The constant emergence of new companies and technologies makes rapid growth in the legal technology sector. Artificial Intelligence-powered technologies play a vital role in that regard. This week's Tech Savvy Lawyer podcast episode features Nicole Clark, the CEO of Trellis.Law.

Nicole is the co-founder of Trellis. Nicole specialized in business litigation and labor and employment matters, representing multinational corporations in high-profile trade secret disputes and complex class-action cases. Nicole's idea for Trellis was born late one night as she was trying to write a complicated motion for summary judgment. She didn't know much about the judge assigned to the case, leaving her unsure of how to structure the document. That's when a colleague let her browse through his old case files.  While doing so, she stumbled upon a past ruling by her judge, on her issue. Nichole felt like she had a detailed study guide for a final exam. She won her motion for summary judgment, and everything changed.

It quickly became obvious to Nicole that there was a massive opportunity to build a thriving, scalable legal analytics platform, one that would help democratize access to state trial court data. And she wanted to be the one to build it. Thus, the creation of Trellis.

Join Nicole and me as we talk about the following three questions and more!

1. Aside from Trellis, what are three AI programs attorneys should be using in their work today and why?

2. What are three things, Trellis does better due to its use of AI than its competition?

3. What are three things about AI you think attorneys should be keeping an eye out for in the future?

In our conversation, we cover the following:

[00.09] Tech setup – Starting the conversation, Nicole shares her current tech setup with us.

[09.10] AIs – Nicole shares three major areas in which attorneys should use AI tools and the reasons behind using them.

[15.29] Trellis – Nicole shares three things that they do better at Trellis than the other AI competitors out there.

[21.22] Federal courts – Nicole mentions structured data as a way of getting information when it comes to federal courts.

[23.39] The future – Collecting data, ethics, and data analytics are the three areas attorneys need to keep an eye out for in the future of AI.

[27.53] Content creation – Wrapping up the conversation, Nicole shares her idea on AI-generated content creation and its benefits for both lawyers and clients.

Resources:

Connect with Nicole

LinkedIn - linkedin.com/in/nicole-a-clark/

                  linkedin.com/company/trellis-law

Website - trellis.law/

Twitter - twitter.com/trellis_law

Facebook - facebook.com/trellis.law/

Instagram - instagram.com/trellis.law/

YouTube - youtube.com/channel/UCwfgGH-yMFmf3tW5M7UukIg

Equipment Mentioned in the Podcast

• MacBook Pro - apple.com/macbook-pro/

• LG dual screen - lg.com/us/monitors

• Apple XDR - apple.com/pro-display-xdr/

• Mac mice/keyboards - apple.com/shop/mac/accessories/mice-keyboards

Software & Services Mentioned in the Podcast

• DISCO - csdisco.com/

• KARA software - karasoftware.com/

Transcript (beta)

 Episode 56, getting the extra Step over opposing counsel with Court Data and Analytics. My conversation with Nicole Clark of Trellis.

Nicole is the co-founder of Trellis. She had specialized in business. And labor and employment matters representing multinational corporations and high profile trade secret disputes, and complex class action cases. Nicole's idea for Charles was born late one night as she was trying to write a complicated motion for summary judgment.

She didn't know much about the judge assigned to the case, which left her unsure about. How to structure the document. That's when a colleague let her browse through his old case files where she stumbled upon a pass ruling by her judge on her issue. Nicole felt like she had a detailed study guide to a final exam.

She won her motion for summary judgment and everything changed. With the help of a few software developers, Nicole began aggregating state trial court data to use in her own private practice, slowly accumulating an ever expanding database of tentative rulings by the judges in southern ca. This helped her solve her own need for access to state trial court data and analytics.

Nicole used these rulings to structure and organize every motion that came across her desk, weaving the facts of each case into the types of arguments highlighted by her specific judge. The results, her motion practice grew. It became obvious to Nicole that there was a massive opportunity to build a thriving scandal legal analytics platform.

