Transcript
Transcript

Hello, everyone, and welcome to the show. I’m your host for today, Gabrielle.

Today, we’re gonna be joined by Camilo Oregoso, whose River Logix direct of solution design. Today, we’re gonna be going through a River Logic live demo. So we’re in for a real treat here. Camilo is gonna be walking us through demonstration.

Of the, all of the capabilities that come with this platform. So Camilo, welcome.

Very, very happy to to to be here. And actually, we have prepared this presentation for for our customers and prospects to understand what we can do in terms of, infrastructure strategy and capacity planning focused on on the building materials industry. So, so that’s that’s gonna be something around twenty minutes or so. So we hope, everyone enjoy enjoy the the presentation.

Absolutely. So much, Camilo. Well, you know, I’d I’d also like to remind our audience that there’s gonna be a live q and a session after the presentation and the demonstration. So I do encourage you If at any point during the presentation that you’re listening, that you have any questions, go ahead and add them to that chat function over on the right there.

And we’ll take a look at them and make sure that we get them over to Camilo, to get them to be answered for you. So without further ado, I’d like to hand it to Camilo here so that we can get through the presentation.

Thank you, Gary. Absolutely.

Okay. So I will I will keep you before starting a quick introduction of our company. So we are, a company with the, over twenty years of experience in the, in the industry.

And we have found we have supported our customers to found more than fifty billions in value always from optimization processes. And that’s that’s where we are going to be focused today.

First of all, I want to get you, to the message that our solution is, It’s a platform that supports end to end notices. Alright. So here, you can consider not just actually just the the splashing silos as as a typical supply chain optimization tools does. But you can also include all the financial commercial and procurement details. But that’s the meaning means that with our solution, you will be able to include, all the financial constraints, financial policies, financial objectives, and optimize the supply chain based on that. Right?

Same thing with the procurement on commercial side, we got some, additionally days, like being able to support very specific details on the contracting, aspect of of the relationship with the, with the stakeholder.

So in those, in some cases, we can, for example, consider very specific commitments from the contracts at the supplier side to satisfy the full supply chain in terms of that constraint.

With that holistic trade offs in, in, in our analysis, we can always find different type of values. So the values can go from financial Right? So we can always find, being focused on optimizing the net present value that’s gonna have a higher impact in in different scenarios.

Or going actually to have direct impact on, on the supply chain silos, as, as, reducing production cost or actually, having better, better performance on distribution and the transportation utilization, things like that. Right? So That’s that’s that’s that’s the advantage of using our end to end solution for those type of finances.

So, just to give you a quick introduction on the, on the, demonstration itself. I want to just give you a highlight on the dataset that we are going to review. So you can understand easily what we are going to do.

First of all, we got a a supply chain that is, based in the, United States.

We got in the, in the network that we defined. We got fifty nine customers around the country. We got twenty, twenty two distribution centers, sixteen plants, and there is a single vendor that, I’m actually modeling as provider of raw material, but I’m not using it flows, for demonstration purposes.

I have to say that in case you want to model a longer end to end splatoon, like, including Bend or or even more type of disease, like, or a crosstalk, So, we’re, different, these classifications, you can always do that. Right? So this is a simple data set. So you can actually understanding that in a, in an easy way, what’s, what’s going on with the with the data. So we go at a year of of demand, we got monthly, monthly periods. And you can see there is a peak in the middle of this year, of that demand.

Okay.

So, with the products, we got, here, five different end products.

And as I told you before, this is just one raw material identified in the expansion.

Okay. So we got three scenarios to show.

So the first one is gonna be the baseline where it’s actually showing you what’s what’s hap what’s happening with the, with the current supply chain. Right? So that’s gonna be my Well, the the performance of the optimis of of the splashing without optimization. Okay. So that’s gonna be just what digital planning to ensure reflecting, current policies and misterities.

Then we’re going to see what happens if I allow solution to make a strategic infrastructure analysis, which means that I’m going to say, that I have someone available sites to be open. They are going to be both production plants and distribution centers.

And I’m going to constrain the solution to have some CapEx available to be allocated on those investments.

So, so with that, we are going to see what’s what what the solution is gonna suggest in terms of opening new sites and what’s gonna be the effect on that, of that on the supply chain. Both the physical supply chain and the, and the financial performance.

