Red Violet at Midwest Ideas Conference: Strategic Insights in Identity Verification

On Wednesday, August 27, 2025, Red Violet Inc. (NASDAQ:RDVT) presented at the 16th Annual Midwest Ideas Conference, offering a strategic overview of its identity verification solutions. The company highlighted its robust market position, competitive advantages, and areas for potential growth, while acknowledging challenges such as reliance on key data providers.

Key Takeaways

• Red Violet’s fixed-cost data model supports high gross profit margins, exceeding 80% last quarter.
• The company powers the backend for seven of the top ten identity players, underscoring its market strength.
• Red Violet’s cloud-native platform offers a significant edge over competitors with legacy systems.
• The firm is exploring AI integration to enhance customer interactions and automate processes.
• Public sector and background screening markets are key targets for future expansion.

Financial Results

• Fixed Cost Data Model: Long-term agreements with data providers allow for a near 100% contribution margin on additional revenue.
• Gross Profit Margin: Achieved over 80% gross profit margin in the last quarter.
• Adjusted EBITDA Margin: Approaching 40%, indicating strong operational efficiency.
• Data Provider Concentration: One provider accounts for 40% of data costs; the contract was renewed for five years with minimal cost increase.
• Retention Rates: Gross retention rate was 97% last quarter, with guidance between 90% and 95%. Net revenue retention targets range from mid-teens to 120%.

Operational Updates

• Vertical Market Focus: Revenue is evenly distributed across five verticals: collections, financial & corporate risk, investigative, real estate, and emerging markets.
• Cloud-Native Platform: Built from the ground up, providing a competitive edge over legacy systems.
• Forewarn Real Estate Safety Product: Servicing over 575 real estate associations and approximately 350,000 individuals.
• Public Sector Expansion: Secured a significant contract with a major U.S. toll authority.
• Background Screening Product: Gained a contract with a leading payroll company.

Future Outlook

• Public Sector Growth: Aiming for larger contracts with lengthy sales cycles and budget-dependent ramp-up periods.
• Background Screening Market: Actively developing a productized solution for this sector.
• AI Integration: Plans to leverage AI for improved customer interaction and internal process automation.
• International Expansion: Currently no plans; focus remains on U.S. market opportunities.

Q&A Highlights

• Switching Costs: Vary by use case; online platform has none, while API integration allows quick deployment.
• Competitive Advantages: Continuous technology development and data aggregation are key differentiators.
• Artificial Intelligence: AI is used to enhance platform interactions and automate processes, supporting margin expansion.

Readers are encouraged to refer to the full transcript for a detailed understanding of Red Violet’s strategic direction and financial performance.

Full transcript - 16th Annual Midwest Ideas Conference:

Steven, Conference Organizer: Here again for day two of the IDEAS conference. The next company we have for you is Red Violet. They’re a leading solutions provider in the ID verification sector. And with us today, we’ve got the vice president of investor relations, Camilo Ramirez. Camilo?

Camilo Ramirez, Vice President of Investor Relations, Red Violet: Thank you, Steven. Appreciate it. So I’ll give you guys a bit of background about what we do, management background and then we’ll go over our use cases, exactly what we do. And then, let’s make it conversational so feel free to ask any questions. Stop me if you need clarification or anything, we’ll go from there.

I’ll quickly flip through the deck, I’ll highlight couple pages but preferences for conversation. So what do we do? We do all things identity. High level, we aggregate the spirit of databases, call it liens, judgments, credit header data, anything and anything and everything on every adult individual in The US. We aggregate that data and then sell it back out to different industries.

So, we serve five different verticals, collections, financial and corporate risk, investigative, real estate, and what we call emerging markets. I’ll dive deeper into that in a little bit, but let me take a step back and give you a little history about management. So, in the late nineties, management team built a business called Seizen in the same space, Data Fusion Identity Verification. As you can imagine, technology then was very different. We built it in data rooms.

There were ad hoc connections, so if you see Camilo and Steven, always present them in an investigation as opposed to a more dynamic presentation where the Camilo result can be applicable only to the situation and don’t don’t present Steven. Ultimately, that was sold off to Reed Elsevier’s LexisNexis for about 750,000,000. Non competes expired, team got back together. They started a company called TLO. They were it was being personally funded by one of the founders.