One that would help democratize access to state trial court data, and she wanted to be the one to. Dus, the creation of Trellis. Enjoy. Hey everyone, just a quick shout out before we start. Are you enjoying the Texa Page podcast? Consider giving us a five star review at Apple Podcast or wherever you get your podcast feeds.

Also, consider buying us a cup of coffee or two from the link on our blog to help the phrase some of the production costs. Thanks and again, enjoy. Nicole, welcome to the podcast. Thank you so much. Great to be here. I appreciate you being here and to get things started, what is your current tech set up?

Well, let's see. I am in our office. We are fully remote in general, but we still have office space since we used to be in an in Brooks and company pre covid. And my MyTech setup is laptop, dual screens, apple, and then cordless. Mouse and keyboard, and then technical, but I have a gong here to bring for accomplishments.

Okay, so is is your laptop, is it? Is it an Apple or is it a Windows machine?

It's a MacBook Pro with an apple. And is it, uh, does it have an M one or an M two chip? You know, I'm not the important engineers, so no, I don't have that. And I actually, you know, turned over to Apple probably a couple years ago, but I was one of the last holdouts at the company, but over to Apple.

It's been an improvement. I understand why people like them.

Well, uh, then, you know, not to encourage spending money. You really do need to check out the M one and the M two chips. They are, they're really fast. I've had no compatibility issues and I'm gonna ask you, uh, perhaps a slightly silly sounding question.

Okay. I can get that alliteration out. You have for the. A Apple business account.

You know, I do have an Apple business account. Go ahead. Especially cause we have engineers that mm-hmm. need laptops. Mm-hmm. and it's just made, and it's made it really easy when we need to get new equipment. So yes, we do have one.

And so you know that they've got a great buyback program.

No, I don't know that. So

much more so based on how old your machine is of course's. Also the conditions of the machine, you may be able to sell that in exchange for a. And get some good credit for it. Is it the most amount of credit you can get for it?

No, but it does take out a lot of the back and forth and worrying about, you know, if the person actually gonna pay me and proper disposal Totally. Or, or reinstall it of the whole system so that all your stuff is wiped out. Of course, I would encourage you to, you know, wipe your stuff yourself, but you know, you are the boss and.

Interesting. So the two other things I'm gonna leave you with on this, okay, on this part of the conversation is one, check out a podcast called the Mac Power Users. I'm sure the audience is just tired of me constantly referring to that every time I come across. A Mac user, but it's a great podcast. It's done by David Sparks and Steven Hackett.

David is a former attorney. When I say former attorney, he just quit his law practice as of the end of last year after 25 years, I get the number right. And he's a content creator, okay. For Max Sparky, which is also a great site to look at for Max stuff, but you, you know, they don't talk about like Max and law, they talk about Max and everything that you could possibly use it for, and they talk to different types of creators and users, whether it's photography, Programming.

Uh, think they've done a lawyer one yet. I, I, I kind of pitched myself to them once, uh, you know, yeah. Actually have a lawyer on, but you, you learn a lot by osmosis. Some of it's a little bit over your head. Some of it's, you know, obvious, some of it's like, I never knew that. And it's just a really great, uh, podcast to listen to.

The other I'm gonna recommend is mac rumors.com. That's not a podcast, it's a site. Okay? And they're really good at the development cycle of different Apple products, iPhones, iPads, computers, the heart, you know, the, uh, the, the headphones. AirPods, which is where air were, airs the AirPods and it gives you a good time of like, you know, buy now mid cycle or wait something new is coming.

So Oh, that's interesting. I use that a lot when I'm upgrading, uh, my hardware for the office. and for the, the, the blog as well. I gotta end up getting a max studio with an M one Alto chip that is this blazing fast. And wow, since I'm trying to get into more content creation in my night job, it's been a great resource.

