From Language Models to Intelligent Teammates

Julia Nimchinski:
And coming up next, Team Vivan. Welcome to the show, Ryan, Director of Product Marketing, Brett, VP of Sales and Solutions, and Taylor, Senior Sales Engineer. Super excited to have you on the show. What’s the latest and greatest, and what’s new?

Ryan Radcliff:
Yeah, thanks for having us, Julia. We’re really excited to be here. Before we get going, let me share my screen, just so we have that up, and then when I can introduce my, My, coworkers here. Yeah, so, great to be with you, joined by Brett, who is our VP of Sales and Solutions, joined by Taylor, who is our Senior Sales Engineer.
We can’t wait to talk to you. We’re just gonna dive right in, folks. But something I want to start with. A forester analyst walked out of B2B Summit last week with me, and he said something that’s really been sitting with me. He said, as agents absorb so much more and more of this top-of-funnel work, like a lot of the scenarios we just saw.
Those human interactions that remain really have to be extraordinary, right? That’s the world that your sellers are already in, and I can’t wait to talk to you about what it really takes for those sellers in the moment to really win those moments, right? When things are really on the line.
So, as we all know, and this is a stat you’ve probably seen before from Gartner, 95% of your Gen AI pilots are really showing zero financial ROI. You’ve seen this, our viewers have seen this, our viewers have probably run one of these pilots themselves, right? The models are solid, the demos are compelling, but then nothing’s actually moving.
And the question is not whether AI is powerful. It’s clearly powerful. The question is why the architecture most companies choose to keep producing, gives the same result, right? The issue isn’t the model, the issue is that what we’re seeing is AI bolted onto systems that were really never designed for it, right? All these classic CRMs.
bolting on AI, and we’re not seeing the ROI that we want to see. So, we talked to a lot of sellers, we’ve talked to a lot of folks, you know, dealing with revenue, CROs, every day, and we really looked at the whole market, and I want to show you this chart. AI has really reached every stage of the revenue cycle.
Awareness, education, onboarding, retention, expansion. But that middle, I think, is really interesting. There’s two stages where the human seller is really in front of the buyer, in the live conversation, deal on the line. And that’s where we’re seeing so much investment drop off, right?
The urgency for first mover advantage that led everybody to the wrong problem, everyone around this moment. Most of AI in sales is optimizing for those stages that surround the conversation, and not for the conversation itself. And so. 50% of buyers are feeling very overwhelmed by technology in this space, another quote we got from Gartner.
And every tool that we’re adding to the stack is another system the seller has to manage when all they’re trying to do is really win a deal. Right, Julia? And none of this is really solving the actual problem that when a buyer shows up in a conversation, they’ve already done so much research, they’re ready to talk.
They’re giving you really 5 minutes of attention before they’re gonna check out. And the more AI that we kind of add around the conversation, the more that pressure really lands on the seller in that moment. So when a buyer asks something really tough that a seller hasn’t prepared for, they’re on their own more than ever.
And that’s why we think this is a really critical moment, where sellers don’t need just another tool, they really need a proactive teammate in the room with them.
They need something that’s going to surface what they need right in that moment that they’re having that conversation, they’re trying to build that connection, and they need something that really shows up where it counts, and I want to pass the mic to Brett. Who’s gonna show us what this looks like in the market today.