He ended up passing away abruptly through the development phase. So revenue run rate at that time was about 25,000,000. They were losing anywhere from 1 to $2,000,000 a month and ultimately that was sold off to TransUnion prematurely. Right? They’re still going through the r and d phase.

Again, non competes expired. Team got back together, call it in 2014. I’ll show you guys a little roadmap of the history. They got back together in 2014. As you can imagine, technology has changed drastically from the late nineties to 2014.

We had AWS, so this iteration is cloud native. It was built in the cloud from the ground up, that’s a big differentiator from the competition, the Seizen product and the TLO product that management built. And then you have LLM models, AI, so it’s able to learn upon itself as you feed that data, it’s making those connections, building new data points go out and clear transactions.

Unidentified speaker: So what do we do?

Camilo Ramirez, Vice President of Investor Relations, Red Violet: So I’ll give you a couple of use cases. We’ll start with collections, it’s the easiest one. You’re, let’s say, you buy debt from Capital One, you have a million records, you wanna go out and You buy a million records, you wanna go out and validate that information. I’m getting kind of an echo in the back. See, you buy those million records, you go out, you want to validate the information, right party contact information, have they filed for bankruptcy, we’ll pen that information, send it right back.

We’ll go to real estate, we serve real estate in two different manners. On our IDI side, it’s going to be more of a marketing play. I want a list of individuals that are 16 and above that live in a two storey home propensity to sell. But on a under our brand Foreworn which is basically just a skin application that was layered over our core platform that’s sold directly towards the real estate community. We go after associations.

That is going to be, let’s say we’ll, let’s say you’re a real estate agent, you get a phone call, I wanna see this $3,000,000 home, I’m only in town tomorrow till tomorrow. My name is John Smith, purposely using a very generic name. I’m gonna show up in Mercedes desk class. What it does when that phone call comes in, it does a reverse phone number search and it comes up, brings up their background. You don’t see John Smith, you see a different name.

You don’t see that Mercedes s class. What you do see is this individual just got out of prison for sexual assault. So you’re not going to show that home. What we noticed was that there was a lot of crime committed against realtors. So this is more of a safety product for for the for the realtors, and we go after the real estate associations.

Today, we serve about 500 plus real estate associations. There’s, call it, about 1,100 associations in The US. So the associations, what they do, they buy this product for their members, so it’s a member benefit for the users. So if you’re part of, let’s call it, down by us Palm Beach Real Estate Group, the state of Florida purchased for Warren for all the associations underneath it, they’ll just sign up. It’s free use, unlimited use and that’s a SaaS product.

So, if you’re an individual coming on board, not under an association, that’s going run you $20.25 dollars a month because we sell direct to the associations, economies of scale, those prices can are reduced drastically. So on the Florida Florida is one of the largest associations in The US, that’s going to be a couple dollars per member. They have about 400,000 members. So it just depends on the scale of the association. Next, we have financial and corporate risk.

Under financial corporate risk, we have background screening. So, I’ll give you a couple of use cases there. Let’s say you’re at Walmart, you have an applicant, they’re applying for a job, they enter four addresses and I’ll disclose this name because we disclosed it publicly early on. They’ll go to a company called Innovative. Innovative is the background screener.

Innovative will call out to us, is this information accurate and complete? We’ll say it’s accurate but it’s incomplete. They left off the fifth address. And that’s usually where the criminal record lies. So, innovative will go pull that criminal record at that fifth address and ultimately send that information back to Walmart so they can make their hiring decision.

A use case on innovative, we won that business early on from TransUnion. They’re doing low 5 figures a month. Ultimately, they grew up into well into the 6 figures. They were sold to Apris, another identity player. Ultimately, Apris was purchased by Equifax, and as you can imagine, has all the data in the world.

Right? They have all that information, but they don’t have an aggregation platform. They have the individual data points. And at that time, during that acquisition, the innovative contract was up for renewal. Equifax reached out, hey, we get an extension on this contract, three month extension?

