HaystackID,and I stayed with Haystack for
two years, which was great.
And then I was out of the industry for ayear and I kept going to Legalweek just
(01:56):
because it's, I see a lot of friendsthere and it's always interesting
and I was really asking about ai.
I was very interested, you know, I wasthinking about how it might change the
industry and I was introduced to Jim.
Through a mutual friend and I wasabsolutely blown away by what he had
already built, what he was doing.
I wanted to be part of it immediately.
In the year and a half that I've beenworking with Jim, I just see more and
(02:16):
more potential for this on, in the future.
Jim, what should legal professionalsbe doing today to prepare for and adapt
to an AI centric eDiscovery landscape?
Use it.
Just use it.
Use it for fun.
Use it for work.
Use it for whatever itis that you're doing.
(02:37):
Generative AI is incredibly powerful.
Most people have access to somethingsimple like ChatGPT to help
brainstorm ideas, answer questions.
One of my primary ways of using it earlyon was I used to work with my daughter.
She used to like drawing pictures.
So we would just describethings and AI would draw it.
And she would come up with another thing.
An AI would draw and it would bea cat riding a unicorn, jumping
(02:59):
over a rainbow, and we'd makecoloring books and things like that.
You just get experience from using it,seeing how it works, how it answers
some questions, what things it's goodat, what things it's not good at.
And then just to take that a step furtheris, use it in your job, use it, with.
What we're trying to accomplish.
One thing I saw too often with predictivecoding, and we're seeing a little
bit now, but luckily not nearly asmuch, is people that are pushed into
(03:21):
a situation where their first useof technology is out of necessity or
panic, where, they don't have time.
They have to use a technologysolution because there's
no other options available.
They're using it for the first timeon the biggest projects of their life.
The number of times where we saw someoneuse predictive coding for the first time
(03:42):
on the massive second request where theyhad no other choices, don't do that.
Test it out on small projects.
Use it on small matters.
Run it side by side withyour existing process.
Do it exactly like you're doingnow, but then do it the same
way with AI and see how AI worksand see how much better AI is.
So when you come across those bigprojects and you need to use it, you
(04:03):
already have the familiarity you needand understanding of how it works.
Tom, what is early case intelligenceand how does it affect the way legal
teams prepare for complex litigation?
I was an early tech adopterthroughout my career.
I really liked the ECAtools that had come out.
(04:23):
They were successively betterat what they were doing.
They really allowed people to addressdata sets and understand them more quickly
in ways that were more sophisticated.
Jim led many, advanced text analyticsoperations, for years and, and
was a real proponent of that.
When I started to understand what we coulddo with GenAI, I immediately thought of
(04:47):
that early part of the process, but Ididn't think early case assessment really
said it well, because while those toolscan get their arms around what the data
looks like and give you some concepts andcluster things, they couldn't give you
the insights that you could literally getright at the beginning of a case now, so I
do think that things are rapidly changing,and I think this is one of the areas
(05:07):
that will change the most is that withinthe first week, the amount of insights
that we can gain from a data set havingto do with a case, an investigation, a
possible litigation coming up, a breachmatter is amazing and I didn't think that
ECA was the right container for that.
I thought early caseintelligence made more sense.
(05:27):
And I really do think that this isthe beginnings of what's gonna be
a very sticky go forward processthat, and people use our tools, but
I think there'll be others as well.
That'll be really good.
But I just think the amount ofinformation that you're going to be
able to get from small and large datasets within three days, five days.
This is compressing what it took 12weeks to understand, in 2022 or 2023
(05:51):
I don't know what that ripple effectis to change, our industry on, maybe
it's just a time compressor rightnow and other things will come along.
But I do think if you're that early ina litigation and you understand so much
about your data that fast, what doesthat relationship look like now between
corporation, law firm, provider, software.
I think it's gonnareshuffle that a little bit.
Jim, how does servicing key documents,people, events before a document review
(06:17):
begins in power litigation support teams?
It just gives you more knowledge.
It gives you more insights into yourdata, so now you can move forward with
that information to make your processmore efficient, better, across the board.
We're always trying to find waysto give you information that helps
your case as early on as possiblewith as little effort as possible.