And finally, we are going to see what’s going to happen if I have, my model to understand how to face business growth. Okay. So what’s I I will set up, of course, those contracts that your your companies are going to have, like, well, in, in, in a negotiation or as, possible deals. So you can actually understand what’s gonna be the analysis telling you in terms of how, how to support those contracts, and and that’s what’s gonna be the effect on that, of that, on, on the splashing capacity.

So, so those are the scenarios that we’ve got.

I think I will just jump to the tool.

And you’re already seeing the tool here.

Let me let me just, first of all, give you a quick background of this. So this is this is the cloud solution that we use, to solve the the analytic problems that that we want. Right? So in particular, I have a solution that is called network design optimization.

Right. So this is our network design solution.

And this is where most of the users are gonna be interacting with distribution in terms of uploading data, creating scenarios, to ask what if, what if analysis, what if questions, and then run-in the scenarios and see results get insights from the solution. So this is this is where you are going to get, most of the interaction in the time.

However, I have to say that with our solutions, you will be always able to go behind this and access the optimization algorithm in case you want to change or you want, in case you want to, enhance your optimization model. Right? So, that’s something that you can do with with our solutions.

So let me start now showing you, a dashboard.

So this is, an API that we got with MacBook.

By the way, this is, something that you can also do with the word solution is getting, connected with different APIs.

So this one is a MacBook one. I’m just, having a quick configuration here, so you can see a little bit more details. So as you can see, this is a very easy to use API what is what I like from this one is that it’s going to give you a good visibility of the initial resource. So let me just point out the central region, the United States here.

So you can actually see the main changes.

So we got in the same order as I explained the scenarios before. We got the the solutions here. So we got the baseline.

First, then we got the scenario where I am allowing the solution to open new disease. Right?

And then I got this, the solution where I am just calculating a business growth. Okay? So as you see, wide, why, locations are actually the plans So as you see, I’m actually having an additional plant around Texas, right?

And that implies that a distribution center, which is actually this one. Is going to have a different flow, and, so it’s actually serving different type of customers.

So now that you have this, let’s say, visibility of what’s the main change in the, in the split chain, let me go to our reports.

And I have to say here that for reporting, we got Power BI embed in our solutions.

So you can easily configure those reports.

And, actually, you can you can use the ones you have if if you have some.

So this is our network design power BI.

I’m well, this one in a specific contains something about for your fifty different reports, in the, all along the supply chain silos.

So we can easily understand what happens with the solution. So let me just start with this.

This one is comparing the baseline, versus the scenario where where I am optimizing those, those up as, sites openings, right? So as you see, and that’s probably, simple to understand is we are increasing the processing cost This is a summary of of the supply chain costs. Right? So we are increasing the processing costs. We are reducing significantly the transportation costs.

So that we are increasing our income.

While we are doing that, of course, we are open insights, right, which means we are serving customers closer than before. Right? So as we are delivering closer distances, and that’s the most impact impactful pricing in my supply chain. I am actually saving, most of the amount just by decreasing the delivery distances.

If I want to, go and see a little bit of details on that, and let me start with the financial side. This is where we can actually get insights to align the CFO and other stakeholders with display chain solutions. Some of the of these challenges that our customers have is actually on how an optimization process can be aligned with the, with the financial expectations of the company. And that’s what what we are doing here, right? So we are actually considering financial objectives, objectives. We are considering financial policies and constraints, and we are including everything together with the supply chain optimization.

Same thing we get, as an output. This is an example of that. And what you’re seeing here is actually the P and L of this So we are going to be able to produce P and Ls of each single scenario.

How to manually from, from, from the, from the output reports. Right? So at this point, we don’t need to, work everything by hand after the optimization.

So as you see here in the, if we compare the baseline versus that is scenario, what, where we’re where we were talking before.

We can see actually the the increase in the net income.

Right, of, eleven, eleven percent. So that’s the comparison between both, profits.

Now, So we can also do the same with, with the scenario where we have the infrastructure optimization versus the one where we have the growth optimization.

So now here, as you see, we are increasing the sales in fourteen percent, but at the same time, we got to increase the profit in almost ten percent.

Beyond the the financial statements or the PNR, we can also go and see for example, the detailed unit costs, where we’re going to be able to understand what is the total learning cost of every single, well, an average of of every single customer product combination.

That’s showing an average, of course, but you will be able always able to, add more details to the reports. So you can see, for example, what’s what’s the change on the, on the detailed unit cost per customer, per product. Let let me just show you an example of that. I can easily edit here the, the report.

