Jim (00:00.066)
What holds people back from using AI?

Justin (00:03.446)
I I would probably say imagination. maybe even hope in a weird way, right? Is it's like I hope this can do it for me.

Veer (00:15.32)
Welcome everybody. You'll notice it's a little bit different this time if you're watching, because there's three boxes instead of two boxes on the screen. and so we've got a special guest today. And so, you know, a lot of guests or a lot of executives, they're still using you know AI as a chat box. Justin's not doing that. He's building where AI has to answer a phone, use real data, make right handoffs.

it needs to make good decisions and it needs to create real results and that's that's just a very different point of view of a of a practitioner versus a user.

Jim (00:51.99)
Yeah, and it it really raises a question, you know, a lot of other people aren't asking right now, which is who maintains it? What happens when it doesn't work the way you think it's gonna do, or you get a wrong output from AI? So when can you trust the data? And then I think really critical nowadays, because people are leaning in heavy in some cases, when do you build, buy, or just you know

run a model internally yourself. I mean, all of those things are I mean, they're ROI questions. They're near and dear to me as a CFO because I want to make sure that I'm I'm spending the money the right way.

Veer (01:32.876)
Yeah. And so Justin Ray is the founder and CEO of Cinch. He's been working on the data gap between large companies and local businesses since long before like Gen AI was on the scene. So he's got a long

Jim (01:46.958)
Long before the I mean, you're dating him. That's that's pretty rough, man. First guess right out of the

Veer (01:53.39)
Justin has been working for a long time on this and and I think you're gonna be able to give us a really great like perspective on how the the world has shifted over these last several years, especially. So Justin, thanks for joining us. Yep.

Justin (02:20.29)
Good to be here.

Veer (02:22.274)
Well yeah, so why don't you give us a little bit, you know, you know, as you talk about cinch, you know, and you know, give us the short version of the path of like, you know, maybe customer data to, you know, reminder marketing to the cinch that you're building today.

Justin (02:37.378)
Yeah. Yeah, no, defin definitely. The the biggest, most valuable thing. I mean, we've heard for years and years data's the new oil, right? Those, you know, ten, fifteen years old type of mantra. But but it really is still true, right? Is the fact that having good data and being able to manage that data in the right ways is becoming even more valuable than it was before, right? You know, you're not just connecting that to a

BI tool and being able to get some insights out of what what's going to happen there, right? You're actually able to take action and work from that. And that's really one of the the core things that we've done at Cinch is we've really focused on how do we ingest as much data as we can and then match that up to a single source, which in our case we're focused on the customer. How do we know who the customer is? And then we know all these behaviors. We know what they're doing, how they're interacting with you, what is their relationship really like? And you know, one of the things that we really want to do with that is like.

How how does it turn into a virtual representation of the times when you could walk into a store and the store manager or the person in the store would know you, right? How do you turn that into that same type of b type of experience in a virtual world, right? Or in these digital or or the the AIH, right?

Jim (03:48.076)
Yeah, which is where most of this is happening now too. I mean, face to face is not a not nearly as common as it used to be.

Justin (03:56.314)
Yeah, you know. We've got so many more people and so much more consumerism that we're trying to get out the door and how do we in interact with it a lot faster?

Veer (04:06.03)
I guess for you as as giving a little bit of you more background about, you know, kind of, you know, cinch and the work that you're doing. I mean, you know, you s me you mentioned the oil, you know, like this the data's the oil and and that's where the value is and and you know, how's that become how has that become more valuable as you know, we're we're using different types and forms of AI?

Justin (04:26.69)
Yeah, I mean just being able to access and and make decisions relevantly relevant to the data that's happening. Right. What w at Cinch, we have for years used machine learning since our since our initial launch. We included a lot of different machine learning about how a customer interacted with a business. And a couple of those ways, number one is like customer valuable. How valuable is this customer to the rest of the to the business?

relative to the rest of the customers in that database, right? And so if that customer is moving up at the same trend, like most most people's database, they they're engaging, they're becoming more valuable to their customers. And so their customers become more valuable slowly at a like a linear path, right? If a customer is not moving up with the rest of the path, then they're actually becoming less valuable, right? This this especially happens when

You know, you've got pricing changes, or you just got, you know, over you know, if you've got a customer over the you know 10 year time period, right? Your pricing and what you offered 10 years ago is different than what it is today, and right. So that that monetary value has moved up and to the right. If a specific customer didn't and they stayed, maybe they're still spending the exact same amount, right? And you can't look at that and be like, yeah, they're still the same value. No, they're not the same value because the rest of your customers have become more valuable.

And so they become less valuable. And how do you look at that in a weighted way? That just the same way that an LLM applies weights to all the different words and processes that it's going in its decision making, you know, we're adding weights and measures to each of the interactions that a customer has, right? And over time, how are those changing? How are they getting better or worse? And so so we're we've been putting things like that into the process. We have things like pricing sensitivity, which tell us.

Hey, this customer's always using a discount and it's the deepest discount, or they never use a coupon anywhere, right? Those are the types of things that become really valuable at helping to dive in deeper to using that data. Like you said, it it it is it's the more valuable oil now because you can get more value out of it. And so you can dynamically change a coupon on an offering because we know this person's pricing sensitive, right?

Justin (06:41.142)
Maybe you even give them you know they're high value customer. They've always been high value, but they're always pricing sensitive. So if you give them that discount, they'll probably come in more frequently. Or you don't give them that discount, they come in less frequently, but still spend the same amount. And so those are the types of details you can really start to get into now at the granular level and you can personalize that communication in ways that were really limited before, right? You still had to work in an aggregated level with most of your customers.

Veer (07:09.006)
Well, and and I've like I f it feels like that, right? The idea that we had to work in cohorts and and and and and we had to stratify and and and kind of build kind of right, we would A B test things and and try to figure out a way to to prove a hypothesis. And now it feels like you can microtest that and have a way better shot at getting it right because you're seeing a lot more trend, like you're saying, at at this really granular level. Like I know Jim.