(06:37):
We don't want it to be that youhave to go through a tremendous,
number of hoops to jump through , toget pieces of information or,
have to do a ton of upfront work.
People really don't like goingthrough long drawn out processes
to try to train a model.
We're just trying to get you theinformation that you need as quickly as
you can with as little effort as possible.
So then when you face that firstcase and you're on your first week.
(07:00):
Whether you're starting to do adocument review in a traditional
fashion, whether you're gonna usetechnology in some way, having all
that information at your fingertipsreally makes it a smoother process.
I think we've all been in cases, at sometime, where we had a review, a protocol,
and we started working on a review witha team of people, and as we learned more
about that data, that protocol evolved.
(07:22):
We learned who the different partiesare, we learned what some of the
events are, what some things that wedidn't know upfront, and that changed
how the document review happened.
And it evolves over time.
And I think most human docreviews evolve over time.
So we're trying to just getyou that information before
you start so you already knoweverything that's gonna come in.
(07:42):
And now obviously some things arestill gonna pop up, but we can try
to minimize that as much as we can.
Tom, where do you see the mostsignificant opportunities for legal
teams to improve outcomes in e-discoveryand litigation by embracing AI?
In a risk assessment business, right?
In the end, if somebody's doing aninvestigation or somebody's responding
(08:04):
to, litigation, we are trying tounderstand where we sit in that,
what is the risk that they want?
Even the spends and the proportionality,all stems from that equation.
And AI is going to, acceleratethis risk assessment.
Am I investing in this case, knowingwhat I know now in two weeks.
Along with outside counsel who israpidly adapting to this shortened
(08:26):
timeframe and knowing so much, Ithink we're going to see things
move faster to conclusions with AI.
I think that's good for everybody.
There's a growing mountain ofdata that can only be managed
by tools like this today.
We can't use older methods to dothis and by the way, it's interesting
because I'm talking about morecriminal matters than I ever have.
My career has only been civillitigation for 25 years.
(08:48):
But criminals also buried under a mountainof data that they can't get through.
They don't have the budgetsto get through, and it just
gets left behind a lot.
And I think these tools aregoing to accelerate that
process, make it more manageable.
I think they're playing fieldlevelers in a way because plaintiffs
can use this as well as defensecan now to get through data.
So I do think that, this is goingto change how this plays out.
(09:10):
I don't think big productions andlong, case cycles are necessarily
going to be an advantage anymore.
I do think there's gonna be someshifts, but with what the effect
that AI has on, what happens inthis whole risk assessment cycle.
Jim, how do you see e-discovery evolving?
I think we're gonna be able to identifyrisks earlier on and, hopefully, at
(09:32):
a point where we can identify risksbefore they become litigation, identify
the issues before they become civilcases, identify the problems before
they become bigger issues to helpthose corporations save a lot of the
money associated with those risks.
So if we could identify a risk earlieron there's just a lot of advantages
to how that can save time and money.
And shrinking the impact of the discoveryphase or the review phase, in a case
(09:57):
where it's now gonna be a lot easier,it's gonna be a lot faster, it's
gonna be a lot cheaper to get to theinformation you need to get to so you
can focus on the other parts of thecase that matter and hopefully being
addressing, what we wanna know is,are we gonna win or lose that case as
quickly as possible so we can determineis this something that we wanna settle?
Is this something we need to work out?
A lot of that case strategycomes from the knowledge and the
(10:18):
information that we can gain.
This is gonna give us knowledge andinformation earlier, faster, better, and
going to only improve to a point whereat some point we're gonna know nearly
everything at the tip of our fingers.
This is Ari Kaplan speaking with JimSullivan and Tom Paladino, the founder and
(10:39):
president respectively at eDiscovery ai,which leverages artificial intelligence
for document review, privacy response,investigations, and litigation.
Jim, Tom, thanks so very much.
Thanks.
Thank you.
Thank you for listening to theReinventing Professionals Podcast.
Visit reinventing professionals.com orari kaplan advisors.com to learn more.
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Special Summer Offer: Exclusively on Apple Podcasts, try our Dateline Premium subscription completely free for one month! With Dateline Premium, you get every episode ad-free plus exclusive bonus content.
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!