This week we sit down with Matt Rasmussen, Founder and CEO of ModeOne, to dive into the evolving challenges and solutions around mobile device discovery. What started as a frustration-fueled “passion project” has grown into a powerful, cloud-based legal tech tool that dramatically speeds up mobile data collections while safeguarding user privacy. Rasmussen brings over two decades of litigation tech experience, and his team is focused on automating the traditionally slow, invasive, and expensive process of mobile forensic collection.
Matt shares the lightbulb moment that led to ModeOne’s founding—after nearly being hit with a book by an executive unwilling to hand over their entire phone during an M&A data collection. That experience crystallized a need for a targeted, remote, and custodian-friendly solution. ModeOne’s approach allows for precise data extraction, filtering out personal messages, and narrowing collection to relevant participants or timeframes—thereby reducing friction, legal risk, and cost. The tool shrinks a two-week process into a matter of hours and removes the need for shipping hardware or dispatching personnel.
The conversation then turns to the power of cloud scalability and how ModeOne’s architecture enables parallel processing of hundreds of phones simultaneously without ballooning costs. Matt recounts a case involving over 400 phones processed in just two weeks—compared to the seven-month timeline it would’ve required using traditional methods. He explains how operating directly on devices with lightweight agents and leveraging cloud resources allows them to outperform older queue-based systems and ensure defensibility through record-level audits.
Beyond litigation, the use cases for ModeOne are growing fast, particularly in corporate compliance and legal holds. With recent updates from the DOJ and FTC increasing expectations for mobile data preservation, companies are now compelled to treat phones with the same seriousness as emails and cloud documents. ModeOne’s ability to preserve data in a scalable, minimally invasive way makes it a key player in this regulatory shift. Rasmussen also highlights that while AI may not be the focus of this episode, ModeOne is quietly integrating features like sentiment analysis, emoji flagging, and communication mapping through a partnership with StreamView.
As the episode wraps up, Rasmussen discusses the startup journey—from bootstrapping to being named Legal Tech Startup of the Year in 2024. While initial adoption faced the usual “wait-and-see” mentality common in legal tech, ModeOne is now working with several Fortune 10 companies, AMLaw 25 firms, and leading LSPs. Looking forward, Rasmussen predicts mobile data will only grow more central to investigations and legal matters. With privacy and policy changes ahead, ModeOne is doubling down on mobile—not diversifying away from it. As he puts it: “We’re digging deep on phones.”
Listen on mobile platforms: Apple Podcasts | Spotify | YouTube
[Special Thanks to Legal Technology Hub for their sponsoring this episode.]
Blue Sky: @geeklawblog.com @marlgeb
Email: geekinreviewpodcast@gmail.com
Music: Jerry David DeCicca
Transcript:
Greg Lambert (00:00)
Hi, I’m Greg Lambert with Geek in Review and I’m here with Nikki Shaver. Nikki, we were talking about deal intelligence. Can you tell us a little bit more about that?
Nikki Shaver (00:09)
Yeah, absolutely. Hi, Greg One of the hot areas for legal tech over the past year has been deal intelligence. We’re seeing in the market that large firms are typically buying into both broad legal AI assistance and also point solutions. And they will typically buy point solutions in areas that are particular priorities for them. Deal intelligence is one of those categories where we’ve seen consistent interest from firms
in spending extra on a point solution. And the reason it’s important for firms is twofold. First, it’s a problem that firms have been trying to solve for some time. Extracting data from contracts at scale wasn’t really feasible previously without training a tool or using one with a lot of pre-trained provisions, and the accuracy just wasn’t really that great. It’s much better now. Second, once you’ve extracted data points, you can do a lot of different things with them. You can profile matters,
which is useful for pitches and proposals, but also to bolster the ability for lawyers to be able to meaningfully search for things like past precedents in similar matters. You can also build What’s Market databases, which is an essential negotiation and advisory tool for corporate and transactional lawyers, and use the extracted data to inform various other knowledge tools or build knowledge tools.