I know how you know, I know he likes to cut a coupon.

Justin (07:42.71)
Yeah.

Veer (07:44.376)
Yeah.

Jim (07:45.866)
Yeah, I I I completely agree. I think, I mean, from what it sounds like to me though, at least just what I know of Cinch, I mean that A B testing now, it's it is happening, but it's happening rapidly. It's happening like basically around the clock, just to try to figure out what the next insight is and the next unlock is to to be able to sell the next widget.

Justin (08:11.062)
Exactly. I mean a a a really cool use case of this recently is just being able to customize tones of an email, right? And so you still kinda work in a certain level of cohorts, but you can identify, you know, hey, what what tone does Jim need? Jim needs the educational one and Veer needs the urgency one, right? And

And so changing the content of that email, changing the subject line to get you opened and engaged, right? Those are all done by A B testing and a machine basically trying to say, okay, well, I'm gonna shoot over this one's gonna be the gym in a social proof tone, right? And so I mean from where we're going is we have about 10 different social proof or we not social proofs, but we have about 10 different tones that we're trying to place customers into and identifying, okay, when you're trying to do this type of thing.

You need this tone, but when you do this type of thing, you need this tone.

Jim (09:05.912)
Do you see it stopping though at ten tones? I mean, like that's the I mean, just kind of going back to what you were saying earlier about how granular you can get things. I mean, seems like eventually this will be Jim has a tone, Veer has a tone.

Justin (09:20.012)
Yeah, I think I think there's still gonna be certain cohorts, right? When you think about human and consumer behavior, right? People there are certain groups of people that tend to behave very similarly, right? and so you'll probably get down to like get down to that, but you'll have a whole lot more, right? You'll your cohorts will be many, many times more. but you'll still have certain groups of people that'll behave and interact very similarly as far as that goes. But I think some of the other things that are really changing that are really cool are that

You know, you can you can have the subject line and ba general content that is similar for one customer, but then you can get, you know, or you can have the tone as the same, but you have hyper personalization where, you know, maybe you're taking and this is again bringing all that data together, you're taking information from a phone call that you had with the customer or a text conversation and you're able to bring that in, right? Maybe maybe you're selling shoes and you had a conversation with somebody

Or they're chatting with a in a chat bot and they say, Yeah, I really love to run marathons. And I feel really lucky anytime I sell blue shoes, right? Or excuse me, I I I wear blue shoes. I'm gonna I'm gonna really do great, right? Those are my lucky color, right? Now I've got some extra blue shoes in their size that are coming out, right? I can dynamically send those over and be like, Hey, here are your lucky blue shoes, go buy right? Those are the types of things that it can become you know, you still have like cohorted tones.

But now you have hyper personalization based on a lot of the data that's coming in and that you have on this customer profile.

Veer (10:52.344)
Well that I mean like that's excit like that 'cause I mean from what you were saying, you have hopefully at some level you've got like ten, fifteen, whatever it ends up being that are statistically relevant tones and but then you can mix them right down at this like micro segment level with like, but Veer likes blue shoes and you know, he he you know, he he likes when the twenty percent off sale happens and yeah, that is power.

Jim (11:20.526)
One of the one of the things that I want to ask you about is so you're doing all these really powerful things, but if you could possibly tell us, just give us a little glimpse into maybe what your stack looks like. Now I know there's some secret sauce in there. So whatever you feel comfortable talking about, but what is, you know, how do you as a practitioner go about implementing AI not only into the product that's consumer-facing, but also into your back office and just

into the DNA of your company.

Justin (11:51.028)
that's there's there's a lot to that, right? And it's it's not one of those that happens overnight. You know, we've been working with this stuff and trying it for a while and and going going forward with that, right? I mean we as far as our software goes, we have a pretty typical software stack using Postgres, using Snowflake, using React as as general aspects of and and Python and how the actual product works, but then we're able to connect in and bring in

you know, things like anthropics API and using the cloud cloud in that scenario. We have Gemini, we have Codex or we you're able to work with Open AI as well as with their aspects and and and then we have local models. And so I think yeah it's really interesting because you have that that's what happens product wise, but as you kinda highlighted there's also the like operation side of things and how do we how do we function and work with those and you know one one of the cool things I think

we started doing in 2022, we actually were even telling our team, hey, AI is gonna be the change here, right? I want my team to know how to use AI. And so we gave everybody the chance to use Chat GPT back then, telling them to try to come up with it. We had little contests and we've actually continued to do this since then, is having contests off and on about who can do really cool things with AI. Like, let's go try to do this thing and or go try everybody would come up with something that's gonna be more valuable, bring it to

The team and we'll give out gift cards to whoever wins, right? we actually did a complete conversion in the team or in in Cinch in late February. We cut everything over, it maybe early March, we cut everything over to Claude, and we were using the Claude desktop app, right, once that came out. And and you had Claude co-work, you had Claude Code all inside of one single app, and we did the same type of thing. We basically told everybody.

Build something that is going to make you more effective in your job and then come share it and we actually voted on it as a team, then we had the leadership vote on like what it would be and and we picked who won based on how efficient that make it, right? But so these are the types of things that while like the stack can be changing constantly because, you know, the world's changing so fast this way, right? But how do you culturally build the the opportunities for people to be able to do that, right? And that's what we've really

Justin (14:15.786)
focus on as far as that goes. we haven't yet gone to the point where I'm willing to buy everybody a Spark box, the Nvidia Spark and and put it on their desk. But but I think that if we did get to the point where where I knew that people were going to create the value from that, I wouldn't even be opposed to that, right? Is having that local model to be able to run through and and just have something constantly monitoring where they don't have to worry about tokens. You know, it might not be a a frontier model, but it's going to be able to do some of these things that

You know, six months ago, honestly, you couldn't do with a frontier model. You can do on a local box now.