So tho those are my, uh, my three friendly suggestions. You said you have a dual screen. Do you, so do you have two different monitors and the laptop? I do. I

do. I send, it's a bit overboard. No, it's not. No. You don't really like the space. I really

like it. Yes. Yes. So wait, how big is your, your laptop? Uh, is it 14 inch?

12 inch? 16 inch.

Uh, it's 15, I think.

Does that make sense? Yes. So the, the MacBook Pro has 16 inch right now. Okay. So you might find the It's what I have when I travel. Yeah. The Mac Studio. Sometimes

the heavy gets me. It's not,

I mean, I don't know, you know, I know a lot of people like to travel with like a MacBook Air.

because, you know, they're light, they're a pound or two. It, but this is maybe four, four to five pounds. And I, I don't, I personally don't have a problem. But then again, when I travel, I either use my wheely travel bag that ideally fits under the seat in front of me on the airplane. Okay. Or I have a weight balancing backpack, but I, I prefer the wheelie typically.

Cause you know, the back who needs that? I do know that. So tell me who makes your dual screens.

The dual screens are

lg. Okay. They are, well, they are the unofficial apple screens. I think that's how they, the are made. And since I got into to content creation, I also got an Apple xdr, you know, the expense of $6,000 32 inch screen.

Ooh. Those were pretty. They're very pretty. I've got that in front of me and then I've got two lgs two four Ks in front of me left and right. Oh wow. So you do a big Yes. Yes. And I'm having fun with it. Trust me. So, uh, anything special about the mouse? You said it was a track pad? Is it the, uh, apple

track pack?

Oh, actually don't do a track pad. I do an a, a physical cordless mouse and physical. They're both Mac and. Keyboard

as well. Now, uh, do you have the keyboard with the, actually, I guess you don't have the keyboard with I don't, I have fingerprint. I have a tiny one. Oh, ok. So, yeah. Whoops. You got the time. Well, they do make the, they do make the fingerprint ID on Apple keyboards for, for the short ones as well.

Oh, that's

so cool. I didn't know that. You teach me all kinds of new things. .

Oh, serious. Well, I mean that's what blog's all. The podcast. So, but you have to have an M one chip and this is really constant, handy. And when I was, when I first graduated high school, I had a job, a part-time job. For a couple days I was an office temp because long story short, you know, I just was in able to find a job.

Um, but they kept me busy. And because I knew how to use a computer and I knew how to type, they kept me very. and I taught myself numerically. Really, and it's, it comes in really handy when you have to put in certain data. Absolutely, yes. Let's actually use it. But I tell you, apple keyboard. Mm-hmm. new laptop, computer.

Yep. Just don't send me your bill. Is there anything else in your office that you might like to share with the audience?

Let's see. The, the desk is a standup

desk. Okay.

Now I don't use it standing up as much as I should. Mm-hmm. , but I like having the option too.

Yeah. What, so do you have like a, like what kind of chair do you have?

I

think they're all, um, like autonomous or something like that.

Dunno that brand. Yeah. Several years back I invested in a, a Carbon Miller chair. Ooh. Yeah. Uh, the investment,

that's a, that's a natural

investment and it was worthwhile. I, my wife and I went to a Airbnb during Covid cause we were really just, you know, tired of just being at home and I was working at the kitchen table all week while we were down.

And it was a wooden chair. And every day when I kind of stood up and whatever, I was like, oh my God, I can really feel the difference between the two chairs. Yep. Um, but it's, it's a worthwhile investment. So that all being said, let's get into the questions. Sure. Aside from Trellis, What are three AIS attorneys should be using in their work today and why?

Well, I think it's gonna

depend on the, the particular practice area, the particular type of work that an attorney does. But I generally, since I was a litigator, think about things from a sort of litigator's perspective. So one, I would say hands down, you need to be utilizing AI for in tools for your e-discovery.

That's just a must have. Should not be doing discovery reviews by hand or one by one in documents. Even if you go, well one by one, allowing yourself to sort of, The computer to aid when you could key in on documents that might be important or that are similar to something else that you're looking at. So e-discovery for sure.