We said, of course, we understand we understand you’re trying to execute on synergies. We don’t think you’re gonna have the same throughput or lift on data, but we’re here to help if you need anything. They came back, asked for a couple more extensions, ultimately they signed a multi year agreement. They couldn’t recreate the the data quality or the throughput on their side even though they have all the individual data points. So we have a really good relationship there, multi year contract.

And then we can go into investigative. Investigative vertical, that’s going to be, for example, law enforcement. So you get pulled over law enforcement, very easy in our system or one of our legacy products that we sold off. They’ll run a play, do an investigation. How we differentiate in that space is we have a very neat mobile application where let me just flip to another side.

Neat application, so let’s say you had a witness, I saw this red f one fifty in this intersection, it was a hit and run, something of that nature, crime committed, so the investigator can come in, basically do a geofence, drop a pin within that circumference of that area and say, give me all the state public sector. Public sector, we’re really excited about the public sector space. We made a hire, call it just over a year now, Jonathan McDonald. He led the public sector at TransUnion, built us up from zero to where it is today at TransUnion, and we built up a team around him as well, call it around 15 to 20 individuals. And so public sector, as you can imagine, your typical three letter agencies doing investigations on individuals, you have ICE doing investigation as well, so those are all opportunities we can win, but even outside of that where those niche use cases, so for example, we just won one of the toll one of the largest toll authorities in The US without naming specifically which one.

So down by us in South Florida, we have what they call SunPass program for Florida Turnpike. They can do bill by plate. So let’s say you’re running through the toll, you don’t have this SunPass to automatically pay for it, it’s going to run, it’s going to take a picture plate, then they have to do search based off that plate to understand who’s the owner of this vehicle registration search and then they have to figure out the address, send out a bill to that that vehicle owner. If that owner doesn’t pay that bill, then it goes through a collection process and they have to go through right party contact information. So we won this contract.

Just call it maybe a quarter ago, we disclosed it on our last earnings call and that’s going be well into the 7 figures once that’s up and running. And that’s one of 50 call it. Some other niche use cases are like homestead exemptions. Are these individuals truly living in that home that they’re claiming a homestead exemption? So doing address verification, homeowner verification, so forth, or even something as niche as is this child truly living in this public school boundary, right?

So as you can imagine there’s a lot of situations where parents say, hey, my child’s living with the grandparents so they can go to this A rated school in a public school system, but in reality they’re not. So we have school districts reaching out for that type of data, address verification essentially validate that those children truly live in that area and they are eligible to attend that school. So those are some of those niche use cases in the public sector that we’re really excited about. Those five verticals we say revenue is pretty evenly distributed, call it 20% across the board. Pause there, see if you guys have any questions.

If not, then I’ll jump into like the financial model. So we like to say our our our data is fixed cost in nature. We go out, do long term agreements with the data providers as you can imagine, some of those are going to be credit bureaus, niche data aggregators that are getting data from different municipalities aggregating that information, we’ll consume it. So we do long term contracts on that and it’s fixed cost for unlimited use. So every additional dollar we’re bringing in today is nearly a 100% contribution margin.

Our last quarter on the gross profit line, we reported just over 80% gross profit and then we’re starting to approach 40% adjusted EBITDA margins. So, we have one if you take a look at our financials, disclosures in the 10 ks, you’ll see that one data provider accounts for 40% of our data cost. That is not just one data asset, multiple data assets and we have a really good relationship with that credit bureau and then ultimately we just renewed that contract for another five years here a couple months ago and nearly minimal incremental increase. The renewal prior to that was flat. We always get the question, hey, if you see these if the credit bureaus are seeing the type of margins you guys are having, why wouldn’t they just escalate the price on you?

One, we’re multi source on every data point, so if that does occur, we’ll just say, hey, we’re not going accept that and we’ll just bring our tier two data provider up to tier one and then continue to move on and we can give those data points back. If those data points go back, we don’t lose the learnings, those connections between brother, son, family connections, those learnings, those are all proprietary to us so those learnings stay with us and data points go back and we just bring up our tier two. But the last couple renewals, we have a really good relationship and we renewed pretty much flat from that on our last renewal, so no concern there.

Unidentified speaker: So are you dependent upon your patents? And are you, do you have some special technology that enables you to do this or are you Yep. More than this?