Jim (14:50.858)
If you would, I mean, just y you know, I'd love to hear a little bit about some of the wins that you saw. And then I'd also like to know where you've seen maybe function by function, whole use of AI spurring like creativity, efficiency, where have you really seen that take off? And where have been some of the places where you're like, man, I really wish that function would have latched onto it a bit more? And yeah, you know, because I can imagine in your mind, it's like, well, there's a priority stack.

So you're paying closer attention to some functions than others.

Justin (15:22.2)
Yeah, no, I think in that priority stack for sure has been engineering, right? We've we've heard just all about how you can build so much faster and plug things together. So definitely the R and D team, so our product and our engineering teams, being able to work out and get things going there. did you have something, Beer?

Veer (15:42.958)
Well, I was gonna say, like as you're kind of talking about like, you know, part of it is, hey, you know, it sounds like folks are using it, you're getting it into the hands of end users, desktop workers, knowledge workers, engineers. I think we all I mean, like you we have talked before and we we we have wins. And I think an interesting way to maybe kind of like highlight is it's like what hasn't worked? Right? Like what what w you know, like what what did you try? You're like, wish you could or you know, like you know, like 'cause I feel like that is where, you know, every st every you know, trip and stumble

Right is like a like, I learned something and now I you know, I'm do this better the next time and you know, trying to let folks know that even those of us that are using it all the time, we still trip and stumble every once in a while too.

Justin (16:23.416)
Think you actually hit it perfectly on the head, how you said it, right? As we learn, we trip and stumble, and then we try something again, right? I mean, this is the you know, the the whole practice of everything, right? Test and test and repeat. And the aspect of how often are we giving context? What context are we giving to an AI? And then we're we're seeing what it does, and then we do it again, right? It's just a matter of iterations, right? And

And you know, we were talking before a little bit about how sometimes we feel like we're getting behind because everybody else is moving faster, right? But the truth is, is that's just us like everybody's getting these at bats. And the more at bats you get, the more experience you have, the more conversations you have, the more you get to learn from somebody else's. And so you gotta be having some both of these. But what's really fun about it, that's exactly how the AI works, right? And so if you're learning and you're the kind of person who really likes to get the at bat, even if you're gonna fail.

And you're like, I know I'm I'm fine. If I fail on this one, I'm just testing, I'm just seeing what I can do, but I wanna see what I could get out of it, right? And you get the result or you don't get the result, but you got the same thing with the AI. And you and that's what becomes really cool is is in especially as we start to think about how do we how do we replicate this or how do we help teach people this is how do we give it the context we need, how do we let it try something, how do we let it get the results of the the trial that it had and then go back to it, right? It's it's just a re rinse and repeat process.

Jim (17:45.518)
Question for that is, and I've I've actually written about this a bit and would love your take. What holds people back from using AI?

Justin (17:54.024)
I I do think it's a little bit of like understanding what they can imagination. I I would probably say imagination. You know, it maybe even hope in a weird way, right? Is it's like I hope this can do it for me, right? But on the same side, because AI can have all its wonderful hallucinations, you also gotta like be able to have wins. So maybe it's the fact like, could it do this for me, right?

And I hope that it can because I imagine it should be able to based on other things that I've done. I've seen it do this. and I think that maybe that's just it goes back to iterations again. Like what what do you do? Like what what maybe holds people back is the general aspect of of the other things that they've done or the way that they've used technology, right? you know, it's l like we of talked about at the beginning, it's not just a chat bot anymore, right? It it's

It's getting work done. It's building it's orchestration of multiple agents that have specific tasks of their own and those tasks get done and and commingle with the other tasks of of other agents, right? And and that stuff just builds on top of each other. I think maybe you guys have heard of Hermes, but Hermes has their stages, their levels, right? And you can g hit the different levels of of Hermes and

and kind of grow into those. And I saw a really great YouTube video kind of explaining and walking through that. And I think that's the same thing for anybody. And if you can have a good experience at that base level, you can start to move up. Right. And it's how do you get people to have that good first experience? And I think that maybe going back to the long way of answering question, Jim, is it what holds people back is they haven't had that first good experience yet.

that lands them in like the aspect of I can imagine what this could do now over here. Like I imagine more that it can do. there's a period of time where I feel like if people were using Chat GPT, they probably weren't having the best experiences that the people that were using Claude were. Right. I think that's changed today, but I think late last year that was definitely the case, right? Especially maybe even the first quarter of this year. And so you you're just like, I can do this. Like but I think that's how it needs to work, right? You gotta be able to

Justin (20:12.724)
know that you can execute something and believe it's gonna be worth your time.

Jim (20:17.23)
Yeah, we definitely want to hear from you. I I don't want to interject too much, but I think our my philosophy and yours is somewhat similar. although I didn't have the nuance on the first experience, which I think is a really like that's insightful. That's a takeaway that I'm going to steal from you. but my whole thing is is I don't think it's fear. I don't really think that fear is holding everybody back. And I don't really think it's laziness. I don't think people are super lazy.

I really don't. They're working hard all day long. Just to build on what you said, I think that having founders like you or business leaders or champions for this like you, allowing them the space to have the good first experience is what is holding a lot of people back. They can't get out of the hamster wheel of I've got to get this report done. I've got to this is for knowledge work, so I'm

But maybe engineering is the same too. You guys are better to speak to that. But in knowledge work, it's like, well, I have to get the cash forecast out. I have to get the financial model done. I don't have time to sit and re engineer my entire process if the board needs this by tomorrow. That's my take on it. So I think you have actually solved this is one way to solve that issue is just giving your people space to learn.