I think some of the, the one, the platforms where you can load up trial briefs. Mm-hmm. and it will scan the case law for you and bring up recommended. And I think that's really interesting. I think that it's something you you'd wanna watch and you'd wanna, you. Look at the cases and make sure, but I think it could really save you time depending on the, the platform.

I think for, for any sort of contract management. There's a lot out there now that's come a long way, but that again, is gonna depend specific to sort of what you're, what you're doing, what, what contracts you need to be drafting. How many, what volume and then what provisions and all that. So I think there's some really good AI contract management, um,

platforms out there as well.

Recommendations for each category. Suspension. Ooh,

let's see. Uh, for e-discovery, I think disco does some great stuff. I haven't been, oh, uh, logical, I think does good work. I'm not heavily into it anymore, but I know those two and I know that they're doing some really interesting, uh, work and I've used both relatively recently and, and can, uh, vouch for both.

I think that, uh, case texts, uh, would be an example for Cara. Which is the sort of load up a brief and it will analyze the case law within there. And I thought that actually Lexus or Westlaw just built out something that's competitive to that. Lexi Lexus

did. Lexus did. I'm not sure about Westlaw, but I, I'm a Alexis Ryer and I, I've tried to use it a couple times.

I Y'all have an opinion yet? I, okay. The one time I remembered to use it, it was, it was a very short something that I wrote and it had like maybe two case law references. I didn't have enough case law references to make any suggestions. I'm like,

Interesting. Yeah, so it's always, it's always the interesting thing is at the moment that you try out new technology, is your use case going to be the one that sort of matches what the functionality of the platform can?

Right.

Yeah, no, it's can be luck there. It's just, it was just a little, little frustrating at the time, but it was easy to use and you know, when I have, it depends on the type of brief I'm submitting cuz a lot of the briefs I submit are usually to agencies. In particularly the Department of Veterans Affairs that don't necessarily need extensive research back because the common cases are usually the same and nothing's been updated in for a while.

Yes, that makes sense.

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Thanks again and enjoy. Anything for contract

management. There's a bunch out there. I'm not gonna be able to vent personally, but I know some of the founders are doing interesting work. Mm-hmm. , I think Kira sold recently doing a lot. I have to think on it more, but I did just think of one other area, which is interesting, which was.

Again, from a litigator's perspective, but for table of authorities, table of contents. Yep. To be able to generate those automatically, I think is a huge time saver for attorneys. Uh, and I think clear brief is one that does that

well. Can, I mean, what's wrong with using Microsoft Word? Maybe I'm missing a point that you don't have

to, you don't have to do it.

It does it for you. So it basically pulls out and then automatically sites to the actual portions of the exhibit. That you're citing to, or the portions of the cases. So it just takes away some of the work that you have to do, creating a head. No, not the head of the actual table, the table of authority. So citing to the facts.

Oh, okay.

Oh, the case is, okay. The case, I

dunno why citing to exhibit saying to a particular case law. And the interesting thing there is that it can actually, it will, it will attach to it all of your citations. So the actual cases, or if it's fact statements, the depositions, or whatever the case may be.

Okay. Okay. And just make it super simple for the judge to be able to look directly and confirm that it is what you say it is. ,

uh, Of course, if you have a problem where the judge has to check your work, uh, that could be a problem. , you got that reputation. Well, I'm excited there. Although I, and you know, it's funny, my clerks have, I was like, why do I have to check case law?

I mean, it's cited. I'm like, because trust me, I've done it myself where I've seen other attorneys cite to something and it either be not what they say or just, oh, it says completely wrong. And Absolut. I and I was like, first thing you gotta do is check their case log cuz if something's not quite right and mind you, I tend to go against the government.