Brett Crane:
Yeah, thanks, Ryan. Yeah, so as Ryan mentioned, we have all the tools in the world before, and all the tools in the world after.
A lot of these tools are there to really help get the calls, curate who’s going to be on the calls, gather the information, and then after the call, you know, gathering that information, summarizing it again, recording it. But a lot of that’s in service of what I sort of might refer to as, like, the history book, right?
The CRM is this, you know, whatever it is, 50, 60-year-old history book, probably the most popular one out there right now, right, in the last 30 years, has been curating this history of data that takes place on sales deals.
So all these tools have been sort of stacking around that in service of everything sort of around the call, but the hardest part of a deal is actually, you know, it’s hard to prep, but when you get on those calls, all these tools are there to record, retrieve, summarize.
And they’re there a little bit before and after, but they’re not there in that void, the moment where sellers are most highly paid for to execute on that call. The rep is on the hook. under pressure, you know, when things go sideways, there’s nothing there to actually help them in that moment.
And so it’s not a, do I have enough tools problem, as Ryan mentioned, it’s do I have the right tools, the tools to service me when I’m on that call, in that moment, with my prospect. Go to the next slide here, Ryan. So what we’re thinking about here is, like, how do we actually solve for that moment when you’re on the call and you’re alone?
Sometimes you have some teammates there with you, but a lot of times you don’t. And so, these… we’re thinking about this as a system of action that’s there with you in the moment, with you on your deal. it thinks about the context that’s existed in the past, for sure, but it’s there to help you live as the conversation plays out, and as it unfolds.
So it’s a category shift of not having something just bolted on to service the CRM, or sort of write the pages of the history book, if you will. It’s there to really help run the deal alongside of you.
So Hero is there in, sort of, the three moments of, you know, where the deals, like, start to happen and shape around that call, before the call, on the call, after the call. But really, the during the call is where we wanted to focus a bit more today, because that’s the void that Ryan just talked about a moment ago.
That’s the void that we’ve seen, and we want to have sellers have the right answers, not trip over any hurdles during the race of their deal. They need to make sure that they’re highly paid to build rapport, they’re highly paid to distill the value of what you’re selling for their particular prospect.
And what we do is, in that middle zone when they’re on that call, we give them various modalities to actually get that value on that call. The first of which, Whisper, that’s invisible to the prospect, that allows your reps to, you know, maintain eye contact.
Be able to talk to your prospects, be able to be there in the moment, but get served up expert advice when things go off the rails. Hard questions happen, objections take place, things are going wrong about the call, we serve those things in the moment.
It’s not flooding their inbox, it’s just giving them the warning signals and the answers to the test when they need it, when it gets the hardest. Voice is there as a way to really prepare them for the future of what might be the way they can interact with their prospects directly.
So, hey, this is an important evaluation for you, I don’t want to waste your time, let’s make sure we have something in that moment that can answer your question directly. So if you want to bring voice mode into the picture, they can actually bring that on and directly converse with their prospects and customers.
Keeping that credibility, making sure that no time is wasted, and moving the deal forward. There’s also an avatar as well, too, so they can see a face and humanize the experience as well if they’d like to.
And then, of course, after the call, we do some of these things too, similar modalities where they can see coaching work together with our avatar, with our voice, to make sure things like not only are deal assets produced and the, you know, the history book is written up over in, let’s say, Salesforce, but also they get coaching in the moments of what took place just now that I can improve for the next time.
Go to the next slide here, Ryan. So, okay, so what does this look like in practice? A lot of tools are out there that we sort of refer to as, like, the generic LLMs, or the LLM as the brain. They’re really good at things like local reasoning. I give it a file, and I say, give me the insights from this file.
Or we get off a conversation, what did we just talk about? It’s actually a simple Q&A type of back and forth. Really good for a single source context. Where it gets sort of hairy and bad is this concept I’ll get to in a second of multi-hop reasoning.
So it’s bad at these, like, global, very big, complex process-type questions that happen all the time in sales, right? It can help you answer the next question, but it loses that through line as things get more complicated. So things like, hey, how do I win this deal?
It’ll probably look through a transcript, it’ll probably look through something, maybe you could provide it, like your sales process. And then it starts getting generic, pulling in web advice, things like that, start to sort of add hallucination, add some generic nature to it. And that’s just more retrieval, not strategy.
And so Hero is built a little bit differently. What we’ve done is we’ve actually said, hey, we need a real reasoning model, a full knowledge graph to underpin how this thing works.
And what a knowledge graph is, for those of you that aren’t super technical, is It’s kind of just think about it as concepts, referred to as nodes, and then connections between these concepts referred to as edges or relationships, so things like what products you sell, what’s your sales process? Who are your competitors?
What products do your competitors sell? What do the prospects need? Other deal contexts. All these things are interconnected things. So when you ask for a how-to in a deal, all those need to be considered in the answer.
All those things need to be first-class citizens of how that answer is crafted in order to actually be a useful answer and useful advice for brand new sellers, because they have to get it right, or even experienced sellers who generally know how to sell, because they’ve been doing it before, but they might be in a new domain, or they might have been asked a question they never heard of before, or maybe they’re a really good seller that knows they don’t need to be the most technical expert in the room, but they do need to offer that credibility in that moment to keep the deal moving forward with maybe a thorny IT person or something like that.
So, all those things are really the line that we draw between LLM as the brain and actually having a strategic partner by your side an AI sales team that works through, hops through all those complex problems, and actually gives you an answer that you need in the moment.
So, to get a little more technical and give you a sense for how this all works, let’s go to the next slide here, Ryan. I don’t mean technical in that I’m going to talk about APIs or things like that, but one of the things that we realized was, hey, we should actually prove that this works.
And so we took the best of the best frontier models, and we said.
What would questions that come up in sales conversations look like when you use LLMs as the brain versus use domain expertise applied to the LLM so the LLM becomes more of the mouthpiece to structure sentences correctly, and the brain or the reasoning model of HERO is applied on top of that to make sure a complex question is actually answered in a way that’s useful to win a deal.
And so what this graph shows you is that In a sales conversation, typically, when you get asked a question, it might sound simple, like they might ask you a functionality question or something technical. What you should do to get a strong answer as a seller is say, hey, what do I know about what we’ve discovered so far?
What are the business outcomes they’re trying to drive? What are the criteria they actually have in their evaluation? Is it scored high priority, low priority? You know, what are the capabilities our products actually have? Do our competitors have these capabilities? You know, are we kind of screwed on this deal?
Is it going to be time-bound, tied to value that they’re going to actually buy our product from?
All those things should be under consideration when you give an answer, even to just a functionality question, because sometimes you don’t have that functionality, or you have something like that functionality, but there’s a better way to describe it based on what you know about the deal, and how you guys sell, and how you beat your competition and box them out.
So what does that mean when you look at a graph like this? Well, typically, the cliff happens at about 3 hops. So when I mentioned that a sales question typically is 8 to 12 hops, it goes through those steps of, what do I know? What about my competition? What are the outcomes? All those things are hops in the chain.
And you may not realize this because sometimes you’re chatting back and forth with an LM, you actually correct it all the time, you give it context, but the thing you can’t do on a live call is do that, right? It can’t ask you for clarifying questions, it can’t ask you for wrong things that you have to correct, right?
This is where we put all the work in to make sure that all this stuff happens. in under 3 seconds, when you get a really difficult question on a sales call, you need that help in the moment. We’re targeting, you know, 1 to 3 seconds of.
Question detected, expert answer coming back, that reps can actually use in that moment to drive the deal forward, show that they have the confidence, the skill, and the teammate by their side that they can choose to show or not show on that call to move the deal forward and really make a material difference.
Alright, so with that said, I want to kick it over to Taylor, I think, at this point, to showcase how this works in a demonstration.