So as a result, we’ve seen a lot of new providers in this space like Centauri, Hebia, Ivo, and Noetica. We’ve also seen the AI legal assistant providers like Harvey and Legora build out similar capabilities. So we think this is a really interesting space to watch. Will it be necessary in the future for firms to still invest in one of these separate point solutions or will development and the broader tools catch up to those point solutions so that firms no longer need
the additional license. Stay tuned to developments in that space. And for more analysis on the market, visit us at LegalTechnologyHub.com. Thanks, Greg. Exactly right.
Greg Lambert (02:10)
All right, knowledge is power, so thanks.
Marlene Gebauer (02:22)
Welcome to The Geek in Review, the podcast focused on innovative and creative ideas in the legal industry. I’m Marlene Gabauer.
Greg Lambert (02:29)
And I’m Greg Lambert and this week we are diving into the world of mobile device discovery with Matt Rasmussen who we met at Legal Week this year. Matt is the founder and CEO of ModeOne.
Marlene Gebauer (02:40)
Mm-hmm.
Matt Rasmussen (ModeOne) (02:44)
Hey, thanks for having me. It’s crazy to think that it was like six weeks ago that we were in New York. Time flew there.
Greg Lambert (02:48)
Yeah,
Marlene Gebauer (02:50)
It seems like a lifetime, right?
Greg Lambert (02:51)
time really goes by.
Matt Rasmussen (ModeOne) (02:52)
Yeah, for sure.
Marlene Gebauer (02:54)
So ModeOne is tackling the challenges of collecting data from smartphones for legal and investigative purposes, Matt, what you call the industry’s first automated, truly remote collection solution. now know you bring over two decades of experience in litigation technology, having worked with top law firms like a O’Melveny and Myers.
and fortune companies before founding ModeOne. So Matt, just want to say welcome and, you know, we’re, we’re glad you’re on the show and I don’t know who’s, who’s upset in the background, but tell them it’s okay. well I’d be, I’d be screaming for it too. If someone was making me pancakes. So
Matt Rasmussen (ModeOne) (03:27)
This is how we’re hearing him. Yeah. It’s pancake time. It’s Friday pancake day. ⁓
Greg Lambert (03:38)
Yeah,
if my dad was on a podcast instead of making me pancakes, I would be upset. So Matt, as we talked about, you spent years at big law firms like O’Melvany dealing with the e-discovery issues. So really I want to kind of jump right in and see what the light bulb moment was for you in.
investing your own savings and your own time into developing ModeOne is what you referred to when we talked as a passion project.
Matt Rasmussen (ModeOne) (04:11)
Sure. Yeah, I know it all was born out of self-preservation. I was just kind of, I was tired of being yelled at all the time that I was over collecting data from people’s phones. So I was the light bulb moment. The short story is I was handling a pretty major M&A deal and had a entertainment executive who had some texts on his phone that were client related. I needed to take them from him before he exited the company. And he almost literally threw the book at me.
when he found out that I needed to make a collection of his whole phone to take it back to the lab to then go find the specific thread I wanted. And so I just had realized I’d had that conversation over and over and over with my custodians in the past. And what are the things I need to do to make that better? So we dove in, I figured it out. And so I decided that was my calling, jumped into the deep end on the software side of things.
Greg Lambert (05:04)
Yeah, yeah, can imagine, I mean, it used to be that you literally had to take like everything in order to find the one or two things that you wanted, right?
Matt Rasmussen (ModeOne) (05:14)
Correct.
Yeah. And so that’s, mean, it was, that was, it was so nice to actually kind of figure that out. Cause like, as a, as a kind of a technologist by trade, right? I’m always looking for ways to make it faster, make it easier, make it less steps. And so being able to kind of solve that challenge was pretty, was pretty exciting.
Marlene Gebauer (05:33)
I know I’d be upset because you know, you’d have this whole collection of dad jokes that you’d have to go through if you were on my phone.