Camilo Ramirez, Vice President of Investor Relations, Red Violet: No. No. No. So so no patents. Right?

We don’t have any patents. It’s the technology that we have that aggregates that that information and links those data points together and continue to learn from that information. So, good example that I like to give is in certain industries they have what they call the waterfall effect. So, you’ll go into an industry and try to gain a customer and they’re gonna We will go and say, hey, let us come in at tier three on your waterfall. So what that means is they’re sending a million records to let’s say TransUnion.

TransUnion’s gonna have a certain hit rate, call it 70%. Some of that’s gonna fall out. They don’t have information. They’ll send it to the second provider, Rudel Sphere’s LexisNexis Aggron product. They’ll be able to hit some amount on that that fallout as well and we’ll say, hey, let us come in third.

We know we have high confidence in our data assets and we’ll get a high hit rate on that and we’ll come in even though it’s been scrubbed twice already and we’ll get a high confidence hit rate. And that that’s how we’ll start moving up the waterfall as well. If you have a high hit rate, the customers want you to be first in waterfall because you get economies of scale. As you go down the waterfall, it gets more expensive for them. As you can imagine, they’re pushing less less data through you.

So it’s what we do with that data and how we aggregate that data as opposed to just hustling or just reselling data points. Right? Because a bankruptcy is just a bankruptcy. It doesn’t tell you anything. As you’re transacting in in the e commerce today, you’re leaving a footprint every single day.

Banks for like know your customer or or loan decisions can’t rely on data from yesterday or the day before. They have to have the most recent data. They want to understand, did you just file for bankruptcy? Did something occur? Was there a lien or judgment placed on your property or anything of that nature?

So you need the most current information.

Unidentified speaker: What about the international market?

Camilo Ramirez, Vice President of Investor Relations, Red Violet: So today, we’re not in the international space. We have a lot of GoGet in The US. Today we have about 9,500 customers. The Acurin product has, about 400,000 customers, and then the TLO product has anywhere from like 60 to 70,000 customers. So we’re just scratching the surface.

And then, so we’re powering seven of the top 10 identity players to the likes of Callitprove, Jumeo, Ecada now earned owned by Mastercard. They all have their own niche way of doing identity verification, how to clear a transaction. So, of them are gonna be mobile authentication. Let’s say you’re logging into Bank of America or Wells Fargo using facial recognition. What what’s actually happening behind the scenes is saying, hey, this mobile ID belongs to Camilo Ramirez, does it match the bank side and here’s the PI information?

Yes, grant access, if not, ask security questions of that nature. Or they’re going to be doing like document verification, load up, take a selfie, load a picture of your ID, and they’re gonna do the identity verification on that physical document. And it’s still pulling PII information behind the scenes. So those providers, they have the technology, the front facing solution, but they don’t have the data in house. So every time they’re clearing a transaction, they have to call out to someone like us or one of our competitors.

I think there was a question over here.

Unidentified speaker: Can you talk about the switching cost

Camilo Ramirez, Vice President of Investor Relations, Red Violet: for your for your customers? It’s a good question.

Unidentified speaker: Like, is it difficult if someone with better technology comes along and they

Camilo Ramirez, Vice President of Investor Relations, Red Violet: No. So I it so it’s use case dependent. Right? If someone’s coming on board using our online platform, there’s no use cost. No switching cost because they’re just, going through our credentialing process.

We’re validating that they have a valid use case and then they can start using our system. So that that’s how we win business too. Right? Because they’re not they’re not coming in and dropping a team, building out a whole platform. On the API side, our our API is very flexible.

They’ll we like to say it’s very customizable but and behind the scenes, it’s just turning on and turning off levers depending on what they need. So usually, they’re gonna have teams on their side and they’re up and running between twenty four and forty eight hours. So a good example there on switching costs and and ease of use on the API side. So a number of years ago, we had a customer. They’re doing well into the 6 figures a month.

They’re an identity verification mobile they do mobile authentication. So what they’re doing is, just the example I gave, they were raising capital, TransUnion ended up leading that capital raise. TransUnion CEO gave gave them a call and said, hey, for us to close this transaction, you’re going have to stop using I Red By Lights IDI data and move all your your consumption to us. And so the customer gave us a call, told us what was going on. We said we understand we would do the same if we needed capital.