Taylor Bukowski:
Awesome. Thanks, Brad. Let me go ahead and start sharing. All right, so excited to show you all, really how I work alongside my AI teammate. Now, if this was a real customer conversation, I would be able to jump into that call directly here from the homepage, and join that, call with my teammate, hero.
But because this is a webinar, I’m going to show you guys just a quick clip example, and then we’ll get into some more of the demo.

Unknown:
Audio shared by Taylor Bukowski: Jonathan, great to see you again. Happy to pick up where we left off. What’s on your mind? Audio shared by Taylor Bukowski: Yeah, great to see you again as well, too. As I mentioned, a couple of questions for you. My CISO basically pinned me down on a few items.
The main one is, can you tell me about your encryption policies and data storage and retention as well? Audio shared by Taylor Bukowski: He’s got a lot of questions, Audio shared by Taylor Bukowski: I’ll do my best. Look, I’ve only been here for 5 days, as you know. First of all, absolutely, right, data is encrypted at rest and in transit.
Audio shared by Taylor Bukowski: But in all honesty, Jonathan, I’m not the expert, that’s why I’ve got my teammate on the call. Hang tight, they’ll be able to help us give you the details that you need. Hey, Ava, could you answer that question for Jonathan about our data encryption policy? How does that work?
Audio shared by Taylor Bukowski: Yes, Jonathan, your data is encrypted both at rest and in transit, and we adhere to SOC 2 Type 2 compliance standards.
Audio shared by Taylor Bukowski: For detailed information on data storage, retention policies, and security controls, we have a vendor security questionnaire available that covers encryption, tenant isolation, identity access management, and incident response.
Audio shared by Taylor Bukowski: Ava can provide you with the full details, or share the security questionnaire for your CCISOs review. Audio shared by Taylor Bukowski: Cool! I’ll be able to send that over. Do you think that, is gonna work for your CISO? Audio shared by Taylor Bukowski: Yeah, that’s perfect.
Glad you were able to answer that for me. And just one last thing, after this, can you just send me over the full value case so I can share it around with the team internally and discuss with them as well? We’ll do it now. You’ll have it in your inbox in, 5 minutes. Thanks, Jonathan. Audio shared by Taylor Bukowski: Awesome, sounds good, thank you.