Greg Lambert (05:40)
That is true. I’ve seen her Facebook page. I’ve seen that.
Marlene Gebauer (05:46)
So traditional mobile forensic collections are often described as slow, expensive, and sometimes over $4,000 per phone. I had no idea. And invasive. So how does ModeOne specifically address those core challenges?
Matt Rasmussen (ModeOne) (05:57)
Yeah, no worries.
Yeah, so you know on the on the speed factor right there’s a lot of components if I needed to collect your phone Marlene as an example like I need physical access to the phone so I’m either shipping a person or a kit to where the phone’s going there’s lots of companies that will do phone swaps so I need Greg’s phone I’m going to send him a temporary phone he’s going to send me his real phone back so just like
Just in logistics gaining access to the phone, that takes days or weeks, right? And so people can’t be as actionable as they want. They can’t cross things off the list from like a data preservation issue. So that’s how we’re really kind of tackling the speed part. We can get connected in about 10 minutes. And so really kind of shrinking a two week process down to less than a couple hours has been great. And then the fact that we like being able to be targeted on these devices is super helpful for us to kind of
maintain the custodian’s data privacy, which is huge. Everyone wants the data that is super private to be maintained that way. But it’s also good because we’re able to reduce over retention and over collection from a corporate or business perspective. So that’s been great. And then on the expense side, you take a traditional workflow, you’re getting charged professional services and shipping, collection fees, processing fees, conversion fees to make it human readable.
And so that’s, like I said before, one of those things I always kind of looked at in my career is how do I shorten the amount of steps it takes me to get to the finish line? How can I automate a lot of those systems? And so being able to do that with cloud computing allows us to give flat fee kind of pricing and really kind of maintain a solid price point that’s not gonna be super expensive.
Greg Lambert (07:45)
Yeah, yeah, like we said earlier, people hate giving up their phones. My phone’s usually not with, you know, less than three feet away from me at all times. In fact, I tease my wife as like, if I don’t have my phone on me, I feel naked. And she doesn’t care. I mean, I find her phone laying all over the house. We have different approaches on this. you.
Matt Rasmussen (ModeOne) (07:54)
Sure.
For sure.
for a second.
Greg Lambert (08:09)
You talked about how the cloud computing has really kind of helped with this and especially with what you’re referring to as the truly remote solution that ModeOne brings. I guess, you kind of mentioned this earlier where there’s physical kits or technicians that really had to be right there with the phone. So can you…
just kind of walk us through the process that you have and how that kind of differs from what normally happens when it comes to pulling data from a phone.
Matt Rasmussen (ModeOne) (08:42)
Sure, yeah, absolutely. So I think the big thing for us to talk to these phones, it’s still kind of agent based things. So on the iPhone, we route through the custodian’s own laptop or desktop. On an Android device, we can operate right off the phone. But usually when we need access to the phone directly, it’s because we need heavy processing power to chew through all that data, right? So these phones can be a terabyte large now. And if I needed to process,
800 gigs of data on the fly or being collecting that in real time I need to send like a larger laptop or have a beefier kind of desktop with good processing power and RAM a lot of space to write that data to So it’s kind of like a high hardware component, right? That’s Needed to do this. So the the big thing for us is a the fact that we can be targeted means that I don’t have to pull a terabyte off the phone
to then go parse through it. So I can, you may have a terabyte of data on your phone, but I can focus on the 10 gigs of data. And then because our agent only plays as traffic cop, we’re not processing on the computer, we’re not doing a heavy install. It allows us to be like very transactional and very lightweight. And so in cloud computing, if it’s gonna take me 10 hours to do something, I can throw as many resources as I want to get it done and
five minutes and my cost is the same, right? Whether I had one agent do it for 10 hours or I had 10 agents do it for one hour, my cloud computing costs are the same. And so that’s another one of those things that helps us get through these so fast remotely is I can in the cloud scale infinitely to chew through it and then ramp back down.
Greg Lambert (10:22)
Yeah. What about if phones are located in another country? How do you handle those sorts of issues? Are there any regulations or whatnot that you have to face?
