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This podcast offers business solutions to help listeners develop and implement action plans for lean process improvement and implement continuous improvement projects, cost reductions, product quality enhancements, and process effectiveness improvement. Listeners come from many industries in both manufacturing and office applications.
Shayne Daughenbaugh 0:00
Hello and welcome to the next episode of Lean Solutions Podcast. I'll be your host today, Shane Daffenbaugh. Today's topic is something many leaders are excited about, but may feel stuck on some of the first steps. This episode should give some practical advice on how to get started, what areas of business to look at first, and where companies are seeing the biggest efficiencies and the biggest efficiency gains in this topic. This we are bringing back a fan favorite here. Dr. Saeed holds a PhD in artificial intelligence, spending more than a decade in software development, delivering over 150 products projects. Sorry, he is the founder of Alpha Chi, where he helps small and mid-sized businesses apply AI to real operational bottlenecks, including lead response time, customer follow-up, and front desk workflows. So, Dr. Saeed, I am happy to bring you here onto the stage. Thanks so much for joining us. Now, this is a part two for you and I. Your first one that we recorded dropped around October 2728. And if you haven't watched that yet, please do so. Get to that because that one we talk about not automating the waste. How AI, how companies that that begin to implement AI tend to do it in a way that doesn't give them the results they want. So today we're going to focus on hey, where do we begin with this? So if you are ready for this, I got some questions for you, Dr. Saeed.
Anas Saeed 1:32
Sure, ready to start again. Thanks for having me again.
Shayne Daughenbaugh 1:35
I I am jazzed to have you here. Let's finish this, or at least continue the conversation. I don't even know we're going to be able to finish this topic on AI and where to begin. But my first question for you: If people are interested in doing this, you know they maybe they watched our other episode. They learned about some of the pitfalls when it comes to automating and using AI before your processes are ready. If they're interested in AI but don't know where to begin. What should they do first? What are some things you suggest?
Anas Saeed 2:06
So the first thing that they should do is that stop reading about AI, stop watching videos about AI, and start doing something with it. Yes. Okay. So the simple thing is that the first thing you should do is that get a chatbot, a paid option, be that ChatGPT, Cloud, DeepSeek, Grok, anyone that you like, and start using it. Okay, some of the basics aspects of any chatbot that you should be able to do is write stuff, summarize stuff, be a companion for stuff, research stuff. So if you start with this, okay, you'll start to learn about what artificial intelligence could do, what AI could do, what are its limitations, what guardrails do you should you have, and you'll start to develop a better understanding. So that would be step one. Start using it because no one learns how to ride a bike or swim by reading books or watching videos. Yeah, that could be helpful, but until you fall a few times, you're never gonna learn how to ride a bike.
Shayne Daughenbaugh 3:04
Right. Yeah.
Anas Saeed 3:05
Step one. Second thing is that once you're familiar with it, the next level is if you go to custom systems, is don't start with hey, what can AI you can do and follow up on the hype. Start with your week. Start with the repetitive tasks that you have to do. Start with the biggest problems that you have, because think keep this in mind that AI is just another mass. It's it's another tool in the toolbox. It's a great tool. It could do a lot of great stuff, but it's another tool, and a tool is only as good as the problem is going to fix and the person who's using that tool. So what you should do is that figure out okay where you could actually use it. So see what the biggest problems are, where your time goes, and then this concept that we use that you have to find stuff that are repetitive, rule based, high volume, and they are rule. So there are four things actually. Find those which are AI are great at, and then use AI to solve those problems. So those are the things that once you find it, then you could actually practically start to implement. So the first thing is stop leaving the hype. Start doing stuff. Start with a small chatbot. The second thing is that see where your week goes. That your calendar, your biggest to do list. That's where you should focus on because you have to figure out okay or a consultant would figure out on your behalf that hey what are where can AI actually help what are the problems and how could AI help to solve those problems that's
Shayne Daughenbaugh 4:35
right so so when you because because you focus on Alpha Chief focuses on small to mid-sized businesses. So when you're talking to people about this, and and if you know if I was one of your clients, and you're telling me this, you know, hey, start using it, stop reading about it, you know, and and start with the repetitive tasks. Would you advise me when you say to start using it? Would you advise me to to to buy like? A team subscription or an enterprise subscription, or just my own. While I get to understand it, like how do how does that work with with how you're talking about starting? Should I get it for my other employees or just for me?