Okay, interesting. So I'm not saying that they're being deceitful, just sometimes they can be lazy. I wasn't

gonna say it. I'm glad you said it and not mean, but Well since,

since I sue the government, you know, I could. I could say that, yes. Excellent. Yes. So let's move into question two. What are three things Trellis does better due to its use of AI than its competition?

Well, in general, what we do is we're a state trial court data and analytics platform. So think of Lexus and WEX Law as being your sort of court of appeals research. Mm-hmm. , we do the same thing on the state trial court side. So aggregate. Separate individual county courts where you'd otherwise have to go onto county court website and make it searchable across counties, across states, from a single interface.

So on the one hand, the um, basically the pure ability to have the data and coverage that we have is due to our technology and this scalable ability to bring on so much data. And the reason that we're able to do it and what makes us better is because. , when you think about it, if you think about going onto a, a county court website to, uh, look up a case, well, every county does it differently, right?

So you're gonna have a personal injury case type is going to be said a thousand different ways. And every county that says it, they'll call it PI or personal injury or PI plus 25 or whatever the case may be. So part of what we need to do with all of this messy, raw, unstructured data is really create that s.

And that's something that a human really wouldn't be able to do. Um, so we figure out, classify this data, which allows us to structure it, which then allows us to use algorithms to predict information. So really it's the classification of the data, it's the normalization classification and sort of understanding and the ability to deduce meaning out of the data because it's other.

Just unstructured and unuseful in its current state. All right, well, that's one. Two more. Okay, two more. Uh, specific to ai, I think it's the, the search algorithm itself. Mm-hmm. , right? Mm-hmm. pulling up relevant information, and that's an interesting one because that's one where you can actually continuously tweak to raise better and better results as you.

Watch what people are searching. Watch. Mm-hmm. , what pages they stay on, recommendations. So there's a lot of really interesting work that we do to. Make sure that search results are relevant and that you can find information and highlight information, because I think I would say like one of the things that attorneys struggle with is actually just too much information.

It it's, mm-hmm. , there's that, it's difficult sometimes to determine what's actually gonna be the best use of your time, and so how can you bring result? Kind of like Google, right? You want the result that you want to come up in the first three things that you click into. And so how do you make that better to save attorney's

time?

Well, let, let me ask you this. So for your search criteria, is it sort of like a bowling kind of search? Uh, it is path

that you create. It's natural language and boo. Okay. So, okay. Um, basic bullion, everything that you're used to. One sort of Lexus and Westlaw, but combined a lot more with natural language.

So what you might really, I I like to describe the way you search on Google would be very similar to the way you search on Trellis. Westlawn Next is another example. Right? Okay.

No, excellent. It just 1, 1, 1 to have an idea of the field. How you have to do the search terms versus, you know, some sort of complicated or semi uncomplicated, you know, language that the user would have to learn.

And it's good to hear that they don't have to do that with, uh, trellis Such it's,

it's

very, very true. Yes. Um, the, in fact it's sort of a, a goal here that, you know, if you know how to use Google, then you're gonna be able to know how to use. We know how difficult it is for people to take time training themselves on new technology.

So we always work to try to be better and be more intuitive and, and get people to

results faster. Well, not just just the time, but also the fear. Fear. Tell me more the, what do you, well, I mean cuz people were like, they're used to doing. Something the way they've always used to do it. Attorneys are the worst that comes to that.

Dana, you know, it is very true. What is, yes. What is this Researching and online stuff? I, I don't know, comfortable with that here. Yeah. You know, or, or typing your own, you know, your own briefs. Yeah. I mean, You know who has a secretary anymore. But it's true. You know, it's, I think that puts way there. Fear of having to learn something new in the sense of having to learn how to utilize the product.

Yep. Makes because that creates, cuz that creates hesitation and that's not good for you because you want them as a new client. Absolutely.

Anything to lower the barrier . So number three. Number three, uh, number three I'd say are, are judge analytics. So part of what we do in gathering all of the state trial court data is provide analytics on specifically how state trial court judges rule.

