TrialView, an AI startup focused on litigation management, has raised $4.1m in a funding round led by Elkstone Ventures. It follows several years of bootstrapping while they grew the business under their own steam. (See In-depth AL Interview below with CEO, Stephen Dowling.)
Since its founding, TrialView has been primarily self-funded and has grown to almost $3m ARR in the last 3 years. Unusually for a tech start-up, they noted, the business has also been profitable to date, which has enabled expansion across the UK, Continental Europe and the Middle East. The additional funding will enable TrialView to focus on new markets including the US, Singapore and Australia, they added.
The funding will also substantially increase the business’s headcount, with plans for new hires across its development, sales, and customer success teams.
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Legal Innovators UK starts tomorrow with Law Firm Day on Nov 4th, then Inhouse Day, on the 5th, and then our new Litigation Day on the 6th.
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They’ve already had some notable success, and 15 of the top 20 law firms in the UK have used the technology, which helps with a range of case management and handling needs from analysing and tagging written evidence, to drafting, to the creation of timelines, and much more – (see TrialView here )
Below is an In-depth interview with Dowling, Founder and CEO of TrialView, but he added the following comment with the announcement: ‘This investment is a significant milestone for TrialView. It helps us promote our vision of helping litigators serve their clients through more effective case preparation. Our platform is more than an AI tool – it’s a partner for disputes teams through the life cycle of a case.
‘We are thrilled to partner with Elkstone Ventures, who share our commitment to innovation and growth. This funding will allow us to accelerate the development of our AI-driven features, expand our team, and establish a stronger presence in key markets, including the US.’
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In-depth AL Interview with CEO, Stephen Dowling.
(Transcript by AI)
Richard Tromans
First of all, tell us about the investment.
Stephen Dowling SC (00:41.581)
Yeah, so we just raised close to $4.1 million in investment. The investment has been led by Elkstone Venture Capital. It’s an investment which is primarily defined as a growth round for us. We are a company which has been growing quite well over the last four to five years. And this round is basically designed for us to allow us to grow into new markets, particularly the US.
Richard Tromans (01:07.982)
When you say it’s a growth round, mean it’s a seed round, it’s an A round, what is it?
Stephen Dowling SC (01:12.099)
Well, we’re in an unusual position in that we’re we are a company who’s at this stage profitable after four years since inception. We’re currently approaching about three million ARR. And so for this round is we would be usually in series A territory, but unusually for a tech company of our nature, we’re being profitable.
So we’re defining this as a growth round as opposed to a seed round or a series A round. But in truth, the companies reached around series A land.
Richard Tromans (01:44.525)
And you said the money is going to be used for expanding in the US, did you say?
Stephen Dowling SC (02:09.549)
Yeah, there’s two things. Firstly, AI is expensive and we have been heavily focused on AI engineering over the last year and a half, two years, but we want to significantly increase our spend on that and also to focus on products and areas which are going to leverage both the UK market, which we focus on heavily, but also the US. So part of the money will be into the engineering aspect of it. But secondly, it be into exploring and breaking into new markets, new territorial markets.
Richard Tromans (02:39.48)
Gotcha. And if people don’t know, if you could just explain to the audience generally what is TrialView all about? What are you providing?
Stephen Dowling SC (02:54.607)
So Trialview is legal tech, but it’s legal tech focused exclusively on disputes and dispute resolution. Its primary challenge or focus is the challenge of enabling lawyers to much more effectively prepare their cases for hearings and for trial. And by that we mean really the challenge of navigating through very large volumes of documents, being able to streamline evidence presentation, being able to surface relevant and critical evidence over a vast data set and being able to comply with quite rigorous workflows, standards and guidelines when it comes to marshaling your evidence for trial. And in addition to all of that, we facilitate digital trials as well. We facilitate lawyers being able to run their hearings entirely digitally from start to finish, and that brings with it a lot of the advantages of having access to evidence very, very quickly when you’re in the clen and thrust of an actual live trial.
Richard Tromans (03:58.094)
And is that how you started? it that kind of COVID era? Hey, we were all going to stay at home, but we’ve got to run this court case digitally. And then you added the AI bits as you went along. I how, did trial view come into existence? Well, you were just in the bar one day and you just thought link.
Stephen Dowling SC (04:12.674)
I was sitting in a courtroom one day, drowning in paper and documentation as a relatively senior junior counsel barrister in a very large construction case. And I was essentially watching all the lawyers and participating in basically handing up paper evidence to the judge in a case where there probably was hundreds of thousands of documents.
And I said to myself, this is absolutely unsustainable. Forget about the environmental cost and the legal cost. It’s going to basically damage all of our health, our psychological well-being if we don’t sort this out. So primarily, the original focus is on the logistical challenge of marshaling digital data in the trial itself. The actual complexity of pulling together material digitally and serving that up to a judge and ensuring that all the parties are coordinated with respect to that digital data is quite a complex process, far more complex than people will realize, mainly because you’re trying to keep everybody on the same page and coordinated in an environment where they’re otherwise at war. So that was the first challenge we tried to address at TrialView. And we started that pre-COVID. So we started essentially in 2019 with a very, very large piece of litigation in the Dublin commercial court.