Matt Rasmussen (ModeOne) (10:36)
So the only regulations that we face would be kind of client driven. like there may be like reasons to keep data in country, right? So being able to spin up a ModeOne environment in Germany to collect phones in Germany and maintain that data in Germany. That’s one of the cool things that we can do in the cloud. But we can also route that data to any of the AWS regions we want. So like when a fun story I kind of always tell is
We had a project where there was five board members and they continued to just not collect their phone, not collect their phone. And then they got a court order that you need to produce your phones by Friday. And they were all in Mexico on like a company retreat. And so we were able to, get one of their laptops set up on the resort wifi and pull all five from Mexico and route that back down, back to the U S so that the attorneys can get through.
what they needed to go through. it’s kind of cool that we’re able to operate somewhat universally here.
Marlene Gebauer (11:38)
So you’re, Matt, you’re highlighting a key features is this targeted collection ability. So, you know, we don’t want any more books thrown at people. you know, you can filter by date or participant or apps, you know, while ignoring the personal data. And, know, I imagine this, this does help balance the need for discovery with, privacy concerns. So can you give us an example of how the.
Matt Rasmussen (ModeOne) (11:46)
For sure.
Greg Lambert (11:46)
Ha ha ha ha!
Marlene Gebauer (12:06)
the new participant exclusion filtering works.
Matt Rasmussen (ModeOne) (12:09)
So there’s a big debate right on phone types. it do corporations want to have a corporate own device policies? Do people want a BYOD policy? What I’m kind of seeing is BYOD is somewhat the more favored kind of ⁓ program because there’s not a heavy hardware cost, but that opens up some legal risks, right? That now I’m forcing somebody, not forcing them, but
somebody’s electing to use their own phone, which has a majority of their own data on it. It’s a very small amount of data that could be truly professional communications and things like that. So that inclusionary and exclusionary filter has been so good for that specifically. And so where we use it a lot is we may not know the bad actors or the custodians in play, but we do know the
family members, phone numbers, the significant others, the neighbors, things that are absolutely non-relevant. And so being able to come at that in a different way, like, I need all the texts except for the ones that we can corely mark as privileged and personal and non-responsive here. That’s been huge. where we’re seeing the biggest door open here is for C-level execs, SVPs, EVPs who
usually have a little bit more weight to throw around that they are or are not going to comply with something or that you’re going to have access to their phone. So being able to do this, give them the assurance that like we can segregate the threads that they don’t want and collect everything else. That’s just, that’s been huge for us in the last 12 months here.
Greg Lambert (13:48)
So going off to a retreat in Mexico is no excuse anymore.
Matt Rasmussen (ModeOne) (13:51)
No, no, not
Marlene Gebauer (13:52)
You can’t get away.
Greg Lambert (13:55)
I wanted to pull on the thread that you mentioned earlier about using a number of agents and that your cloud costs are the same to pull the data in 10 agents in one hour as opposed to one agent in 10. Do you mind kind of fleshing that out a little bit and talk about how you get your data ready in shorter periods of time and kind of how these agents are set up?
Matt Rasmussen (ModeOne) (14:23)
Sure. the, one of the things I was trying to learn from, if I go to like an old ediscovery kind of methodology through anything, there’s usually a queue of work. So I need email to be processed and I’ve got a hundred terabytes. My processing team is going to be chewing through that week over week doing rolling releases because they have a fixed amount of hardware. They have a fixed amount of processing power. They have a fixed amount of data storage. And so.
In the cloud, we don’t have any of those restrictions and cloud costs are charged on processing time, RAM used, storage used. So in those kinds of environments, whether it was a one gig phone or a terabyte phone, however long it was going to take to process through that data is a fixed cost. It’s going to take X amount of processing power, X amount of RAM, X amount of storage. And so
What we’ve done in ModeOne is it’s built to scale resources directly per phone. So we have no queue system. And depending on how much data is there, how much data we have to chew through, how much processing power it’s going to take, then the system will ramp up to meet that demand because my cost stays the same and we can chew through it faster. So we allocate more resources, get that cleared out of the queue.