Taylor Bukowski:
So the idea there was giving you guys a flavor of what that would be like to actually have Hero on a call with you directly. So it’s that proactive teammate that’s working alongside you, helping you on your deals, not waiting for a prompt. It will pop up proactively anytime you have those conversations to help you in the moment.
And additionally, if you guys want to try this out yourself, you can also go to meethero.ai and participate in the simulator. And that’s another great way to actually get hands-on and see what it would be like to work with an AI teammate. So I’m going to show you just a quick intro to this, and then we’ll jump back into the product.
So you’ll see I’ve already been briefed on the left-hand side with all the information, and now we’re starting the call.

Unknown:
Audio shared by Taylor Bukowski: Hi, Morgan and Ellis. I’ve got a hard stop in 15 minutes. Jennifer from the board asked me to take this. What are you hoping to cover?

Taylor Bukowski:
I’m Oregon, no problem, I’ll keep it tight. In the next few minutes, I’d just love to understand where your team is feeling the most friction in the sales process, and whether or not it’s before, during, or after the call, because we really think Hero can help.

Unknown:
Audio shared by Taylor Bukowski: Got it. Just so you know, we’re already looking at a couple of conversation intelligence tools for the team, so if this is in that category, I think we’re covered.

Taylor Bukowski:
That makes sense. I’m not trying to replace, what you’re already evaluating. The reason teams look at Hero is that live moment, so when a rep gets asked a question they can’t answer on the call, what happens today? So, you’ll see.
Please go experience that for yourself, at the full, sim at meethero.ai to really understand what it would be like working alongside that AI teammate. Now that the call’s finished, I’m wrapping up, I have to make sure that I’m taking some action, and I’m updating the rest of the team. So when I think about that, where I go to is the My Deals tab.
And here I can see all the deals that I’m currently working on with those proactive suggested updates. So… Here, you’ll see my proposed next steps. I can see the source of where this is coming from. I can also view the existing, if I want to know what was in there before. and then push directly back to your CRM or your system of records.
So this is doing all the admin work that I hate, proactively doing it for me, no prompting required, and I don’t even need to leave Hero to update any of this. Now, if I want to get the full MedPick breakdown of my opportunity, I can actually jump into that space directly and see my deal review.
So, here, we follow MedPick at Vivint, so that is how we like to have our deal reviews. So all of this is organized in my preferred sales methodology. I can understand the strengths of the deal, the gaps.
what the recommendations are, and then if there are any areas that look weak, I can drill into those even further and understand what I need to do to keep this deal moving, and what supporting evidence is actually supporting those claims so I know exactly where all the information comes from.
And when I need to go ahead and update my entire team on this, that’ll be pushed back directly into Salesforce, but additionally. We chat a lot over Slack, right? We have our team channels, our op channels, so that we can keep everybody up to speed on everything that’s happening, and they’re not on every call.
They don’t want to have to sit there and go through all the notes or the recordings. So here, within my Slack channel, with all of my teammates, I can just ask hero for a summary, and get that full breakdown on what’s going on with this deal, the status, recent activity, blockers, and then what the immediate next steps are.
Again, everything’s cited here clearly for all the information on where this is coming from. Now, the last thing I want to do is, you know, work on a little bit of strategy for my deal, and help to move these things forward. So for that, I’m actually going to pull up the avatar and ask Hero directly, and see how we can push this deal.

Unknown:
Audio shared by Taylor Bukowski: Hello, Taylor, what can I help you move forward on in this deal?

Taylor Bukowski:
How would you pressure test this deal if you had to forecast it today?

Unknown:
Audio shared by Taylor Bukowski: I’d pressure test it by checking whether the deal has a confirmed executive sponsor. Audio shared by Taylor Bukowski: Clear business pain tied to a quantified outcome, and evidence the buying group is aligned on next steps.
Audio shared by Taylor Bukowski: I’d also verify the current stage is supported by real actions, not just optimism, and look for any open risks around tech stack fit, procurement, legal, or data residency.

Taylor Bukowski:
Thanks, Harold. So, hopefully, we’ve shown you a little bit about what it’s like to work proactively with an AI teammate. And with that, I’m going to turn it back over to Ryan to wrap us up.