Anas Saeed 5:13
So I would recommend that start with yourself and then expand to your team. But when you implement it for your team, you have to then have to implement safeguards and precautions and educate the team. Because the thing is that, like the saying that okay, a tool is as good as the person using it.
Shayne Daughenbaugh 5:32
Sure.
Anas Saeed 5:32
With cars, okay, the mention that there is a statement that okay, the the the worst thing that could go wrong in a car is the nut that's sitting behind the steering wheel, aka the driver. So what happens is that if you give everyone ChatGPT and say, "Hey, we're gonna go AI first," okay, what will happen is that people can take that in a negative direction and misuse it or have fears. So what you should do is that educate and inform, and based on that, say, "Okay, this is step one, and how we're going to use it. And these AI tools could be there to help take work off your plate. Every job has some kind of grunt work that AI could be helpful solving. That's the goal first,
Shayne Daughenbaugh 6:14
and that's the the repetitive, the rule based. You know those those those kind of repetitive,
Anas Saeed 6:20
Repetitive, rule-based, huge scale, and time consumption.
Shayne Daughenbaugh 6:26
Okay,
Anas Saeed 6:26
which are a lot of times these copy-paste tasks, coordination tasks, answering these sort of things.
Shayne Daughenbaugh 6:32
Sure. So even though I would be underutilizing the capacity and the capabilities of AI, you know, because I know that it can do so many things, but you're asking, hey, just become familiar with it, using those, using it for those repetitive grunt work tasks that, you know, summarizing this document or this contract, you know, sharpening this email, those kind of things. Some of the smaller things, what is what I'm hearing you say, to become familiar with it and then work toward, you know, expanding that to to possibly my team.
Anas Saeed 7:04
So exactly again, things that you could add to that as a very basic level is researching a topic. Anytime you get an email or you get something that you don't understand, you can ask it like, explain this. Like you're talking to a five-year-old, right? Or if there's a long document and you don't understand a small portion of it, you could explain that. Then, if you have to make a choice between two different aspects, never ask AI to make the choice for you. Ask it to give you the pros and cons of each one of them. Like we talked last time, okay? AI should never be in control of the judgment, the exceptions, or the relationships.
Shayne Daughenbaugh 7:43
Yes.
Anas Saeed 7:44
So, and even with emails, okay, you could use it to draft emails, but never use it to send emails. So that's why, like, okay, when you're using just it, just at a personal level, you can learn the limitations, what you should do, what you shouldn't do, where should there should be guardrails, what are the limitations? Where it shines, so you can learn it, and then you can go to the next level. And the next level is basically custom workflows. So any business, okay, it basically consists of a list of things that have to be done. So for those list of things, okay, you basically design, okay, these are the top things that have to be done. Okay, that could be responding to leads, converting leads into customers, completing work, seeing what's going on in the business, inventory management, completing work, organizing stuff, checking on inventory, checking on leads, summarizing stuff, feed customer feedback. All of these are areas.
Shayne Daughenbaugh 8:38
Okay.
Anas Saeed 8:38
So you basically see each area and see these are the custom workflows that could be implemented. That's the next level, and on top of that, there are custom systems that are built that could run the whole process. That's the way it works.
Shayne Daughenbaugh 8:52
So you just you just named off a whole bunch of things that it could do, but if I'm brand new to this, what are some areas of business that I should look for first, or that I should look at first. You know, what are some practical starting points? I've I've spent some time in it. I understand how the chatbot works and and how to kind of you know manage it and make it my own. Become familiar with it. Now I'm looking to expand it. You just named off a whole bunch of stuff. Of those, what would you say would be some, you know, some some areas that I should look at first, and some some of that practical starting points?
Anas Saeed 9:27
So the thing is that you should look at your calendar and you should look at your to do list. From that, you should figure out which are your stuff that's repetitive, rule based, time consuming, and high volume, and those are those high probability tasks for typical businesses. Okay, that could be lead responses, follow up on leads because first time someone reaches out, they're not gonna buy. There's really small probability they're gonna buy. There, there's a whole sales cycle. It could be a couple of days to a couple of months or years, depending on the product. So you can. Use AI to basically automate that part. So the first thing is that when a lead comes in, okay, responding ASAP greatly enhances your chances to close that person.