Justin (21:40.654)
Yeah, it's definitely been really great. You ac kind of asked about some of those wins that people had had. And it was when we did that contest this earlier this year, we we saw some really cool things, right? We saw our customer success team was focused on like, hey, how do we support our customers better? How do I how do I more efficiently manage my time to make sure that I have time to deliver really good value to the customers I'm trying to work with, right? Once you have people that were like,

Build in an agent that was going to using cowork. Go through all of their emails, go through the support tickets that came in, highlighting the customers that they've had and highlighting, you know, what are the the the issues that are gonna have a bigger impact and trying to prioritize those so that they can tackle those faster. they we had on our sales team something very similar in the aspect of looking at the email. How do I follow up with the prospects faster? How do I answer the questions and

having an agent that's that's finding the answers for the the sales rep. we had one where the trying to do a demo in a way where you could mask all of the information that was on a page, right? And so you could basically we have like a demo that's built out for the Quick Loom or oil change space, right? And they he made it so it could mask it to display pest control or it could display

It just basically would change it to make it look like the data was somebody else's, right? But there was still an underlying thing on top of that. And that was really cool. what else do we have? We had like analyzing digital the digital ads and how some of those function. So just all of our teams are coming up with the things that like we're trying to solve their problem. And it was really cool to just to see that people were doing that and we'll probably be doing another one again here here soon just to see how things have changed.

specifically trying to get people to try agent orchestration, right? How do you take two agents and get one agent to do one thing and another agent to do another thing and then them to interact or an an a an agent to work off of the two of right? And see what we can do to with our team. That's

Veer (23:49.902)
That is really cool. Like I think like to kind of tie like Jim kind of brought up the fact that like urgency, tyranny of the urgent, right, is is maybe something that holds people back. And and I don't want to, you know, like like like lose the thread where, you know, it feels like, you know, because what you've shared with us already is one, you've created space for your teams to be able, and you've created incentive, which I think is should be a takeaway for folks who listen, right? Is you know, by creating kind of

contests or you know, like there is something tangible, right, to kind of work towards. I mean, that that feels like it's not just one more straw being laid on my back of, you know, just something else that, you know, I I have to do, right? But this is something

Jim (24:32.152)
I hate to say it, but I think what you're describing is change management and

Veer (24:36.824)
you're gonna you're don't, don't.

Jim (24:39.906)
Yeah, I knew I knew V would hate that. I mean, I know that's consultant speak, but that is what we're we're dancing we're dancing around. Like how do you change an organization's culture or DNA to orient around this?

Veer (24:52.45)
Well, and it sounds like Justin, you're and and I'm gonna make an assumption here. I hope you can maybe like like you know, validate it. I mean it y you've created space, you've created incentive, and I'm gonna make this assumption that you you run your business with a clear set of of metrics that people understand what is important. So as you said, they were working on projects that improved, but improved means, you know, like s you know, something that that's really, you know, like like

like a hard number, right? I mean like something that's measurable, demonstrable, that is is not just it feels new or it feels better or feels faster, but it but it feels like maybe you're like it so the assumption is is that your your team, you've also created what the finish line, you know, like w you know, like the North Star. Everybody knows where that that that star is.

Justin (25:41.506)
Yeah, exactly. I mean it's just like if you you go back to that loop of AI, right? You gotta know what the end result what was the mission I set out to do and how do I know when I hit success, right? What is my success criteria? What did I try? How did I end up with that? How can I try it better? Try it again, right? Just keep going around with it. And yeah, I think, you know, kind of tying this back to some of the previous part of the conversation, but where, you know, we d we did have a period of time where

we s one of our teams, they have they're they're everybody's just crunching at cinch. We're just all trying to get everything done. There's a lot going on. We got a lot on everybody's plate. And we had one of our teams was just like, you know, asking us to try this thing in AI feels like it's just been another thing on our plate right now. This to to Jim's point, right? Now that team, they actually knew the value of AI. They knew what the AI could do already. This wasn't like you know, we were

We're jumping into something totally new. But what I didn't hear right at the moment from them was it's like, look, we have, we gave it that try, and like we didn't get like we didn't get the results we wanted, right? And so going back to that, like having a good first experience, they knew what AI could do. This was something we were trying to build and put together, and it just wasn't it wasn't helping them. About five months later.

We totally changed up some things in it from product and we were coming to that team. We were talking to them to try to see what we could do and totally different experience. Right. now I think if you took that exact same thing away from from them, they would be like, I don't even like y you want me to go back to working that hard? Like you just gave me a tool that made it a lot easier, right? I often think about the the differences in these tools, like we can all visualize the difference of a hammer and nails and a pneumatic nail gun.

Right? And how much faster you can just go through and you're putting a roofing project down or anything else, like nail, nail, nail, nail, right? As opposed to like I gotta hit this a million times with a hammer, right? Or in the automotive space, right, you got a pneumatic wrench and you're trying to put on lug nuts back onto a tire, right? Well it's gonna take me a lot of wrenching on that without that. But I get this pneumatic wrench and I can just zzz zzz right and

Justin (28:02.446)
And that's the way it is really with AI, right? Is now we're kind of getting these real power tools. It's not just like, hey, this was a thing that helped me with like as a knowledge worker to get things done, right? Excel has been the tool forever, right? Excel used to be one of my favorite tools. I use cloud way more than I use Excel now. But I used I used to have fifty Excel files open at any given time to help me manage everything and where it was going. And and so I think

Yeah, going back to like having that good first experience. How do you get somebody to have that experience that lets them know like, I can have some trust, I can move forward with this, and it's gonna actually be worth my time. It it it saves that change management fear, right? It it gets them into, I actually want to change because you know, I I can see that I can change, you know, ten tires in the time it takes me to change one tire, and or I can you know, put in

fifty nails in the time it takes me to put in five. So you you you're showing that ten X experience in in functioning and getting things done.