Mm-hmm. . And we go across a, a whole variety of sort of surfacing information on state trial court judges from how many active cases they have to the outcome of their cases by case. All the way down to really granular information like how they rule on specific pretrial motions. And that is absolutely in a large part to our, our ML team that constantly works there.

And then of course we have humans check it over. Um, because there, there, it always, there always is. Um, the machine can sort of get you 80, 90% of the way and then the human will help to continue to make it better.

Wait, I'm sorry. Could you explain this concept to me? What, what's a human, I'm still working on

that one.

It's a lifelong myth. Third journey to figure out

do they still exist? Who then would you recommend to, to find this kind of information, this type of database? When it comes to federal courts?

I would say on the federal court side, one, the, the nice thing is that it's structured data. . So anyone who is layering analytics on top of it is going to have an easy time to begin with because they start with pacer, which is one unified instruction data set.

I think Lex Monet does a great job on the, on the ip on the federal side. Mm-hmm. , I know that Lexus acquired a few people at Lex, Monet being one of them. I think RL earlier, uh, was doing that as well. I'm trying to think who else, uh, does judicial analytics on the federal side? Um, cause

I've seen nobody, am I missing someone?

I, I mean, you know, cause I'm thinking about like my Lexus use and they don't go that deep when it comes to different judges in particular cases, et cetera. Unless I'm missing something. Uh, mind you, my work typical doesn't go in that direction, but it would help. Yeah. That's on

the federal side too. You don't see them?

No. On the

federal side. I just, I'm not familiar with anything. Any programs similar to Trellis. Yep. You know, maybe there's a hint for you to consider expanding pellis to state versus federal. Um, Interesting. But, but, um, I, I, I won't, you know, earlier, I guess I was giving you ways to spend more money. Um, this would obvious be a larger investment.

So I, I don't wanna be accused of anything, um, but I, we totally plan

on, on rolling out in the federal space. I think the idea first is to take over the state trial court space where there's never been a, a single, searchable platform to begin with. Mm-hmm. , um, with the idea that maybe there were a lot of other players in the federal side, certainly providing.

But it's really interesting here that you don't think there's a, a great solution doing federal judicial analytics right now. Well,

I, maybe you misheard me. I don't think there's any, I love it. Not just a, not just a great, but there seems to be like a nice, uh, Platform for you to consider entering

intel.

All right. That's awesome. I I like that. That's interesting.

So for our third question and our last question, what are three things about AI you think attorneys should be keeping an eye out in the future in

general? I think that we're, we're at a good place where, um, there's a lot of good data being collected that will allow just a, a ton of analytics in the future.

We. We're not there yet. We are. It's, they're cleansed, normalized data sets. Uh, but I think that we're getting closer. What I would say is almost in, in the way for, for instance, We're working on lawyer and law firm analytics. So think of the way that we do judge analytics right now, but the ability to look at your opposing counsel, see all of their cases, how many of them do they settle?

How many do they take the trial, how many do they win? Summary judgment motions, do they not write really deep diving in both individual lawyers, but also law firms in general. So that's just sort of one piece of, uh, imagine. A world where you're going to be able to have insights across the board, both in, in your own work, but also competitive intel on the, the folks that are your opponents as well.

So I think that's a really exciting thing that's coming. And generally just the ability to, almost, almost everything that we're utilizing is collecting data on. At some point, some of this data, now a lot of it's obviously being sold because we're the product, but there's a lot of ways that this data can actually help us to make better products and can provide information back to us to work more efficiently.

And so I'd say that's something that I, I really think is coming as we move

forward. Well, that's one. Any other areas you think that we should be keeping an eye out for? I think

in general you wanna think about ethics, right? There's a, there's a lot of questions now. I think AI has got a long way to go, um, before these become real questions.

Right now they're kind of philosophical questions. Okay. Which are, is there something unethical about having an algorithm pro highlight certain case law to you? Um, an algorithm bring up sort of whether predicting whether you might win or lose. Is there information that might be surfaced to some people that isn't surfaced to.