Shayne Daughenbaugh 10:11
Sure. For
Anas Saeed 10:11
example, if there's a roofer and that roofer gets a call, and if your roof is leaking or your toilet is leaking, okay, you're gonna call someone and the whoever responds first, that's most likely the person that's at the job.
Shayne Daughenbaugh 10:23
Yep.
Anas Saeed 10:24
Okay. If you have a problem with your garage door, okay, you're not going to wait five days for someone to get back to you. Okay. So speed to lead for a lot of these home services businesses is one of the best ones. So responding to leads. The second aspect is lead nurturing. So for example, let's suppose if there's a digital marketing agency. Now, based on AI, you could send everyone a customized email every week. Now, if there are hundreds of 1000s of people in your lead list, you no person has the time or capability to write any everyone a customized one? You could write the basics, but then you could customize them for each of the your potential customers based on their persona and send it out to you. So that's lead nurture aspect.
Shayne Daughenbaugh 11:14
Sure.
Anas Saeed 11:15
Okay. Then we have sales and marketing, all and any kind of content Generation, content distribution, social media. So, for example, like if you have content of any kind, you could have an AI system that basically customizes it and posts it on specialized for each platform. So, like what works on X is not going to work on Instagram or LinkedIn or Facebook. And there's especially for small and medium businesses, they don't have a dedicated person or a team for each different one. So what you could do is that you could develop an AI system that you basically import it what you want and the type of content, and it basically customizes it and posts it for on your behalf on each of these platforms. Because like what we talked before, AI is a system multiplier, a force multiplier.
Shayne Daughenbaugh 12:00
Right, right.
Anas Saeed 12:01
Okay, so instead of you having to customize and post on each different platform, it could do that part for you. But what it can't do is it can't provide the initial content because you don't want generic AI to do something generic that basically makes you blend across the rest.
Shayne Daughenbaugh 12:17
Yes, yes.
Anas Saeed 12:18
He wants. That's where it has the limitation that the judgment exceptions and the relationships that we talked on, it can't provide that initial one. It can customize it to each platform and post it there, but it can't do the initial one. Other than that, aspects like it could help you if you have a large database. Okay, any you could reach out to them in a customized fashion and bring in more leads. So one thing is that this, so that's the lead gen part. Another great aspect about artificial intelligence is that, for often all of these businesses nowadays, they have a lot of tools that they use, and all those tools generate a lot of data, and what you could do is that you could get all that data and plug it into an AI system, which becomes your operating system or your backbone. What it could do is that it could basically see all you have all your tools, all your data, and you put an AI layer on top of it. That allows you to basically have great intelligence into what's going on, what's not going on, and what should be going on, and on top of that, you could create AI agents which are advisors. So, for example, okay, if you had like an Elon Musk, a Steve Jobs in your company, your revenue would skyrocket. We can't have those people for small and medium businesses, but what you could do is that you could have like a sales agent, which looks at all your data and gives you advice customized based on what you do and don't do to how to increase sales. So you could do this for different domains: sales, marketing, operations, finances, business strategy, human resources. So it's basically customized AI agents for a specific domain that has all the context and the data of your business and helps you see how to improve your business for that domain.
Shayne Daughenbaugh 14:09
Sure. So so let me let me let me ask a quick question on that because I'm I'm reminded back to our previous conversation. One of the things that you said was garbage in, garbage out. Yes. So in regards to what you just talked about, with you know consolidating this data so that you can get a you know the intelligence to look at the broader scope. What kind? How can I know, or or how can we help our our our listeners know what what kind of data would be best, and what kind of data to try to avoid? Like if I just chuck everything in there, it's just going to be kind of a tangled mess. But what would be specific data that you know that you can think of? Just real easy off the top of your head. Not you don't have to go too deep in this.
Anas Saeed 14:51
So let me tell you this, okay? Data is the foundation on which art of AI is built. So if you have a beautiful home, data would. The concrete foundation on which that whole home is built. If you have a shoddy foundation, that home is gonna fall apart.
Shayne Daughenbaugh 15:06
Sure.
Anas Saeed 15:07
So what happens is that that's why a lot of times for AI engineering, a significant part of that is cleaning and fixing the data to give it to the AI system because garbage in, garbage out.