Veer (29:05.784)
So we've talked a little bit about how we're you know, like how it's affecting the work and affecting the people and how to you know, kinda you know, and and and you know, J Jim continues to insult me with consultant speak about, you know, my past. And it's just

Jim (29:23.662)
I mean, I I don't I don't have the same visceral reaction to change management. I just don't think people love to hear that word because it's scary.

Veer (29:33.132)
Well, and you know, let's let's just be honest, it's oversold. So yeah, yeah, you know, it's fair. But like I I peace one of the things that people, you know, hopefully are listening to us and and wanting us to talk about together is you know, kind of the experimental kind of things and and one of the conversations Jim and I have joked about like, you know, like when is the next deal gonna close where we're both gonna put

you know, a spark on our desks and start playing with them. And I was talking to a client a few weeks ago and and kind of coaching them as they start their AI journey to because they kind of asked about like do we need to run local models and I'm like no because you don't know why you need to run a local model yet. You need to build fluency and and you know and I talked to them about yeah getting at bats and and and and getting

Jim (30:29.422)
We use that term a lot. It was that's why we both smiled. We talk about at bats, that that's what people need. Rep.

Veer (30:32.376)
Yeah.

Veer (30:37.388)
And so here, you know, like you know, a and and one of the things I've told folks is one, like until you're ready, you shouldn't. And and also you know, until you have a certain level of fluency, it it it's not a conversation you need to have today where I think w we would say that we're all at the benefit where the anthropic and open AI and Google, right, they're still in the drug dealer model where like the first one's free.

Right. Like like we're we're getting a lot of stuff for you know for for low, low prices that is not sustainable necessarily. And but but that's fantastic. Take that and and run with it. but then when you learn, it sounds like y'all have gotten to a place where, you know, you're making some choices of local inference and and putting some tools in place. Like yeah, like how how's that like you know, kind of what pushed you in that direction and kind of what kind of workloads, you know, are are

you know, our local workloads.

Justin (31:35.148)
I just yeah, one of one of our coworkers was just like, Hey, have you heard about the Spark box? And I was like, Yeah, I've seen a lot of these being advertised, like this AI super box, and like there's there was a ton of last fall. Right. And and so at one point I decided, all right, I'm gonna I'm gonna give it a shot. I'll you know, Nvidia's doing this one, like let's roll with Nvidia's. We got the NVIDIA spark. And just again, it's at bats of like trying to like have that experience. And honestly, NVIDIA did a fabulous job at putting that together with like

Hey, here all the things you can do. Here's how much time it's going to take you to set it up. Here's all the instructions on how you get this set up and going. Right. And honestly, it made it a lot easier. The fact that Claude Code knew exactly how to execute that faster while I wasn't sitting at my desk. It's so I could have it setting things up and getting getting things rolling for me. And so I think that that that really again created a good experience from that. I actually now have three of them.

so I am three that are actively being used and then we have another one sitting it well I guess it's actively used as well, but I'm not actively using it. So we have a lot of the local inferences is really going into the things that you're constantly monitoring, right? So if you need like a momentary high power thing, we go for, you know, using something on cloud or we'll use openai or codex, right? But if I need something

a case in point in all of the AI inter interactions that we have on with cinch. We have a spark box that is running entirely to just monitor all of those conversations. Look at those conversations, see how they're going. Are people thumbs upping, thumbs downing? And where we get a thumbs down, what do we need to do to fix that? Taking that information and then passing that off to Claude to go try to write a fix for it and see if we can make a PR that needs to go out, right? And so those typically tend to be things that just like

Hey, we need to tell the agent you can do this or you can't do this, right? Or you function like this, or you know, they're they're typically not very big. If they are bigger, then it needs to go through a little bit more planning process. But but we have it running for that. We also have it running just against our code base to constantly be looking to see, hey, are there places where we have security vulnerabilities? Are there places that we have where we have just potential bugs and what type of bugs there are, right? And how those could be.

Justin (33:59.982)
what else do we have monitoring? We have integrations. Just anytime when you're from our side, data coming in is really key. And so being able to monitor, are we getting the data that we used to be getting? Is there any inflection inflections there either up or down that we need to be aware of that maybe tell us an integration's broken? and so those are the types of things they run twenty four seven, right? They're always trying to go deeper and deeper.

And it would just cost an arm and a leg to try to pay Claude to be able to do that, right? And so if you think about like I'll talk to the CFO and Jim here a little bit, but if you think about, hey, how much would it cost to run tokens full time and to get that out of tokens, that would just be, you know, insane. Even if I was using haiku or something on the lower end of things, it would still be pretty expensive. And so that's when it makes sense to go ahead say, Hey, let's get a box. It's five grand and let's go ahead and

plug that in, right? I I'm pretty sure you'd burn through five grand in easily a month, maybe even less, with some of the processes that we have going through. But then it allows you to run like, I mean you can run some pretty powerful models, right? You can run GLM four point seven with you know typically most people I would say you start with like the anywhere from thirty to maybe seventy billion. but if you really want to quantize that, you want to

make a few different aspects to it, you can you can do some pretty cool things to move that up. I've seen two billion work on a single spark. Not very great, but it can work a little bit. But then you can also, to your point beer, you can cluster Yeah. You can put them together. So I've got sitting right here, the I've got two of connected together and it gives you two hundred and fifty six gig of of and and you can at that point run all kinds of things quantum

Veer (35:53.486)
Cool. But you know, the the thing that I mean you went past it really quick, but I I want to make sure that folks catch this. This is what I heard, right? Is is one it's one thing that the the system is listening and you're being able to use you know you're just paying for you know power, right? You're not paying for tokens and it's and it's queuing up issues or concerns. But but you know, the the part that I feel like you kind of went past, which like I think is the more like like, you guys are doing something.

fix is also being done and getting queued up. And really w Jim had talked earlier about anthropics four D's and you know, like you're still leaving it in queue for a human to do discernment. But but the fact that you're not putting people in a place to discern, is this important? Okay, now we should go do something about it. You're making them it as a gate to say, yes, that's important. I like what got fixed, go.