And then the resources can ramp back down so that we’re back at a baseline level. And so to kind of give you kind of a, how that scale works, I handled a pretty major second request that had 400 phones. And for us to do that back in the day, it took me about seven months to coordinate people and teams and get data processed and an info review. We have a financial services client that we knocked out 418 phones in two weeks.
Greg Lambert (16:04)
whooo
Matt Rasmussen (ModeOne) (16:15)
Right, and so it’s just a much different annual now because A, we can be remote so we can touch these all at the same time, but it doesn’t matter how much data you throw at me, I can still ramp up to meet that demand and get it done in a timely fashion.
Greg Lambert (16:30)
Interesting.
Marlene Gebauer (16:30)
curious. I mean, you’ve, you’ve, you’ve, you’ve obviously addressed our need for speed, but, what’s, know, what’s the accuracy rate in terms of gathering all of the business data that, is, needed and also kind of what’s the rate of, of, error in terms of pulling in any type of private information.
Matt Rasmussen (ModeOne) (16:49)
So the accuracy rate is 100%, which is great. The caveat is, and this is just some of the wonky things that happen with Android or Apple devices, when people have iCloud sync on, or you’re in a group chat that they’ve sent a message, but maybe your phone’s only downloaded the thumbnail until you open that photo, there are gonna be some artifacts like that.
Marlene Gebauer (16:53)
Wait, what? ⁓
Greg Lambert (16:54)
You
Matt Rasmussen (ModeOne) (17:17)
that are stored somewhere else. So for our system, we’re doing a completely logical pull directly from the device. So we’re not then routing through that to iCloud. We’re not checking backups on the computer. So there are some times where somebody will say like, I see it on my phone, but it didn’t collect the data. And usually when we dive into that, it’s some sort of iCloud syncing kind of issue. But we’ve got some things built into our workflows there where we
can audit those things ahead of time when we start the collection, then we audit it at the end so that we make sure like record counts are matching, attachment counts are matching, that kind of thing. Because, know, defensibility is such a high bar for us in the industry we’re playing, right? So authenticity, defensibility, validation, all those kinds of things are super core to what we’re doing and built into the product to make sure that we’re hitting those.
Marlene Gebauer (18:08)
And beyond the standard litigation, e-discovery, what are some of the other key uses that you’re seeing for ModeOne? Maybe compliance or internal investigations, regulatory matters, something like that.
Matt Rasmussen (ModeOne) (18:13)
Thank
Yep, so I would say the top two compliance is the number one for sure. Just.
Marlene Gebauer (18:28)
Is
that growing? you see?
Matt Rasmussen (ModeOne) (18:30)
Absolutely. I talk about this a lot, but DOJ and FTC came out with three memo updates in the last 18 months on what they want from phones. Phones are absolutely mandatory now. So it’s starting at like more heavily regulated corporations right now. We’re going to see this trickle down through really any corporation that’s got a large device pool, has some sort of compliance regulation or federal regulation against them. They need to be touching these phones in a very
scalable way in a very low touch way. that’s corporate compliance is the huge one. And then I really did when I built ModeOne, I really thought this was going to be a litigation e-discovery tool. While it’s somewhat adjacent, the number two use case is just legal hold generally. Because if you think about ⁓ if an e-discovery or litigation matter percolates to outside counsel, we’re probably like, we’re probably dealing with 10 to 20 custodians that we’ve
gone through interviews, we’ve identified that these are the important people. But when that actual matter hit, or when the company thought there’s a potential for litigation and had to put some things on legal hold, net that they cast is much wider. So they may put 100 people on hold for 10 people to actually become relevant in the lawsuit. And so that’s the other thing that we’re really seeing is where people are
suspending email or, you know, OneDrive, things like that. Phones are something that need to be preserved as well. So we’re seeing a lot of steps to the left on the actual preservation of that data before it even becomes actionable.