So I can add home, then I can find a variable that is called location in this case, and then I just gonna add the detail to the table. Okay. So here, I will show what’s gonna be the change per customer. Okay.

Same thing you can do, if you want to analyze that per customer per product or just per product or so.

Okay. Something that, and and this is just to finish the the financial message here is I have already told you that you can always consider the, financial constraints. Right? So that’s something that we can do. Here is an example of Let me just make it bigger.

What we got here is different financial pressures that we already got con got configured here.

I have to say that this is not limited to these ones. This is just, the ones that we got for demonstration purposes. But you will be able always to constrain all these financials in optimization. As an example of that, you can save, Yeah. I want to make the optimization to optimize the sales volume, for example. So please sale as much as you can, but make sure that your net profit margin is at least something. So the only thing you need to do is turning on this, constraint and use the radius.

To change, the data and to say what’s gonna be your constraint.

So that’s all you need to do in case you want to line or to include the financial policies into the optimization of the supply chain.

Okay. So continue with the with the revision of the scenarios. Let me just jump to the production side. Where we can see, for example, the production volume comparison.

So in this case, and then let me go back to the between the scenario baseline versus the scenario where I am opening new sites.

And notice that, most of the changes are actually open insights that That’s something that we realized it before from the financial summary. So we are starting to see details here. Right? So we are saying, okay. So we are opening the plan in Texas, in a plan in Utah. We are opening a plan in Canada.

So we can also see details in terms of, production lines. I have defined only one standard production line for each of them, but you can always include as many production lines that as you want. So you can include all your meals, for example, or all your processes around the, the production details.

So you can see let’s say if you have, plants that have only part of the food production process, you can also include that in here. Right? So you can see details in terms of how efficient they should be in terms of, capacity and and and part of the production processes that we have.

The effect of that, of course, I am opening sites. So I have an effect in the purchasing side.

Here.

So if I go to purchasing comparison, for example, Sorting.

I will be able to see data is loading. So I’ll be able to see, let me go back here if I can look this one better.

I’ll be able to see the difference between how much did I buy in the, in the production plants, versus, well, aided by period, comparing one SNI versus the other. So in this case, as I told you before, you will be able to consider reshaising details in terms of contracts.

So you will be able to constrain the solution to say, for example, oh, yeah.

I got a commitment, which is actually buying at least x number of units or x number of tons from, my supplier in a particular month. Right? So you can always constrain that, and you will see the performance of that in the purchasing effect.

Same, if, same effects, you are going to have the shipping side.

So if you go for example to the to to to understand, okay, so we already shade something, we produced something that we already understood the changes. Now, we need to understand, okay, what’s what’s hap what happens with the with the shipping side? What’s what’s a good logistics?

And let me take advantage of this report. We also did, this one to show you what, what’s gonna be in case Let’s say I want to include here a variable that is called from location.

So this is flexibility that you can have, all the time. So that’s gonna be editing the tables, live. So let’s say in this case, I’m showing you what’s gonna be the changes, along the distribution center. So we got all the distribution centers here, which ones are absorbing more demand. So I got cancers, I got Iowa, I got it, serving demand. We also have some distribution centers that are being closed like Nevada. Right?

So those artifacts on the distribution side. If you want to see details on what happens with the transportation modes, for example, you can always go to the transportation modes report. And see.

In a specific, any type of change or detail that you want to Right? So you can always understand what’s the cost of a specific transportation mode, per product flow, and, that’s gonna be in average per shipping. Okay.

So Just to just to finish with the, with the scenario comparisons, I want to go to the sales side because that’s something that we haven’t down before.

Let me just go to the sales comparison map.

So we are in the growth scenario, and this is where we can realize, we focus just in the central region. This is where we can realize that, for example, Kansas is the region where I am analyzed what’s gonna happen with additional demand.

So this is where I can see the demand changes, right, in terms of, of the effect of purchasing, effect of what’s gonna be the number of materials that we have to buy in addition to the demand, the transportation effect, and, of course, the the financial performance of that change.

So something that we have to, clarify here and and and leave the message for the audience is you can always have a scenarios to analyze particular questions but you can also have, scenarios where you can compare unexpected disruptions in, in, in, well, looking to optimize or to maximize the business continued.

Right? So it’s something that we have in our prescriptive order tag.

Just before finishing, let me just show you a couple of human tables because I want to show you how to interact with data. And let me just take advantage of the demand side to to show you that.

So if I go to my workspace in in the solution, Then, I choose the scenario, then I choose the sales category, and then the V1 table, I got this one.