We’re here if you need anything. We saw that revenue drop off pretty much immediately. Within a couple months, we started to pick back up. What what came out of it was that once they switched to the TransUnion product, they base they couldn’t handle the throughput and the latency on the platform. Right?

Because they’re they’re building a a data room as opposed to the cloud. So during peak productivity hours, they were their customers were calling them and complaining, hey, I sent this call through. I’m not I’m getting false positives or I’m not even getting a response. So ultimately that business came back to us pretty pretty shortly after and the CEO gave us a call, said, hey, TransUnion said they can build us a custom API, just give us a month or two. They said that you guys built us a custom API and we reminded them, hey, you guys were up and running within forty eight hours, there’s nothing custom about it.

And to this day, years later, they’re they’re continuing to grow with us even though they have that relationship with the TransUnion. So would it be fair to say that

Unidentified speaker: you’ve got to stay ahead of the technology, you’ve got to stay on top of things you’ve

Camilo Ramirez, Vice President of Investor Relations, Red Violet: That’s really got to be a fair statement. Yeah. We we can we’re continuing to build that moat around our platform. You have TransUnion, you have Lexis, Redel Series, LexisNexis. They both committed I believe TransUnion committed about $202,150,000,000 dollars a number of years ago to get their platform into the cloud.

We know they’re not going to get that platform. Once you we like to give the example, if you want to if you take a seven fifty seven, you want to make it much more efficient, fuel efficient, you’re not going to just take parts off, put parts you’re gonna start from the ground up. Once you start removing couple of piece from here and here, there’s gonna be downstream impacts that they’re not gonna be able to to to correct within the cloud, they have to start from the bottom up. So we’re continuing to build that moat, one through through the technology we’re using, the throughput, the latency, and then also just from product features as well. So something as simple as when you’re doing a search on the individual understanding is this relative is this relative of that individual?

Is it its mother, father, sibling, cousin, or anything of that nature, we get that granular based off of certain algorithms we have. We’re able to tell you what type of relative that is as opposed to the competition, they’re just gonna tell you it’s an associate. They don’t have that level of granularity.

Unidentified speaker: So I think I I was going through

Camilo Ramirez, Vice President of Investor Relations, Red Violet: the financial model. So, fixed cost model, nearly every additional dollar is a 100% contribution margin. Once you get below the gross profit margin, we like to contract everything long term contracts to any of our vendors. So most of our variability is gonna be headcount and that’s gonna be related to sales and commissions. We verticalize all our teams into subject matter experts.

So we have a real estate team, law enforcement team, and so forth. There’s a couple verticals we’re really excited about for the coming years. One, I alluded to public sector. As you imagine, that’s a very large TAM. With everything that occurred earlier in the year with Doge, that’s a a tailwind for us.

It worked out perfectly. We weren’t deeply penetrated into the public sector market, so we didn’t lose contracts. Historically, you have to wait until those RFPs come up. A lot of those contracts were cut and they’re coming back to market for RFP. They cut too much.

So now we have the opportunity to bid on those RFPs that potentially we wouldn’t have that opportunity for a number of years. And it’s no longer let’s just go with incumbent. Everyone wants to show that they’re executing on synergies, reducing costs and so forth, and having better technology. So we’re having really good success there on on the public sector team submitting those RFPs. These are a much longer sales cycle as you can imagine.

Some of those are gonna be year plus sales cycles and then there’s ramp up period as well because it follows the budget. So on the federal side budget, renewals around September. On the sled state, local, and education, that’s usually around the July timeframe for the state and local budget renewals. So the RFPs usually follow that as well. But those contracts can can be material as you can imagine.

We’ve seen contracts. They’re gonna be the whale contracts, $1,015,000,000 dollar contracts with RealSphere’s LexisNexis. Even if we get a portion of that, that’s gonna be material to our revenue. Secondly, we’re excited about the background screening space. We won one of the large payroll companies out there for their background screening process.

They’re in the process of onboarding. When Innovators was was purchased by Apris and ultimately Equifax, we had a buy versus build decision. Do we continue to just service this industry behind the scenes or do we go front facing? So we made the effort to build out the products. We already had the data, but how do we productize this and go to market with it?