And you know, like you've pulled you you you cut a whole cycle out.

Justin (36:54.294)
Think about how many times do you say, like, I I mean, as a business owner, this has been my entire career is like trying to decide and prioritize, like, okay, yeah, that's important. And somebody else might ask me, Why didn't you do that? And it's like, well, because I had this. And as soon as you tell them about this, they're like, yeah, I get it, makes sense, right? Or some people even are like, Well, you still should have done that. I'm like, Well, that was that unfortunately I have made and maybe I'd agree with you today, but I didn't then, right? I didn't know. And so the nice thing is with this.

is you can start to like you don't have to worry about human trying to prioritize all of these things as long as you know you can handle the output that they do at the end, right? Right. And and that's the key part, right? Is you can you you can trust it to go go fix a, you know, in in case like it's cinch, we have what we call cinch ops, and cinch ops is able to

I like I let it go fix anything that it finds in there and just tell me what it fixed. I let it go through the PR and even deploy those processes, right? and in fact this morning Jim and I were talking about a couple different things and I just asked it I gave it jumped on, used good old WhisperFlow. I've actually transitioned over to a tool called Peanut, which I actually like a little bit better because it'll read back to you as well. Just put that plug out there for

Veer (38:11.04)
No, I I I'm a heavy Whisperflow user, so I I that I and and I'm like, that would be interesting to see.

Justin (38:16.12)
See. No, it's great. Cause then you can like you can just be like read this back to me and let it read so I can still be pacing in my office, you know, getting some steps in or something while I'm thinking about whatever it's talking about. But but I can just let it in this case this morning, I just pulled up Peanut, you know, hit my control start button and told it what I wanted and gave it gave it some context of some extra files and ran off with it, right?

So it built it, it deployed it, put it all together and ran with it. And so those are the types of things where in certain realms, right, you gotta have some places where you can toy around with it, where you can be like, okay, you know what? If that breaks, I know I can just roll back to the li like go back to my Git logs, roll back to it. It's not gonna ruin anything at the end of the day. Now SinchOps is actually becoming more valuable to where it could. but but it's those types of things, like having just that little project that you can work on that you can gain the trust and when you know how that trust works, right?

I think one of the things I've expressed to our team is that in fact yesterday I was on with our marketing team and I told them it's like guys look the future is you managing your own agents. You know, you I want you guys to leave this company one day, not next week, not next year, you know, maybe not in the next few years. I I like like our team, right? But I want you when you leave here to be the most versed in your trade with AI.

than anybody else that's out there. So you can nail a great job. I am

Jim (39:45.07)
I'm really glad you said that. I am not trying to interrupt your flow here. Intentionality and letting people know what you're doing, that's another key point. That's something that I've done when I've implemented AI at scale. certainly not to the level you have. Mine has been more of a how do I get it started as a process or as a thought in a company. But being intentional about telling the employees that you are actually building a skill set.

for their career, for the long term that will set them apart. I think that's really important.

Justin (40:18.584)
Yeah, it was actually really it yesterday, it was actually really nice because what our our copywriter, her name's Erica, she had some really good questions. She's like, Okay, so help me understand, like help me see how this works, right? Like how would this function for me and how would that work with other other people on my team, right? And so as a copywriter, I told her it's like, okay, what are the things in your job that become a little bit more mundane?

Right, that you know they just take a lot of time. And if you could have them take less time, those are the types of things we need to do. So it could be like research. I need you to go do competitive research against, you know, whoever else has this product. I need you to also just go research internally. Like what are the case studies we have? What are these things that we have that that we could use? Let's you have a researching agent, right? You maybe then have an agent that goes and looks at

the tone that is used by a bigger company like Salesforce that maybe we're not fully competing with, but we want to emulate. And so we pull some of those in. And and explaining to her that your job is to really figure out how you can become the trainer of these agents. You need to train You need to then figure out how they work together. Maybe you then write as as a human, you continue to take the long form. You are going to be the one that writes out out the actual case study. But

You can have an agent that goes goes and does the analyst aspect for you, brings back that data and what the case study was and how it w how it turned out. you can have the communication going out to the customer to try to follow up with them about the case study. That can all be automated. But then you write the actual case study. You take the like core of how am I gonna bring the value? Maybe you do it by having a conversation with an agent, but you put that value together and then you say, now I'm gonna have another agent.

Who's gonna turn this into short form? And it's gonna turn it into LinkedIn posts, it's gonna turn it into an ad on Facebook, it's gonna turn it in whatever it might be, right? And so she can take and manage this, she can be the the manager of a series of agents that are orchestrated together, but she has to be the one that teaches those agents. Going back to the whole leveling up, right? It's like over time, she's gonna get better and better. She's gonna know how those agents need to work, she's gonna know the processes they're gonna go.

Justin (42:40.258)
She's gonna know how Stonnet wor works versus Opus when she's using those. and being able to dive into that, you can't tell we're really a claw shop over here, but but that's yeah, those are the types of things that I think are gonna really help people to understand like, hey, you can you can be a whole lot more effective. And I think for everybody this can start to 10x what they can actually do, right? At the least, you should be able to to two X your outputs.

Veer (43:07.532)
work towards kind of like a like land in the plane kind of stuff here, right? Two questions, right? First one is twelve months ago, what did you believe about AI a year ago that is, you know, has exceeded your, you know, like you're like, I I didn't even think it could do this. And and but, you know, like 'cause you've been using it for more than an, you know, if you've been using it for several years in in in earnest, right? Like a and the reason for asking that question, kind of the frame is of it is is

How much has it changed in just a year? I wouldn't have done this a year ago. I can't believe it's here this year.