And we did it as a kind of once-off pilot case, which turned out to be very successful. And from there, we expanded out based on that specific case. We expanded the same system out across multiple cases. And by the time COVID came along, we already were up and running with a very sophisticated trial presentation and management system. And then COVID hit, and that completely changed everything, because suddenly everybody needed to go digital for trials. So we are
Richard Tromans (06:05.598)
Covid really helped you in some ways.
Stephen Dowling SC (06:07.959)
It did actually, yeah. COVID has had mixed fortunes for many people, but for us it had good fortunes. We found ourselves in a world where lawyers suddenly had to collaborate in a remote environment and then actually present their trial, present the evidence in a remote environment. So for us that was a big boon and it allowed us to be profitable. We started seeing significant growth in the UK during and after COVID, and it allows us to explore other aspects which included being able to manage the data and documentation at an earlier stage in the litigation, at the disclosure stage, at the witness statement preparation stage and at the pre-trial submission stage.
Richard Tromans (06:53.112)
Gotcha. And on the AI bit, I mean, you know, these days everyone just assumes, okay, so you’re tapping into Anthropic, you’re tapping into OpenAI, but just a little bit of detail there. what AI skills are you using and where are they coming from?
Stephen Dowling SC (07:09.871)
So the biggest problem I think lawyers face in AI at the moment is volume. That actually is a, I think, widely underestimated problem when it comes to using AI. At the moment, most people have access to the models. The LLM models are freely available. You can access them on a private basis using, for example, ChatGPT Pro. And those models are very, powerful. What we deliver or we bring to the table is the facility to use those models in the context of very large volumes of data. The problem with those models is they have a limited context window. That context window can actually, for any kind of normal use case, be relatively large. It could be thousands of pages. But when it comes to legal and particularly litigation, thousands of pages doesn’t cut it. You need to be examining documentation up to millions of pages. Therefore, what we facilitate
Richard Tromans (08:04.826)
And just for the audience who are not experts in litigation who may be reading this, we’re not talking about e-discovery here, we’re just literally talking about case preparation, case management.
Stephen Dowling SC (08:15.737)
Yeah, we are. Just to be very clear, what’s happened now in the world of eDiscovery is parties come together, they have to exchange what’s called quote unquote relevant documents, which are relevant to the issues in the case. But relevance is a very broad concept. And you could have literally tens of millions of relevant documents that touch upon the issues in the case. Now that would have been a big case, but that does happen. That’s it.
Richard Tromans (08:40.386)
But this is just to clarify for the audience, this is, when you say relevance, we’re talking about e-disclosure in the UK or Europe, or this is separate from why the US does it.
Stephen Dowling SC (08:51.373)
No, the US does it this way as well, although they have different systems relating to depositions. in the common law world in particular, and also the US, is form of a common law jurisdiction, they are required to disclose documents which are quote, relevant unquote to the case. But that has a broad meaning relevance. And these days with digital data, the document pool can be extraordinarily large.
Richard Tromans (09:19.758)
But isn’t that eDiscovery?
Stephen Dowling SC (09:24.389)
It is easy to ‘discover’, but my point is this. You’ve now discovered the quote relevant documents, but you’re still talking at that stage, tens of thousands, hundreds of thousands of documents, which are now relevant to the case. But now you have to sift through the relevant material to find the material that you’re going to use to make your case. And there’s a difference between finding documents that are relevant and finding documents that are going to persuade the judge or the decision maker that your client’s case is right or the opponent’s
Richard Tromans (09:52.334)
And that’s where you come in. You’re the bit that comes in after the e-disclosure, e-discovery?
Stephen Dowling SC (09:58.31)
Correct, yeah. And the reason why we’re seeing an uptick in that space is because the body of documents that are now moving into the case preparation space is growing exponentially. And lawyers and senior lawyers now need the ability to use a system which is intuitive, which speaks their language and allows them to navigate very large volumes of documents.
Richard Tromans (10:23.244)
That’s interesting. So, it’s interesting. So, yeah, so basically as, so like you might say, like, you know, a decade ago, you perhaps wouldn’t have been so useful, but as, as that volume increases, and as you say, you know, it’s just going to get more and more with, you know, Slack channels, you know, not to mention emails and every text messages and everything else. Yeah, exactly. Even what’s left over is still going to be gigantic.
Stephen Dowling SC (10:46.853)
It’s still gigantic. when we just did, we finished out the Russian aviation litigation, which was a six billion claim where a huge amount of those documents that were relevant actually were containing WhatsApp messages, containing essentially dealings between parties on WhatsApp. And the everything now that you can imagine in a piece of complex commercial litigation or construction litigation or employment litigation, all of the communications.
all of the interactions are being recorded in some form digitally. Even now, the meetings, this meeting we’re having now has been recorded digitally using AI. There’ll be a transcript, there’ll be an AI summary of that. And essentially all of the evidence that we’re now going to be sifting through is going to be held digitally. And you need senior lawyers who maybe not have been in the past very tech-versed or very kind of well-equipped with technology. They need to be able to handle this, to manage this, analyze this pre-trial and during the trial itself. So you need a tool that’s going to speak their language.