I think there's a lot of interesting sort of philosophical questions there about whether kind of how much power we give algorithms to even, even, I take Google as an example. Mm-hmm. . We're only shown the information that we shown. Right. There's, there's an ethical question there about is it really an even planning field?

What are the different, different information that's being surfaced to different people? I think those are things to think about. I don't think that we're at a place right now where we need to do anything other than talk about it, keep an eye on it in

general. But still in the end, isn't it the attorney that makes the final decision that they use, the information they get from the algorithm and whether or not they need to figure out whether to investigate more or if this is the proper source or some other third consideration?

I, I guess in my mind, I can't understand why it would be unfair for an attorney to use. Particular program or particular algorithm or use Google versus Yahoo? Yeah. When all of it is accessible. Now for some of it, obviously you may have to pay for it. Resources are a question. Sure, right. Which, but you know, unfortunately, we're in a capital society that.

if you can pay for or use it. Yep. But, you know, and then of course that goes back to whether or not, well, what about the lower economic individuals who can't afford, you know, the attorney, let alone, uh, access to a database, let alone understand how to use it because of the lack of education, which of course, uh, you know, we could, those could go into a variety of different ways in our discussion.

Mm-hmm. on that issue, but let's move on to yet one more, to answer One more. I'm gonna pull 'em out here.

Okay. Uh, data analytics in general.

Um, or, or, yeah. Any AI or the interpretation of, you know, whether it be, you know, AI in your writing. Ai that's

one right now. Uh, I'm sorry. Just that, that's a huge one right now so we can talk about it.

Uh, please. Of content creation. So AI sort of generative content is something that is getting a, a. Uh, interest right now. I think it could be an interesting piece where one of the things you're, you, you create content, um, content is mm-hmm. formative. You feed a business right, and getting full, and it can be lead generation and can help to establish yourself as an expert.

I do think that more as it, as it gets better, and it looks like it's getting much better, that people will be able to utilize AI to generate. Content so that it's not only them, which will, now you're relying on the internet, right? On everything that, the internet that has been sort of, uh, swallowed up there.

But there is a lot of legal information on the internet. And conceivably you could have basic drafts of things created and then a lawyer continued to review and say, yes, I wanna put my name on that, right? No, I'm gonna do this. Right. And I think, There's, there's good and bad to that. I think anything that saves attorneys time where it's actually going to help the client, um, or they're utilizing it to bring in clients where then they can do the work for them, I think that will be a benefit.

But, but it still comes down to, in the end, the attorney has to review what are the draft, maybe what are the research has. Yes. Uh, whatever is going out, you know, it still comes down to the attorneys signing off on that

document. I'm of the belief that that will always be the case. Some people believe that attorneys will be taken out of the equation.

I do not believe that for a second. I, I definitely believe better tools. We will all continue to have better tools, but I do not think that there will be a full scale replacement of attorneys. Better tools to continue to advocate. Now I think some areas of law are a little more susceptible to automation than others.

Um, but I don't see a universe where the attorney is, is taken out of the

loop. I, I agree with you, but then again, I may be a little biased. I am an attorney. I, we,

we all may be biased ,

so no one could repeat us. You know, we, we shall see what happens. Yep. Well, Nicole, I want to thank you for joining us. Tell us where can people find you?

Absolutely. So they can learn more about Trellis at Trellis, do law slash Search and they can just get on and start searching for Urban Button stuff. Um, you can find me on, uh, LinkedIn at nicole underscore a underscore, and also on Twitter at the scene.

Excellent. Well, Nicole, again, I want to thank you for joining us and you have a great day.

Awesome. Thanks so much. Great being. Thank you for joining me on this episode of the Tech Savvy lawyer.page podcast. Our next episode will be posted in about two weeks. If you have any ideas about a future episode, please contact me at Michael DJ at the Tech Savvy lawyer.page. Have a great day and happy Lori.