So we started productizing it and then we’re this year, we’re now ready to go to market in a formal fashion. We had a lot of beta testing per se where we got a lot of feedback from the different player background screening players. It’d be really nice to do this if you can do x y and z. And now, we’re at the place where the the product is fully functioning, should service, call it 99% of the use cases out there. And proof in the pudding, we won one of the largest payroll processors.

We don’t we typically don’t disclose names on the IDI side. We’ll disclose names on the forewarned side. If you look at our press releases, they’re mostly all forewarned related. And that’s by design because there gonna be real estate agents, hey, our sister association offers this product to their members as a member benefit, why don’t you? So it’s more of a marketing perspective on the forewarned side.

And on the IDI side, as you can imagine, most of our customers don’t want individuals knowing how they’re doing their identity verification or where they’re getting their data from. So they’re very hesitant on allowing us to press release their name. And also, don’t want the competition knowing where we’re winning. And then from just a couple KPIs actually on this slide. From a gross retention number, typically we say these businesses run from 90% to 95%.

Last quarter, we came in at 97% on the gross retention side, but we continue to guide towards that 90% to 95%. We don’t publicly disclose net revenue retention, but as you can imagine, we mimic those information solutions companies. So, mid teens high mid teens to upper to a 120% from a net revenue retention perspective.

Unidentified speaker: From my understanding, the revenue, the retention is just of the clients, not the net revenue where they expect.

Camilo Ramirez, Vice President of Investor Relations, Red Violet: Correct. It’s just gross revenue retention. Yeah.

Unidentified speaker: The bottom line is Mhmm.

Camilo Ramirez, Vice President of Investor Relations, Red Violet: So we’re not accounting for any upsells or anything of that nature in this gross revenue Correct. Mhmm. Any other questions?

Unidentified speaker: So a company like Cleo, would that be a customer or a company?

Camilo Ramirez, Vice President of Investor Relations, Red Violet: Yeah. So there’s there’s there’s clear there’s two clear. So there’s like clear at the airport, and then Thomson Reuters has a legacy product called clear. That legacy product is mainly in the public sector space. It’s a very clinically dated product, but they have a huge presence in the public sector.

So we’re starting to bump up against against them. But yes, clear like an airport. So they’re running identity verification. They’re using facial recognition. They’re also scanning your ID and doing PII information behind that validating that it is a valid ID.

And then they’re pulling up your picture as well with your facial recognition. So that’s potential that clear would be a potential customer of us or one of our competitors because they need that information. It’s a good question.

Unidentified speaker: So, how does artificial intelligence, whether a threat or a benefit, fit into what

Camilo Ramirez, Vice President of Investor Relations, Red Violet: you’re A very valid question. So, I’ll answer it a couple different ways. We get that all the time. Right? Because AI is out there, you can aggregate this the data.

So ChatGPT is layered over the Internet. Bad data in is bad data out. Right? So as you can imagine, banks can’t clear transactions with with ChatGPT. They can’t say, hey, tell me about John Smith.

Who is John Smith? Is this the right individual? So how we are leveraging AI today in a couple different fashions. We have a high confidence data cohort. So how do we leverage AI on top of it?

So we can go out and and interact customers can interact with our platform differently. Today, when you go into our online platform, you’re entering a name, date of birth, social, something of that nature and getting information back. What we’re working on today is being more interactive. So tell me everything about Camilo Ramirez or something as simp which sounds very simple but it would require a number of searches. So, is there a family member of Camilo Ramirez that has a violent criminal history, whatever you want to call it.

Today, what you’d have to do, you’d have to search Camilo Ramirez, go into each known associate, look at their criminal background, and that’s going to take you time because depending on how many relatives, you’re going have to go through each relative, you can keep going down the family tree. As opposed to when you’re interacting with the platform, you ask it that question and it’ll either say, yes, this family member, it’ll give you the family member name, has a criminal history, it’ll give you all that information. So it’s doing all those searches in sub seconds. So that’s how we want to interact. We have even on the, let’s say, let’s say you’re CVS, you want to understand upward and downward mobility of the population within this intersection.