Ryan Radcliff:
Thanks, Taylor! That was awesome how you showed different ways that if folks are interested in Hero, they can get in an experience, right? There’s a simulator, there’s a free trial we’re gonna talk about in a second.
There’s all these avenues for really getting in and checking this out yourself, and That’s why you got to see this in practice, you got to see what’s underneath it. Folks, this is not a co-pilot, this is not a workflow trigger, this is not some summary generator feeding another version of a history book, right?
Hero really thinks and acts like your best seller. Excuse me, because it reasons over the same structured knowledge that your best seller carries in their head.
It runs your sales process according to how your business actually works, it integrates with the tools you’re using, there’s nothing new to manage, and I want to transition to this slide and kind of talk about what we’re seeing in the market.
I know we’re all kind of coming here together today and talking about different solutions and Really examining the market, and… I just want you to see here that we’re not the only ones who are really saying this, right?
Gartner published research in February this year, specifically on AI agents that ride along in live sales conversations, and their projections are really fascinating. excuse me, 20% shorter sales cycles by 2027, 40% less training time by 2029.
This is a category that’s really arriving And I think the question for your team is whether you’re in it now, or you’re gonna be catching up, later. And we want to show you a few of the companies that are really in it now. These are 4 of our customers. Each one of these came to Hero really from a different angle, and landed in the same place.
And I want to focus on this first one here, ADP. ADP came in with this very specific problem. They’re in a very highly competitive space, a very complex product set, and sellers who couldn’t always get an SE on the call. And with Hero, they’re seeing 30% improvement in win rates.
A measurable lift in deal size, they’re not changing headcount, they’re not pulling specialists into deals they shouldn’t need to be in. The future of sales won’t belong to teams running the most activity, deploying the most tools. It’s really gonna belong to these teams that win these moments that decide deals.
So, if you’re interested in what you’ve seen, there’s really two great ways to get started. You can try it yourself at meethero.ai, either through the simulator that we showed you, or through a free trial that we talked about. But also, exclusive to HSE today. You can refer your team through this link I have up on the screen.
You can choose 3-5 reps, and they all get hero-free for a year, and then you get custom insights, and you also get a gift. For your team. So, and it’s pretty significant as well. So, I really encourage you to check out that starting 5 deal that we have there in the middle, and get a bunch of your reps on there, for a whole year.
Humor and seller interactions are getting fewer, they’re getting more important, and we believe that Hero is really the way to make sure that every single one of those moments is going to be as extraordinary as it needs to be.
And with that, Julia, we’d like to open it up for questions for the team, and I’ll just keep this up on my screen so folks can get activated.

Julia Nimchinski:
What an amazing presentation, thank you so much. We have a lot of questions here. So the first one is… A question from your users, actually, and they’re asking, any chance you’re working on an AI agent to auto-update activities and gaps would be a massive help.

Brett Crane:
Yeah, so I’ll get into that. Today, we actually do capture their calendar, right, through the integration we have with their calendar events. And then separately, in the conversation, we do detect for product issues that may be arising in conversation, and those things are actually made available.
We call it a popular prompt, but when you click it, it allows you to see what things came up in conversation that might be considered product deficiencies or product gaps, as they’re probably referring to here. So there’s a couple of components in the product that actually does this already.
And of course, we’re a multi-product company, so we have a platform that’s more directly geared towards pre-sales that tracks a little bit more of that, but this Hero product is specifically more geared in the zone that you saw today, which is helping sellers, which could be salespeople, SEs, TSMs, whatever your role might be in the go-to-market space, and it does have components of Capturing what you’re doing with your deals through your calendar integration, as well as capturing those product deficiencies or product gaps.

Julia Nimchinski:
Awesome, and can they hand, emails off to Hero, too?

Brett Crane:
Sorry, what was the question? Hand emails or detect emails? What was it?

Julia Nimchinski:
No, can just hero process emails as well, can…

Brett Crane:
Oh, yeah. Yeah, actually, we just, we just got out our email integrations for both Gmail and Outlook. So, in the last month or so. Now those can be used as information to drive the context of the deal, and really give more information that can be used right in that moment of sales calls as well, too.

Julia Nimchinski:
Amazing, and there’s another question, more philosophical one. What’s the difference between a teammate and a sophisticated co-pilot?