Shayne Daughenbaugh 15:22
Right, right.
Anas Saeed 15:23
So as far as the data happens, what we often do is that the tools and products that the company uses on a routinely basis, we get live data from it through its APIs.
Shayne Daughenbaugh 15:40
Okay, so just for example,
Anas Saeed 15:41
you could connect Stripe, you could connect calendars, you could collect email accounts, you could connect bank accounts, and like for example, for a lot of these home services businesses, House Pro call is used. So you can connect the APIs of that. So you can basically all the work orders, all the invoices, all all the employees' calendars. So you get real live data. What's actually happening in the business right now? Okay. So if, for example, garbage data would be you get a dump of all the invoices sent four years ago. That's utterly useless. But if you put in the invoices that are gonna go out this month. That's useful
Shayne Daughenbaugh 16:23
data. Okay, so more recent data. Not not you don't need nine years of my Excel spreadsheets and all of that thrown in there.
Anas Saeed 16:31
Because think of it this way: simply that okay, what happened nine years ago might not be relevant today. Ah,
Shayne Daughenbaugh 16:38
yes.
Anas Saeed 16:39
So what you basically need is that for this kind of the AI layer that's working on top of your data, typically we connect live feeds.
Shayne Daughenbaugh 16:47
Okay.
Anas Saeed 16:48
So your social media content, email accounts, finance invoices, production orders, Stripe, all this live data, if you connect it to an AI layer, obviously one thing to have to make sure is data security. Let's keep that in mind. You connect that, and now that's why that AI layer has access to the data and the context in a real-time aspect. And to think of it this way, if you can wake up in the morning and see, hey, what's going on in my business? What's not going on, and what should be going on? How beneficial will be that?
Shayne Daughenbaugh 17:25
Yes, right. For a
Anas Saeed 17:26
lot of businesses, okay, as they grow, one of the biggest problems that happens is what was written in the book Only the Paranoid Survives. That Andy Grove wrote that these companies' leaders they start living in glass castles far removed, and the snow force melts at the edges. Okay, so you basically need intelligence into what's going on, what's not going on, and what should be going on, and only then can you operate correctly. And when you add an AI layer that basically can summarize that all that data,
Shayne Daughenbaugh 17:56
yeah. Okay,
Anas Saeed 17:56
so and tell you exactly based on that what you have, that what you should do, what you should not do for each of these domains, that's valuable. So here we go from simple chatbots to an AI operating system, which is like a command center and backbone that runs the whole enterprise. That's the key.
Shayne Daughenbaugh 18:13
Okay, so that's what what you're describing to me sounds like that's where it would shift from. I'm just paying $20 a month, you know, for the pro version, to something after I understand it, get a little bit better. Then we up it to giving, you know, giving it a little more. So now I'm using like enterprise, you know, maybe whatever the price may be could be up to 100 bucks a month. But but that's going to is that going to? As people are listening to this, some of them, you know, bells are going to go off. You know, as if I'm a small mom and pop, and I'm thinking about my hardware store that I'm sending stuff out everywhere. I don't want all that data. You know, what's what's it going to do with you know my friend Fred Rogers over here and all of his home stuff? But when we move to the enterprise, that's where things get a little more protected. Would you say? You know, as you move up in tiers with with the AI platform, whatever platform you're using, right? And I mean, that's that's what I'm assuming, yeah.
Anas Saeed 19:08
So first thing I want to clarify is that these different tiers, from $20 to $100, $200, or whatever, those are diff just for personal use for this kind of system. You the model doesn't matter.
Shayne Daughenbaugh 19:21
Okay.
Anas Saeed 19:22
Okay. When you have a system, you could plug and play models. Okay, because models change all the time today. What is better? Tomorrow the second one is better.
Shayne Daughenbaugh 19:31
Yeah. Sure.
Anas Saeed 19:32
And the other thing is that for these kind of systems, like I said, data security is a simple is an important aspect. So what we could often do is that we could have a local model where all your data is stored on your server at your premise.
Shayne Daughenbaugh 19:46
Oh yes.
Anas Saeed 19:47
So in that case, okay, you're not sending data anywhere, and you don't even have a subscription that you pay. You do pay upfront capital cost of the server because you need at least a $3,000 machine, or. If you're talking about a big enterprise with a lot of users, you can go to 25, 30,000. There's no top limit.