This one is the an example of our tables So as you see, well, this is the demand one. Right? So there is a couple of insights that I want to leave. First of all, you can always add different locations per customer.

So if you have the situation where your customers are having, let’s say, single billing address, and that address is just, It’s just the the corporate address, and and and that’s, of course, it’s not gonna play with your logistics requirements. You can always have that. And also the option to define what’s gonna be the location to deliver a product. Right?

You can have, of course, pricing and the discounts. I want to say here that for discounts, we’ve got three different ways to use discounts in our solutions.

First of all, direct percentage on on the pricing. That’s that’s what I have here. Right? The second one is, fixed value per unit. So one dollar or two dollars, three dollars.

And the third one is, range.

Based on the volume. So you say, okay, so the person that’s count is gonna be five percent if you buy from zero to one hundred tons, from one hundred tons to three hundred tons, it’s gonna be five percent and so on. Right. So this is the three options that we have. And something very interesting is the minimum service level factor.

This is, variable that you have gonna play as a constraint as well to define the demand to be hard or soft constraint. If I set up this as a as a hundred percent as I have it, I’m saying that the solution has to deliver one hundred percent of the forecast. But if I change this and this is how you’re going to change data, right, part of that, I just did it for these random numbers.

So you’re saying that the solution is going to be able to avoid twenty percent of that.

That’s gonna be useful if you are optimizing, for example, profit instead of the sales volume. Because the solution can can understand if you are actually making money or not by delivering one product to a specific customer.

So In case you are not, well, in case you are losing money when you deliver one specific product, The solution is gonna probably like to give you the opportunity to change that demand to other demand in a different place just giving you the chance to increase the profit in a change of sacrifice those customers that actually don’t make, a lot of money. But always, of course, pointing for calls come forward for the splashing performance.

Okay. So I think that’s all that we have, for today in order to show it to you. So, Gabriel, I think we can just jump to the questions.

Fantastic. Well, thanks so much, Kimilo, for just taking us through the presentation as well as the demonstration. I mean, there’s just so much that goes into this platform. So, thank you for showing us, the ways that we can best utilize it.

Well, like Melissa, we’ve made it to the Q and A portion of our show today. So hopefully, you got some of those questions in. At this moment, I’d like to introduce our mister Aaron Berg, who’s a RiverLogic’s vice president of professional services. He’s actually gonna be helping us answer some of these questions we’ve got from our audience here today.

So thank you, Aaron. Let’s actually go ahead and start with this one, Erin, what do you want, prospective customers to know about the flexible configuration of this platform?

Well, I think that, by the way, Camille, if that was a fantastic demo, thank you so much. I think that, when we talk about digital twin, planning or digital planning twins.

We’re talking about an extension of what many of our customers have doing for for years, things like supply chain optimizations, supply chain planning, but extending that out sort of beyond the traditional you know, things like flow path analysis and and, capacity planning, that sort of thing, but going into as Camilla was just showing, how do I take advantage of my markets in the most profitable way? How do I make different contracts with customers. So that kind of flexibility sort of ups the game of supply chain planning. And I think that that that may be one of the big messages we wanna get across. Don’t know, Camille, if you had any other other thoughts on that.

No. No. It came. That was that was And I I think you showed some of that very well, so that was terrific.

Exactly. Well, you know, this is open to both of you. So is it possible to model labor requirements to adjust capacity.

Is that a possibility?

Why don’t you take that Camilo? Yeah. Of course. It is possible. You can always, consider and on each resource, and, that, that includes production resources, warehouse and resources.

You can consider the labor requirements for each case. And you can define what’s, what’s the time available those resources in terms of a standard time and over time, you can also define the cost for both cases.

So, so that’s, that’s gonna be understood, by videos.

So you can easily get a per perspective what’s gonna be the effect on time in terms of labor requirements?

Yeah. I think I’d I think I’d follow-up their on that because there’s a lot of power in thinking in your digital planning twin about, how how is the availability of labor?

Overall, in particular markets, like different locations, there’s more labor available or it’s less expensive.

And then making decisions as you, make capital investments, we talked a bit about infrastructure strategy So if if you are, are making decisions about automation where you’re trying to reduce labor, maybe the best place to reduce laborers in the places with the most expensive labor. It seems kind of, obvious, but imagine you had a network of twenty or thirty different plants and that you needed to make decisions around all of those with any labor and automation where it would best spend it. Those kind of problems are coming up more and more, and and very well attended to in our software.