Justin (43:40.01)
I I probably actually a a solid one is Excel. Right. I was still totally using XL for all kinds of things, right? Claude Skill and Xcel made huge leaps and bounds. Maybe it was late Q four last year, maybe the beginning of this year. But those that changed the game in a lot of ways for me. Like I I never

I mean I I should have thought about it. Like all we got was a spreadsheet is a bunch of code behind it, right? But the ability to be able to drop that in. I remember I dropped in a spreadsheet into Claw and I said, Hey, I need you to recreate something like this with our numbers. And here's access to our Snowflake database, go recreate it. And it did. And I was impressed. Especially as somebody who I I I consider myself a very high

power user of Excel, being able to I mean, I was doing machine learning regression analysis in Excel in 2010, right? Like, but I was just so thoroughly impressed. I was like, okay, this is this is getting to be game changing. And then I think the next one I I probably think was I didn't expect it to turn into being able to actually develop code as fast as it really has.

And so if I take an example, right? Twenty twenty-two co-pilots out and on a co-pilot in Git GitHub, right? it's not very great. It can help answer a few things, but not fabulous. And then and then you had Chat GPT that came around. I got on Chat GPT way early, like I had some fun with it, but there wasn't a lot of like business, like it wouldn't solve the business things that I could do faster myself, right?

and so those kind of changed and came along, right? But I think it was really in when Claude launched their desktop app. And I gotta go back and remember when that was. I think it was February or February or March of this year. But that was like I think the biggest game changer that made things move a whole lot faster, right? Is now you had Claude code that didn't have to be accessible through an IDE and using in VS Code.

Justin (45:59.208)
I did try anti-gravity for a little bit from from Google, but all of a sudden it became so easy to use it in in get value with cowork or with clawed code in this desktop app. And then eventually it got to the point where honestly the biggest game changer for me was the remote access, right? When I could all of a sudden just be out on my phone at a kid's soccer game and I'm like, Yep.

Nope, he's out sitting on the bench. I'm just, you know, sitting here telling my agents to get back to work, right? And that's those are the th that maybe like lines up the story of those changes all happened in the last year, right?

Veer (46:40.694)
Last six months. Yeah. I mean like it's a it it it it no, there's a little bit of you know, like the story's bananas when you when you start like looking at it. And so, you know, I I think, you know, it sounds like you're also, you know, you got you got your finger on kind of the pulse of you know, changes that are coming, you know, playing with new toys that are are coming out. Jim and I are doing similar of with you know, with different models or local inference or b or building things, but you know, for you

you know, as you're doing strategic, you know, as a as an executive, looking at this w you know, a as a tool set, but as this very I mean, yeah, I we I I couldn't have imagined in July of last year what I would be doing in February of this year, much less what I'm building and putting together now. You know, but I'm more fluent and I and right, I've gotten a lot about bats, right? And and and so now

you know, kind of what do you see, you know, kind of like the goal here? you know, well what's what's next for for cinch and, you know, how's this gonna like really play out for you guys?

Justin (47:51.062)
Yeah. I mean, I think the biggest thing that's gonna play out for us is the fact that we will have the ability to have full agent orchestration, right? one of the things that I've been preaching internally and we we gently do out externally is self-driving marketing, right? The general idea, you know, we've talked about it a little bit here on how we're using it or how we've used it in different ways, but the idea that how can I make a marketer ten times more effective at one tenth the cost, right?

If you used to have 10 people that had to be able to do this and now you have one who knows how to manage these agents and the agents are experts on what they do, that's that's the future. And that's where, you know, I I definitely am striving to get our team to. I'm striving to get our product to. But you know, you think about, you know, how much effort and time it takes to just go set up a campaign to run a digital ad campaign or building an email template, right?

to send that out. And those email templates within Cinch now are being dynamically created. They're an AI can go create them, put them together, design them where they want to go and and that's where we're going, right? The idea is how do we get to self driving marketing? and I I think the it's actually really cool to have you guys driven self driving cars, Tesla and yeah.

Jim (49:06.112)
Well, you know, it's funny. Very, very quickly, so I have one. I drive a Model Y. Veer visited. He came to town, spent a few days as we worked on podcast and all other things that we work on. And he drove it home from the airport. So, Veer, what did you think? It

Veer (49:22.798)
It really was like right as a technologist, like I've known about it for a long time. You know, I've been with folks in cars, right? I you know, right with Superdrive in a Cadillac and you know, you know, in rentals and stuff. And yeah, like it is jaw droppingly impressive, right? I mean just you know, 'cause 'cause you're keep keeping in your head the the the math, right, that's happening around you to make that possible. It is it it's impressive.

Jim (49:47.072)
It's impressive. Yes.

Justin (49:47.502)
The idea of the Waymo, right? No, like the legal obligation is now on Waymo, right? They are like to make sure that that drive's safe, that it handles everything. Insane the amount of calculation that is going on, the input that is coming in to make those decisions, the decisions that are being made so quickly, right? I mean, actually, there's some Chinese self driving vehicles that are even more mind blowing, right?

I have not experienced those in person, but I mean I'm all halfway tempted to fly to the other side of the world because

Veer (50:20.686)
I think it would be amazing, right? Because like it th they're you know, like, you know, that Waymo is fantastic, but it's got like all the stuff hanging off the sides of it. And we have here in Nashville, you know, where I live, and and I've watched them get stuck, you know, like like in in the gore in between two roads or you know, or where there's but but it it is it's impressive. It's impressive how much data is getting crunched. It's impressive

The fact that like we're able to do something now, it did not take us this level of s we didn't need this to put men on the moon. Yeah. If you're as long as one of the guys who doesn't believe that that wasn't a real thing and stuff. So

Jim (51:03.744)
World is round. Men went to the moon. Yes. Yes.

Veer (51:09.016)
Yeah. But right? I i it it is really impressive. So yeah, I mean, so yeah, what do you think? You know, I mean, so that you know, that you guys will be you know, kind of working towards this self driving marketing, which I think is an interesting which is

Jim (51:20.686)
It's a cool extension of of, you know, it's using the data and using it in y it's an ex it's an extension of what you're already doing with email and text at cinch and then now taking that out to you really paid media.