Shayne Daughenbaugh 20:06
Sure, but
Anas Saeed 20:07
the model is not important. The model is just like, for example, if you have any like, let me give you this analogy. If you're going to the airport and you call an Uber, does it really matter to you that if a Camry comes or an Accord comes?
Shayne Daughenbaugh 20:20
As long as I get to my hotel, you know, or wherever. One
Anas Saeed 20:23
of the biggest things is that how the driver drives there might be a bigger ask. So that's why it's more about how you set up the system and what intelligence you're getting from the system. The models you can swap in and out. Okay, you could even use local models. That's why I want to emphasize that point.
Shayne Daughenbaugh 20:40
Okay. Okay. Okay. But
Anas Saeed 20:42
and here's another thing. Okay, like with that hardware example, if you wake up in the morning and you see how many invoices are unpaid, and you can see exactly instead of digging through all the material, all the spreadsheets everywhere, you can see in one place how many invoices are unpaid. That's real value. If you can see that, okay, what if there's a home contractor and they can see how many estimates are not followed up law, and you click a button and every week on Monday morning you send up something customized to that person, that's gonna generate money. You can see, okay, which employees are doing good and which are not. That's gonna be real revenue. Those are the things that that AI layer could help you do.
Shayne Daughenbaugh 21:24
And that that is from from where we started with this question, you know, on on where business business should look first. That's that's another level up because we started talking about leads and sales and marketing. You know how to how to promote that kind of stuff. Now we're taking it kind of a little bit further beyond when you have something maybe even in house, like you were talking about. So that that sounds like that that's a even another another step. So there's tons of of or I shouldn't say tons. I don't want to over exaggerate, but but there seems to be a lot of levels you of of AI use would you say?
Anas Saeed 22:03
So let me simply put it this way: the more sugar you put, the sweeter it'll get. So what happens is that okay, using a chatbot is just step one. Okay, there's this like first you crawl, then you walk, then you run. Sure. Okay, in transportation, first you use a bicycle, then you use a car, then there's jets and there's there's rockets. So there's always levels. The step one, like I said, is use a chatbot and see what's working.
Shayne Daughenbaugh 22:28
Yeah.
Anas Saeed 22:28
Second step is custom workflows. That okay. If there's some process that happens quite often in your business, that's repetitive, time-consuming, rule-based, and copy-paste off often, high volume. You can. There can be aspects of it, or there can be whole tasks or custom workflows that automate those. The level, the best level is where you do AI systems, and there are this AI system that I defined for you was basically a backend operating system. Okay.
Anas Saeed 23:00
Another thing is that you could use artificial intelligence to generate leads, and you could use artificial intelligence to nurture those leads into paying customers, and then you can use artificial intelligence to run your business. And then with running your business, or these, there are a lot of smaller aspects of it, and there is no limit to that.
Shayne Daughenbaugh 23:17
Got you. So thank you for for kind of laying out the map of the possibilities. You don't have to start with you know the enterprise system, but if you're going to use AI, that's at least a direction you would want to go. Let's let's we're kind of running out of time now, so I won't talk about one more question. In all that you've talked about, you know, with the lead generations and all of these tasks, all the different ways of using AI. Where are businesses seeing the biggest efficiency gains by using AI? What are some? If you could give some, some, some real life like examples of.
Anas Saeed 23:56
So one of the biggest and best uses of artificial intelligence is bringing in more leads, bringing in more business, and one of the best reasons for that is that's something bringing in more money is something business owners love, and for any small business owners, one of the biggest reasons they're small is because they don't have enough leads. That's the reality. So when you basically what thing one thing is that you could do novel AI-based lead generation, pretty much for any business, where it could basically go and actively search for leads, people that could become your potential customers. That's one of the best best ones. The second one is lead nurturing. Like I said, okay, if you have 1000 people in your list for a digital marketing agency, you could send out customized emails or any other form of contact every week or any cadence you define, and that could generate nurture them towards completion.
Shayne Daughenbaugh 24:54
Right.
Anas Saeed 24:55
And the third thing is that for AI operating system, yeah, it helps you run the business, give you visibility. In the business, so it mostly depends on how you use it.