Greg Lambert (20:01)
And just to dovetail off that a little bit because you know there’s been certain kind of encryption the texting tools on phones that have hit the news recently. ⁓ So I mean a lot of people think of email they think of text they think of OneDrive you know those cloud storage apps kind of evolve or how are you having to evolve with with.
you know, catching up with this stuff.
Matt Rasmussen (ModeOne) (20:29)
daily. So,
so for us, there’s three challenges for us. One is app updates, right? WhatsApp makes a change. They don’t blast the world saying, Hey, all these things have changed in our app. Right? So like staying ahead of like feature updates, new versions, things like that. The second actually is the emergence of new apps. Right? So we can have a good roadmap for texting and for Viber and for WhatsApp.
But we could come up with Lambert Chat and it becomes the number one chat app in the world. We need to quickly get to be able to support those types of things. I am routinely surprised. People ask me if I support apps like QQ and I feel like they’re kind of pulling my leg that these aren’t real apps. then I go look and it’s super popular in South Korea.
Marlene Gebauer (21:19)
It’s an app.
Matt Rasmussen (ModeOne) (21:22)
So there’s that. And then the third issue is staying ahead of operating system changes. So there’s the actual phone that changes as well. One of the biggest things that helps us is because we’re touching this data in a logical way, we’re not exploiting the phone. We’re actually certified Apple and Android developers. So for OS changes, I get new operating system updates about five months in advance.
So we’re on iOS 18 right now. iOS 19 will be scheduled to be released in September this year. We’ll have the beta for that OS this month to make sure that we’re staying ahead of the curve for when it drops in September and the world’s updating, we can have day one support for that system.
Greg Lambert (22:10)
Yeah, it’s a never ending challenge. Yeah. So you’ve also integrated with tools like Relativity and I know that you allow for, you know, for your clients to keep information in a controlled environment like AWS or more likely in law firms, it’s Azure. So, you know, how important is it to you that you make sure that you’re fitting
Matt Rasmussen (ModeOne) (22:12)
Never, it never stops.
Yeah.
you
Greg Lambert (22:40)
you know,
tech that your customers are using into your own ecosystem.
Matt Rasmussen (ModeOne) (22:46)
So it’s probably one of the top things I’ve always focused on personally. I mentioned this at the very beginning, but just through me and my career, I’ve always been looking for the least amount of steps to get from start to finish. And when we look at the software ecosystem and e-discovery, there are so many tools that do so many things, right? There’s 10 different document review platforms. There’s 30 data collection softwares. There’s
Chronology software, depo software, trial software, and none of those things really talk well to each other. So like when we’re going through the life cycle, if I’m going from collection to processing and processing to review and review to depot and depot to trial, I’m pulling data out, transferring it somewhere, installing it again, taking it out, doing it again, you know what mean? And so from a human time component, from a time to…
copy data to what kind of information is being lost. That was such a thing that bugged me that there wasn’t a really good way to have data travel through that whole kind of EDRM being able to connect and kind of be the hub on the wheel between data sources, bringing them in and then pushing them to where they need to go has been huge for us and huge for our clients because they’re seeing the efficiency gain that their teams don’t have to be.
bogged down with importing data, they can be doing more highly relevant stuff to the matter. And so that’s such a huge focus for us and will continue to be throughout the years.
Marlene Gebauer (24:21)
So Matt, I’m really interested in what the adoption curve looks like. Um, you know, kind of clients are most interested seeing the most benefit? mean, you launched in March, 2022 and were named illegal tech startup of the year in 2024. Has that given a bump or a boost?
Matt Rasmussen (ModeOne) (24:39)
for sure. Yeah, I was talking about this a lot in New York, actually. If you look at tech in eDiscovery generally, there’s a, I don’t know what to call it, kind of an apprehension curve, right? Think about when TAR came out, How many people didn’t want to be the first ones to do it? Or Relativity comes out with a new major version release and no one wants to upgrade because they want to see other people go through it first and think if they’re going to suffer through it or it’s something new and something’s going to break.