We have all those data points of that population. So basically, their analyst is gonna say, hey, typical crime rate in this corner is x y and z. Here’s the upward mobility of of individuals and here’s the house prices that continue to go up. So they’re gonna make a decision. Do we build a CVS on this corner or not?

So it’s aggregating all that data and giving you insight into the population as opposed just individuals as well. And then, from an operational standpoint, how we’re leveraging AI. Today, let’s say for every call a thousand customers we onboard, we’re gonna have to add one or two additional credentialing individuals. Right? So how do we automate our internal processes so we can continue to expand on that on that margin?

As we continue to grow, we don’t have to add those one or two individuals for every thousand customers. It can be one individual for every 5,000 customers or something of that nature. So how do we automate, our processes internally so we can continue to extract margin in the future? And then from a margin perspective, just to know, at maturities, these businesses on gross profit line, they’re they’re generating 90 plus gross profit margins on the g’s adjusted EBITDA. Call it around 60% adjusted EBITDA.

Just because that fixed cost nature of the data asset.

Unidentified speaker: That’s how artificial intelligence helps you though. Mhmm. But how do you protect yourself from?

Unidentified speaker: Yeah. That that’s a good question. Right? So there’s barriers to entry.

Camilo Ramirez, Vice President of Investor Relations, Red Violet: So as you can imagine, let’s say you wanna go out and and and start a business in this nature. You had the credit bureaus. They have the largest balance sheet as you can imagine. They have all the data in house. When they wanted to get into the market, it was a buy versus build decision.

And each iteration they they went out and bought the businesses just because of the the the amount of information that you have to gather and the type of information that’s actually beneficial. So a good example, early on we didn’t have business data. I if me saying that you’re like why wouldn’t they have business data. Right? Like it’s very integral to understand who owns businesses but it’s nice to have.

It’s a very expensive data set and there’s not much lift. It’s low ROI on that business data. So early on we didn’t have business data. We’d go out and when go out to prospect customers, they’d say, hey, they would love our product. They would say, hey, but you don’t have the business data.

And when you really dug in, they were doing a couple searches a month on the business data. Ultimately, once our p and l supported purchasing that business data, we layered in that business data and then today we’re work we’re starting to work on k k y b, so know your business. So, we can understand everything about a consumer and individual as your sole data point. We can know everything about a business as well. So LLCs, who are the true owners of these LLCs going down multiple businesses.

So being able to come out in the future with a KYB product as well. So there’s the moat and then the know how of what data to to acquire. And then the credit bureaus have to have high confidence in you keeping that data safe. Right? As you can imagine, they’re they’re not just gonna give the whole US population to anyone out on the street.

There’s a lot of risk associated with that. So we’re audited by the credit bureaus on a regular basis. We’re PCI level one, SOC one, SOC two certified, ISO 2,700 as well. So safety is at the forefront or data safety. I believe you had a question.

Unidentified speaker: How many sort of separate real estate deals do

Unidentified speaker: you have? And have any not renewed in the end of

Unidentified speaker: the contract period? And the second point of question is, like, would Uber be a particular customer possible?

Camilo Ramirez, Vice President of Investor Relations, Red Violet: Yeah. That’s a potential use case. Right? So the I’ll I’ll answer that one and I’ll go back to the other one. So Uber, right, they’re doing background screening on on, drivers as well.

So they have that high transactions. Yeah. They’re doing identity verification, make sure that’s a valid individual, that valid license and so forth. So that’s a potential use case. And then on the real estate side, here let me flip to the side.

So, today we service over five seventy five real estate associations. Again, there’s about 1,100 associations in The US From a real estate from a realtor standpoint, we’re servicing just about 350,000 real estate individuals. There’s about 1,200,000 real estate individuals in The US. Of those that are truly in the real estate business, call it about 900,000 real estate individuals are actually transacting more than one home a year that just don’t have a real estate license just for family and friends and so forth. And there’s no true competing product in in that space.

Lack of better term, most of the competing products are gonna be like find the body, so panic buttons once you’re attacked and so forth. But this is more of a proactive safety solution. Any last minute questions? No. Appreciate it guys for making it interactive.

Thank you.

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