Justin (51:37.134)
I mean, you think about it, the crazy thing about self driving vehicles, those take your life into your your hands, right? Like they can make a wrong decision and you're dead, right? Or, you know, you're gonna be, you know, costly decisions that might happen right there in your personal life, right? The thing that's really crazy is that we don't have self driving marketing yet, because why? I mean, we have the data, it's all here. Like

It's way easier to actually work with and and all of my competitors that might ever watch this. Just, you know, it's hard for you. It's easy for us. But but the idea that well yeah, if you don't if you you're not gonna kill somebody if a decision's made wrong, right? In fact, half the time in marketing, you make a wrong decision, it gets more attention, right? And and so the the concept here, the w the word

Talking about at cinch is there's those levels of self-driving, right? You got cruise control by itself, level one, right? Okay, that's basically what marketing does today. Well, you know, you got MailChamp constant contact that do things like that. Let's send an email out. We're just gonna automatically handle this, like go at the pace we need to. But then you get level two, you start to introduce lane keep assists, you introduce the adaptive cruise control, automatic braking, some things along those lines, right?

that becomes tools that have that are automated marketing, right? I'd consider cinch in the space between level two and two plus right now. And and and so those are making certain decisions, but they're still following a lot of logic that is just defined by the user. You get to level two plus and now you're getting to the FSD from Tesla, right? You're getting into some of the the Mercedes class side of things. And these are these are places where now

automation is making decisions. Liability is still on the marketer in this case. Like they have to ultimately make the decision, but they can let it go, be more automated, make deliveries and decisions for Then you get to level four, right? You're talking about the Waymo's, the the zooks that are out there. And and now we're s we're taking more liability away, but we're letting the engine take a lot more decisions. To get to all this, you have to take those steps. Just like we've talked about the whole time. It's like you gotta have those levels that you're going through.

Justin (53:58.898)
And those help make the decisions that help the agents know how do I make the right decisions because I've had human in the loop as I go each of these stages within the the bounds that I have. And so that's where we're going. Self-driving marketing. The goal is is to get to how we can make people far more effective, making better content, making better things that engage with customers and and actually become valuable. We don't need to send millions of emails out every single week.

just to try to bring that revenue in, right? We can be more targeted. We know the destination. We know who's gonna potentially respond. And how do we bring that that business?

Jim (54:38.168)
then this I I gotta tell you, I mean, Veer, for a first guest on our podcast, I think we I think well, no, well no, I mean I I okay, so truthfully, I'm inspired because a lot of the things that Veer and I have talked about, you've brought up. It's nice to find a kindred spirit, but it's nice to find somebody who's working in a real you know, Veer and I can talk about this and we can tinker a little bit with some

Justin (54:47.918)
Father me.

Jim (55:07.028)
of the clients that we work with to their tolerance. It is very interesting to talk face to face with somebody who's doing it practically, actually engaging with it and making it happen, you know, at scale. I think that's I think that's it everybody should be inspired by it because a lot of businesses can punch above their weight class right now. Yeah. If they start to work a little bit on this change management.

And get people get people to to start using this daily. This has been an absolute incredible conversation, Veer.

Veer (55:46.808)
Definitely. No, I mean it so we you know, we we appreciate you, appreciate the the time. I think we've we've you know, we we've been trying with the whole idea of functional executives to be able to have something that's of value to our peers, right right. Not just, you know, just so we can talk a little bit about the the the f the down and dirty functional, you know, nerdy pieces of it. But I think we've talked a lot about the strategy that you've been pursuing and

You know, I I don't want this to go unsaid. I think one thing that I heard from you consistently and 'cause I think it resonates with me and and Jim is because I we're out talking with people out in the marketplace about this, is you you consistently brought the the person back into the conversation, right? This was not about

I'm gonna s build a company that saves money. I'm not building a company that is just efficient and cold and and lifeless, but this is about investing in people, making people feel heard, both from the people you serve as customers, the people that they serve, their customers, and then your team, you know, being able to say, This is about, you know, we're we're we are really, I mean, you know, trying to lift up everyone, you know, in a way and and the technology is is helping.

Jim (57:03.384)
Yeah. The other thing I wanted to do, Justin, is just give you an opportunity because we'll try to in the show notes also put a link to Cinch. Why don't you just quickly say how people can find you? Are there any trade shows that you're gonna be at that people might wanna know about here in the near future?

Justin (57:19.416)
Yeah. we will definitely be at Pestworld coming up, and then CEMA and Apex in November. So those are some of our bigger shows we will we'll be at. through the rest of the summer, we've got a series of other shows that we'll be going to more regionally. So any really any show we can get to in the home services or automotive services show space, we try to get to those. otherwise check us out on on the internet. Cinch dot IO is our website.

our name is Cinch, but our branded or our website is Cinch dot Io. Yeah, that's how you can find us. If you know, drop us a a line if you wanna out and find out how we can help you with AI and your marketing and just fill out a form to schedule time with our sales team or you can even try out our AI voice agent right off of the the website and our we've got a self served motion. You can sign up. In fact I'd encourage you both of you go check it out, try it out and

You can talk to one of our voice agents.

Jim (58:20.354)
Justin, thank you so much. Veer, this has been awesome. This has been absolutely incredible. I hope that everybody who's listened today has really enjoyed the conversation as well. just tried to stay out of the way because I was learning so much about how you can really make this happen in a business near you, for sure. You know, it doesn't you know that's not all theory right now. There are people that are actually out there doing it. So this has been Jim Boswell.

Veer (58:47.884)
Well and Vir Hossein.

Jim (58:49.964)
And we are the functional executives and thank you again, Justin Ray.

Justin (58:53.388)
Thank you. Good to have you. Or good to be here.