Greg Lambert (25:07)
Yeah, we call that racing to second place in the law.
Matt Rasmussen (ModeOne) (25:10)
Okay.
And ⁓ if like, I think in the last like six, nine months, we’ve really come over that hump and have really kind of supercharged, you know, adoption rates, types of clients that were closing. So when we started three years ago, I was selling to small to medium LSPs, forensics folks, just trying to evangelize the product. Fast forward three years later, I’ve got three clients in the fortune 10.
I’m working with major AmLaw 25 firms. I have every major litigation service provider in the country now. I understand that ModeOne is not the solution for phones for every phone, but it is a very powerful tool in the toolkit. We’re seeing a lot of that adoption across different markets. When we get into the corporate side of things,
the two main drivers there are the compliance, the corporate compliance work and the legal hold kind of preservation work.
Greg Lambert (26:08)
I think this may be the longest we’ve gone in a recent episode before saying artificial intelligence, which is great. But I know that you guys have a, ModeOne has a partnership with StreamView implementing some of the AI capabilities into the workflow. So, how does AI work in this type of environment?
Matt Rasmussen (ModeOne) (26:16)
you.
Marlene Gebauer (26:17)
Congratulations.
Matt Rasmussen (ModeOne) (26:35)
Sure. So for us, there’s several different ways when we’re talking about short messaging, right? So as silly as it sounds, emoji analysis, right? If it’s a sexual harassment case and I want to see what are the top 10 emojis they use in this thread, right? Being able to make those kinds of assessments very quickly is one thing. Sentiment analysis and filtering is the other, right? So like…
Greg Lambert (26:45)
God.
Matt Rasmussen (ModeOne) (26:59)
like pharmaceutical companies want to make sure that they’re checking their sales associates phones to make sure that thing that they’re not making claims that drugs not addictive or it’s too addictive or, you know, things like that. That’s not something that we can be processing that data, have somebody get human eyes on, make a call, report it up. And so being able to
Run those through AI models quickly to like quickly assess flag and promote any risks is another huge thing. then the last thing is just communication analysis, right? So who’s talking to who are they talking to competitors? Are they trying to be poached stuff like that? So there’s just like different kind of layer because there’s there’s metadata of like content of the thread with attachments are sending but there’s other metadata as well where those photos were taken.
metadata about the apps. And so being able to have the AI layer to be really kind of assessing a very technical source is huge for our clients.
Greg Lambert (28:02)
Yeah. like, emoji analysis is the name of my new punk band. So I’m going to do that. Or maybe that’s the new name of the podcast. We, we can call it the emoji analysis podcast. do think, Marlene?
Marlene Gebauer (28:07)
Ha ha ha.
Matt Rasmussen (ModeOne) (28:07)
Yeah, that’s awesome.
Yeah.
Marlene Gebauer (28:14)
I mean, that would, that would be like fascinating to see, you know, it really would
in terms of, of what the, the, the data shows.
Matt Rasmussen (ModeOne) (28:21)
For sure. For sure.
Greg Lambert (28:24)
So Matt, want to talk about ModeOne specifically with being a startup. Especially, I believe you’re probably totally bootstrapping this, right? And then how you’re approaching it.
Matt Rasmussen (ModeOne) (28:33)
Sure. Yep.
We took, we definitely took, so we took an angel round, when we first launched in 22, just so that me and the partners could all leave the comforts of our nests and venture out. but that, that was to get us about a year, I was worth a runway. And, so bootstrapped it all the way through MVP, took that angel round and then a bootstrap since.
Greg Lambert (28:56)
Okay, so what’s been kind of some of the biggest challenges you have being a startup in this industry?