Actually, I got a question here from the audience regarding capacity planning.

So do either of you have any kind of reference in terms of customers using your technology in order to analyze capacity planning?

Yeah. I think, I think the one that we would probably talk about the most And we’ve we’ve talked about them before as Filamores International.

Filamores International is moving from a traditional tobacco product infrastructure to a, you know, some of the new, the the newer products, that they’re that they’re selling.

And because of that, they are in a sort of very dynamic situation.

They have over forty production facilities around around the world. They’ve used our digital planning twin to help them dynamically that is every every quarter, every every month, look at where their capacity is, where they want the capacity to change as their markets are changing and shifting as well.

So they’ve told us that they’ve had cost savings well in excess of five hundred million dollars in the first six months of using RiverLogic solution.

And then we’re able to establish a a much finer grained process. I think monthly to do this replanting and re understanding of of how the dynamic situation is changing and how infrastructure could be optimized as they go.

And reduce the time to do those scenarios, I think from weeks and weeks down to just days.

So it’s a they’re they’re a great client of ours. We love working with them.

Well, that’s fantastic to hear. Well, I know you mentioned, digital planning twins earlier, Erin. So we actually have a question about this from our audience, which you know, what makes the digital planning twin different from the traditional digital twins that we all know in the industry? What are the differences there? That’s a great question. I mean, we specifically talk about river logic and digital planning twins.

Digital twins. Well, digital twins have a few different meanings out in the marketplace these day, but but in manufacturing, it’s, generally around real time visibility around real time impact of change is a place where you can say, you know, take a machine down what happens. Well, digital planning twin goes a bit beyond this. It uses, as Camilla was showing you the technology of optimization to help suggest into the future what you ought to do in reaction to things occurring within your business. So an example would be you know, let’s say, you have a supply chain disruption, and your question to the digital planning twin is if the supply get gets disrupted in this particular way.

How should I rearrange all of my flows, all of my customer sales, all of my sourcing to best recover from that rather than just sort of accept a, you know, a supply chain disruption sort of at face value. So that’s sort of planning that optimization, that looking into the future and saying, what should I do, is really, from my perspective, what what, digital planning twins are all about.

I don’t know, Camille, do you would you add something to that?

Yeah. Actually, the the, that is something very interesting with the digital planning to answers is that you can always find in a different perspective you scope.

Right? So so you can always be more focused on different approaches or, or different, or being more detached, for example. So, so you can actually have a balance or a trade off between on if if you want to go really into it and have him less details of of of the information, or if you want actually to go to optimize something specific, that, of course, it has trade off from from different silos, but more focused on the details or on the tactical side. So yeah. Yeah. Perfect. Well, we’ll actually start with you Camilo, with this one as someone from the audience is asking, you know, why do partners win with River Logic?

I I will say, and and, I will say flexibility.

Our solutions are capable to support difficult problems, right? And, Actually, that’s that’s what we like. We like challenges. We like. We like to solve, these type of problems where customers need to use our solution, and and that’s the one, right, because of, our capability to go to the digital planning train and figure the algorithm itself, and that’s something that the customers can do by themselves and partners, they are going to be able to support also difficult, challenges from their customers. So So that’s something that they like, in my opinion, and, that’s that’s part of the value that we add.

For sure. And Aaron, do you have anything to add on to that?

Well, I I agree with everything that, Camilo Camilo just said.

The RiverLogic platform, in addition to having all the flexibility to model, as Camillus said in any detail or any, difficult modeling capabilities.

You saw Camilla spend an awful lot of time talking about our ability to do financial constraints and financial modeling. And I think that that is, it’s pretty unique in the marketplace. It’s something that is, is is a real, value differentiator for our customers. More and more, the decisions around supply chain are not just focused on tell me how to operate the lowest cost, but they start to ask questions about how do I operate as Camilo showed at the highest profit or generating the most cash or whatever your goals are. And even today, more and more people are asking questions about how do I operate and design my end to end supply chain, balancing, my my carbon requirements against my ability to make a profit or a cost.

So those are some of the things that really drive value, for Riverlogix customers. We hope.

And, enables them to, as you say, win?

Well, let’s delve a little bit more into that value. We started to talk about, because what is RiverLogic’s technical value to partner specifically also building repeatable projects So where is the technical value in that?

Sure.

So when we talk about partners, River Logic not only sells directly to, to, to customers, but we also work through a large network of consulting partners who add value to what we deliver in in a bunch of different ways.