Richard Tromans (11:49.966)
And so how do you get around the context window issue? I mean, the devil’s advocates out there will say, well, hold on a minute. Why don’t I just jam this into an enterprise version of ChatGPT?
Stephen Dowling SC (12:02.702)
Yeah, if you do that, still won’t get the engineering that we would do because JotGPT doesn’t necessarily focus on this because it’s not in their wheelhouse. So there’s a great deal of architecture in place behind the scenes that allows the documents to be chunked up. have a…
Richard Tromans (12:21.934)
And actually, again, for the laypeople out there, what does chunking up mean, as opposed to because it’s a it’s a it’s term that could be confusing. But what does that mean to chunk up a document or?
Stephen Dowling SC (12:31.204)
Yeah, the simplest way I describe is you literally smash the documents into pieces. And those pieces essentially are extracts of text, like phrases or snippets of the text. Now, there’s different ways you can do that. Some ways are very sophisticated, other ways are less sophisticated. But we chunk them up in a particular way. And that means that it’s put into a particular database. And that database is marshalled and curated in a particular way that allows the user find relevant extracts that are going to match the question that has been asked or match the task which the user has inputted in. And within that, there’s lots of techniques that are employed, some are well known within the AI world, things like entity recognition, named entity strategies, using existing knowledge within the case to augment the search results that the users are
putting in and having a system that’s kind of collaborative between the AI and the human. So what we do is we, as people are working on our cases and as they’re adding information into the cases, as they’re, for example, tagging things up as being relevant or as being important for a particular issue, that information gets stored back in the system and can be reused then to find other information which is similar to that information being put in, but previously by the humans. So the system actually gets, it’s not training on us, but it gets smarter by reference to all this extra information that humans are putting into the system. And that really helps at the case preparation stage, because you usually have a group of lawyers who are analyzing the documentation, finding what they think is important. And then when they find that, that same information can be used again to find other similar material, which is important.
Richard Tromans (14:19.182)
Gotcha, so yeah, it’s kind of like son of TAR. TAR had a love child and it’s called Trial View.
Stephen Dowling SC (14:29.818)
Yeah, there you go. That’s a fantastic tagline. And TAR, I mean, the interesting thing TAR is that TAR was relatively successful, but with the AI, GenAI based approach to documentation is far more powerful. Also, clients are expecting that this is used, whereas TAR was absolutely obscure when it came to clients. Clients would never really be aware of it unless it was specifically brought to their attention.
Richard Tromans (14:32.417)
Yes
Stephen Dowling SC (14:59.13)
With AI now, clients are demanding that it’s being used because they’re well aware.
Richard Tromans (15:01.678)
because they’re well aware, because they’ve probably dabbled by dumping a few documents into ChatGPT and seeing what can happen. And now they’re like, hold on a minute.
Stephen Dowling SC (15:11.203)
Exactly, exactly.
Richard Tromans (15:13.158)
So looking forward then, so where does it, so you’ve got some money, you want to expand to the US, you’ve kind of got a broad sort of tech objective. I mean, where do you go from here then? What’s the next couple of years got to install for you?
Stephen Dowling SC (15:26.372)
Yeah, well, mean, for us, our focus is on the litigation community. So for us, that’s a very specific community within Legal Tech. It’s a very interesting area because it’s its own network, essentially. So unlike the other AI companies out there who have been very successful in attracting all aspects of the legal spectrum from non-contentious work to the contentious work, our focus is very much in the contentious workspace.
We’re releasing features that facilitate not only litigation lawyers, but also facilitate judges, facilitate help arbitrators, help expert witnesses that brings that community together. And our focus is essentially on creating the system which hopefully will become the standard when it comes to case preparation and evidence presentation. And one of the really interesting areas is in addition to developments in e-disclosure,
We’re also focusing on things like early case assessment, the ability for parties to analyze their documents at a very, very early stage to get a really good sense of the likely outcome of their litigation. And because we’re experts in what happens at trial and what happens at the end of the trial, we have a pretty good perspective as to how a case is going to turn out if we’re given the right information. So whilst it’s not…
Richard Tromans (16:51.551)
Getting into that case prediction type.
Stephen Dowling SC (16:53.624)
Yeah, it’s that space, but focused on the evidence, using the evidence that exists to get a very much better sense of where the case is going, rather than a kind of a high-level opinion which isn’t rooted in the likely facts as they’re going to emerge at trial.
Thank you and good luck with your continued growth!
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(Main pic of top team: Stephen Dowling SC, CEO & Founder, Frank Brooks CTO, Eimear McCann, Commercial Director.)
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