Matt Rasmussen (ModeOne) (29:03)
so adoption was a big one, I felt like as, as you take on like institutional money or you write, make bigger raises, right? You’re usually being associated with bigger names. They can be louder in the marketing. There’s a little bit more faster path to brand credibility, brand adoption, those kinds of things. So I think that was, you know, it so important to us because
We really kind of wanted to forge our own path here. We think we had a really good product. We had a good way to position this. And so we wanted to set it out on our own. But I think that’s a pretty big, that was a big challenge of just like not being able to be as loud as we wanted to. But it’s like three years later, it feels like what we’ve been doing, the seeds we sowed along the way, we’re able to do that. And then for us, the other challenge is just, know, scale of growth, right? Do we want to hire?
10 people, that’d be great, but we’re doing it in a sustainable way. And so that’s been a challenge for sure, but it’s also been a kind of a blessing in disguise for me, right? Because we are a product that can scale so quickly to touch a lot of clients, lot of custodians, things like that. It’s been nice to not rush some of our processes, our workflows, to make sure that they’re all airtight so that we can be operating at the level we are today.
Yeah, I think those are probably the two biggest things.
Marlene Gebauer (30:26)
So Matt, we have come to the end of the podcast where we ask all of our guests to pull out the crystal ball and sort of give us their thoughts. So we’ve been looking ahead a few years. What do you think is the biggest challenge or change that you see coming for the mobile data discovery and investigations? you know, how’s ModeOne going to prepare for that?
Matt Rasmussen (ModeOne) (30:51)
Yeah, I think, I know this is very self-serving, I really do think we’re going to be seeing a lot more work on what are required from these phones. Corporations demanding more controls over these phones just because they’ve been able to kind of skirt away with negotiating away from phones or just preserving SMS texts and now that federal regulators are now paying attention to this, it’s going to trickle down into the
private practice and civil matters and things like that. I really do think that phones are going to have to be, they’re going to have to have these tools that are scaling, touching them fast, being able to really kind of respect people’s data privacy in a global kind of market. everyone always asks me if I’m going to be doing new products. And we always say, no, we’re digging deep on phones just because there’s going be so many changes that happen over the next two, three years. So I’m looking forward to kind of helping meet the demands there.
Greg Lambert (31:48)
So the big question is, are we going to go away from bring your own device and then going back to Blackberry issued from the firms, right?
Marlene Gebauer (31:56)
I
was going to say it’s like after that, I’m like privacy’s dead.
Greg Lambert (31:59)
Hahaha ⁓
Matt Rasmussen (ModeOne) (32:02)
I don’t think so. mean, if you think about it, if you had a thousand employees that have an iPhone, that’s easily $800, $900, $1,000 of hardware, right? And so certain companies, certain industries, absolutely that makes sense. But you know, some can’t afford that just as a cost of doing business. And so I just, I don’t see it going away anytime soon. just see.
a lot more policy kind of revisions on what’s company owned and what’s private for sure.
Greg Lambert (32:31)
All right, well Matt Rasmussen, founder and CEO of ModeOne. I want to thank you very much for coming on and talking to us here on the Geek & Review.
Matt Rasmussen (ModeOne) (32:40)
Yeah, thank you so much. I’ve been looking forward to this for weeks. So this was a pleasure.
Greg Lambert (32:44)
Awesome.
Marlene Gebauer (32:45)
We have to, so. And thanks to all of you, our listeners, for taking the time to listen to the Geek in Review podcast. If you enjoy the show, share it with a colleague. We’d love to hear from you on LinkedIn and Blue Sky.
Greg Lambert (32:58)
And Matt, if listeners want to learn more about you or ModeOne, what’s the best place for them to go?
Matt Rasmussen (ModeOne) (33:04)
Feel free to email me directly. My email is matthew.rasmussen@modeone.io or you can visit the website at modeone.io Book a demo, see what we’re about. Would love to find some time to talk.
Marlene Gebauer (33:18)
And as always, the music you hear is from Jerry David DeCicca Thank you, Jerry.
Greg Lambert (33:24)
Thanks, Jerry. All right. Bye, everyone.
Marlene Gebauer (33:26)
Bye.