Ryan Radcliff:
Yeah, that’s a good question. What I really like about what we’re doing with this teammate is that this is something that’s sitting proactive on your call, and it’s with you for the whole life cycle, right?
You can build an agent to update a CRM, or you can build an agent to sort of help you role play, or maybe you can really get into it and try to come up with what we’ve come up with on the call. But the reason why we love this teammate framing is that you’re getting something that’s with you from 9 to 5, every day.
You log in, it sees your calendar, it sees how you want to prep, it’s with you on the call, giving you all those moments and all those things that you need. and then after the call, it’s automating all those things.
And so that’s why we think this is so much more than just an agent, and this is clearly more than a lot of the big players are doing with their co-pilots.

Brett Crane:

And domain expertise, I think, is the separation that we talked about today, so hopefully that’s set in a bit, where We have put a lot of thought of knowledge engineering into how salespeople think, should think, the context that matters the most to win deals, and that underlying knowledge graph and the decision-making that goes into how we provide that guidance and how we work alongside as a teammate is the thing that we think separates us, because generic tools like a co-pilot are great, but there’s a lot of building that goes into it, and shifting around that require IT help or other technical resources to help set this up.
Our product actually can be implemented… you can go to the website right now and try it out, or if you have a more complex setup. want to layer in your sales process or other things, too.
We typically see customers getting live in just a couple of days, and we do free trials of our product as well, too, to make sure they get hands-on and feel the difference.

Julia Nimchinski:
Another question here. Do you have issues, with the AI understanding accents on the call? And, what can you share about the latency, Brett? Perhaps, does it occur on an ongoing conversation?

Brett Crane:
Yeah, so, the product has a variety of ways that we interact with the different modalities. One of the things you saw today in a demonstration was speech being… things being said in speech, that being translated to text. You also saw not only just the text space, but also voice-to-voice, so that goes through that… that different path.
But depending on the modality, what we’ve done is we are constantly monitoring and testing and evaluating all of the current state models. Like, even this week, we moved up to the latest GPT-5 models, and we tune all the time for performance, so you, you know, we gear ourselves towards, if I’m in a conversational moment like this.
I need to be able to have latency that’s acceptable for a question being asked, an answer being surfaced, and inserted directly in the conversation. So when I said that 3-second limit, that’s really important for us.
We strive for much lower, but our Our endpoint can’t be much higher than that, and so that’s where we start to use things like mini models, nano models, and other things to make sure Text transcription, voice outputs are all going to be in time to keep the conversation flowing.

Julia Nimchinski:
Amazing, and last question, we have one minute here. I’d like to address the uniqueness of Vivint. We showcase a lot of solutions, and it feels like the market is, you know, gotten larger and larger. So, what can you share about, you know, the way you go to market and your product? Why Vivin, why now?
And, yeah, all of you, Ryan, Taylor, and Brett. Can we realize.

Ryan Radcliff:
Yeah, absolutely. What I’m really excited about is how we’re going to market, is that folks today have no patience on a call, but they also have no patience for a deal cycle. And so what I love about what we’re offering is that you can get in and you can actually try this and get into a free trial.
And I think when you think of GTM, that’s huge, right? We’re not signing you up for a 6-month long procurement process where you’re going to hope that this works at some point. when we finally sign you up as a typical enterprise.
Our team has really built the ability for you to see this right now, today, and then we’ve got this deal where you can get it for your whole team for a whole year. So I love that we’re really putting our product to the test, really allowing you to get in with a freemium model. I think in this day and age, that’s the only way to do it.
Brett, do you want to add to that?

Brett Crane:
Yeah, sure, and I can pass to Taylor for a second, too. I think we’re out of time, but yeah, I love the model we have now, which is you can come in, experience the product for free, no friction, get in there, and if you want to engage with the sales team, someone like Taylor, I was gonna pass to Taylor, because we also offer trials, right?
So, Taylor, I don’t know if you have, like, a word on our trials as well, too.

Taylor Bukowski:
Yeah, I was gonna say, it’s been awesome that now we can actually get people directly into trials. You can try out the product, you can see how it works with your actual data. That’s something that we weren’t always doing, so from my perspective, I love doing that, because the proof is really in the product.
Being able to experience it, being able to have that ride-along agent, it’s been huge for us, so yeah, come talk to us.

Julia Nimchinski:
Awesome.

Ryan Radcliff:
This is our big week. It’s May 5th, we launched a couple days ago. Julia, thanks so much for having us.

Julia Nimchinski:
Our pleasure. We love Team Vivin, love your products and everything you do. So, see you soon on the next AI Summit. Thank you again, and we’ll share the links with the community.