Your large consulting firms have skills or practices in particular areas. And what they can do is they can take the river logic platform and they can configure it for specific use cases that they can then use over and over, you know, capturing their own sort of point of view of their own intellectual property into the solutions that they create. So in addition to being you know, a solution that an end user customer can buy, you can also work through our partners to buy solutions that they have craft it on our platform to create value in many, many different ways?

Well, you know, Erin and and Camilo, you know, there can never be enough success stories. We love to hear them. So, you know, what success stories can, river logic share about clients who have ultimately benefited from its solutions. You know, I’m sure there’s quite a lot. So, maybe you can each take a story to share.

Do I start to build?

Yeah. Sure. I I think, something that came into my mind is, is a company that says furniture.

That, had a break, complex situation where, let’s say, in your business, they have, well, you know, that when you are going to buy furniture, you can actually wait for days and you’re happy with that. Right? So they’re production capacity is not, is not really, problem because they they say, okay. So we’re for me two weeks, three weeks, four weeks, depending on what you’re buying, but but the thing is you need to plan that. Right? So As long as your digital trying to, planning to, and helps you to understand where you need to produce something, in, in terms of that, delivery commitment, and where you have your production constraints, actually close to be fulfilled.

You have a challenge. And, in the, in the optimization side, let’s say if your tool is not going to be able to, give you that flexibility, in terms of the date, delivery.

That’s that’s where the solution is gonna take you to a lot of hand processes and and reloads of the model and and and work arounds and things like that. And that’s what we offered to this customer.

We we actually configured the, the algorithm is the, well, the digital time train, and we build the model in, at the way that they can actually include a date, but that’s not gonna be a hard constraint. So the solution in automatic is gonna take, who’s gonna fulfill the the production constraints and it’s gonna take the demand that is not gonna be satisfied and move it to the next video. You know, the money. So so you’re not getting any feasible models. You need to run the model on the ones.

You get more time to analyze data instead of running the model several times trying to get, nice result, right? So, so that’s something that we offered to them. And, I think that was a good example that I liked.

And, Erin? Yeah. I’ll add I’ll add a brief one, because we have a, a client that’s gonna be joining us, in the near future at the Gartner Supply Chain, Nandico materials will will have their vice president of supply chain there.

So Eco Materials is a is an interesting company, well, it’s an interesting company. In any case, but from a from a modeling perspective, what they do is they, they source supplies of ash, which is a waste from power plants, and they then distribute and blend this ash from power plants and sell it back into the construction industry.

It’s used in, in the manufacturer of, of concrete.

So this this kind of a supply chain is is is interesting. I mean, it’s interesting because the economics are kind of turned around. It’s a bit of a recycling, circular economy kind of model.

And then a lot of the agreements on things like sharing, revenue and sharing, margin, across their, both their customers and their suppliers. I guess they’re both customers for for them. But if you’re if that’s intriguing to you and and sort of the challenges that that, we went through working with ego material, then show up with the Gartner expo and, listen to what, listen to what they have to say.

Fantastic. Well, as we start wrapping up this conversation here, are there any last points, either Aaron or Camilo you’d like to leave our audience with as they, wrap up the show.

I think Camilla, you should you should have the last word with that, that great demo.

Well, actually, actually, I I have, a lot of things that we don’t show, but, I’m sure you you will have a lot of questions. So the last message I would say is done a state to contact us. If, if you have, let’s say, question regarding, hey, can I model this? Can I model that? Can I include this level of detail at at the source inside, or can I use these little off the daily inventories or but anything that came to your mind we are willing to help you to support those challenges?

That that’s what we have. Right? So our digital dream is capable to support and, that kind of complexity and being able to scale your processes. Right? So that’s what we want We want to scale your businesses. We want to help you, plan new businesses in a better way. So so trust trust on this and, just contact us if you need any any additional data.

Absolutely. Camilo brought up an excellent point there. Thank you to all of our audience members who sent in questions that we were able to answer during the show, but if you do have additional questions, as Camilo said, feel free to reach out and you’ll get them answered for you. Alright.

Well, that wraps up the conversations for today. So thank you, Erin, and Camilo, for joining us, for this live demo. I mean, we’ve learned a lot. So thank you so much.

Our pleasure. Thanks so much for participating.

Absolutely. And as always, if you’d like to learn more, please visit riverlogic dot com. I’ve been your host Gabrielle. Thanks so much for tuning in.