Shayne Daughenbaugh 25:05
Okay,
Anas Saeed 25:06
that's what I will emphasize.
Shayne Daughenbaugh 25:08
And and so as as I actually thought about again in in relation to that question, because we've been talking about lead generation and all of that, but what we haven't or what's behind the the the assumption or the scenes with this is lead generation takes time. Yes, you know, do I have the time to write all these emails, send them each out, even if I'm doing bulk? You know, do I have the time to create all this content and try the the thought work that says, oh, I have to write this out? So what what we're describing here with the efficiency is instead of so this in in regards to efficiency this this frees up my time that I would need to be doing to you know do more lead generation or the nurturing of the leads or the creation of the content
Anas Saeed 25:57
yeah so like one practical example I can give you is like one system that we worked on was we were doing outreaches for law firms, and the AI system what it did was that it basically for each law firm it would go to their website, scan the whole website, and find one phrase that would define that law firm. So like someone would basically say that hey I am. They would like to emphasize that we're trust-based. Other would like emphasize their personalized, personalized approach. Other would emphasize we're local. So when we do an outreach, we add that single phrase in the first line. That skyrockets the reply rate because now you're not sending cold email mass bulk. Now think of it this way: as a human, okay, you're not going to be able to do that. But now we could basically customize each line, the first line of the intro, based on that person. That kind of stuff. And for example, if you use that for lead generation or free lead nurturing, it's going to skyrocket your results. So
Shayne Daughenbaugh 27:04
that makes sense. Yeah, yeah, yeah. So we're using it not just to write it, but to research it. All again, all of that would take me hours to do, but if I can automate those things, that kind of grunt work, as you described, important stuff. Still, this isn't just you know this isn't non-important stuff, but it's still important stuff that frees me up to do other things. I love I love where you're going with this. So one, it
Anas Saeed 27:28
frees you up to do other stuff. The second, it makes things that were not viable viable again. So for example, okay, like if you're reaching out to 1000 law firms, no person is gonna go through all their website each week, or if you're doing mass bulk email to all law firms in all of America, no person is gonna research each one, figure out the most important thing, and do it, and customize the email accordingly. And that that kind of customization could you could add at a lot of levels, so like you could research all their websites, all their social media contents, all the cases that they have filed, all the lawyers that they have. Where did they go to law school? Where did they do their JD? Where did they do stuff before? You research all of that. Based on that, you customize the outreach that you write to them. You customize the lead response, and that's just one example. This could be done for a lot of different examples. For example, like for the digital marketing agency, for all the leads that you have, it's typically work emails. For work emails, you could see which company they are in, and for that company, you could customize it. Now, that kind of response email would get a much higher response, and this is just one example. Where I talked before, okay, we were short on time, so I'll just keep it concise. Where we talked before, a lot of those customized examples where you could customize based on LLMs is where you could increase the efficiency manifold. That's the key.
Shayne Daughenbaugh 28:57
Got you, got you. That's that's. This has been great, Dr. Said. I and I apologize that that I I need to say we got to go. But but this has been some fantastic stuff talked about. You know, just for recap, we talked about if someone's really interested, where to begin. You know, what are some business areas they should look at, and even kind of how what are some of the biggest efficiencies that can be found. We've hit all of those things. I feel great about it. Is there any last things that you want to say here before we before we wrap up?
Anas Saeed 29:30
One of the main things I'll say is that AI is going to change a lot of industry, all the industries. It's better to get on board and get started rather than be left behind. I see it from a vantage point where I can see this stuff, and that's why I'm saying it from the bottom of my heart that like things are gonna change for sure. So it's better to get on board. Like for example, electricity changed everything, fire changed everything, internet changed everything, social media changed everything. It's going to be the same thing with AI, and it's going to be even bigger and even faster. And like those small examples that I gave you, just like that, there could be based on your business 1000s of such stuff.
Shayne Daughenbaugh 30:12
Right. Okay.
Anas Saeed 30:13
Better get on board and get ahead of the curve because there are going to be two types of companies: those that get on board and those get left behind. And we all know where we want to be.
Shayne Daughenbaugh 30:22
We want to be. We want to be ahead. That's where we want to be. Keep going. Well, thank you so much for the time that you've given us once again. It has been my pleasure. I know that I think last time we we suggested that they could find you. Our audience could find you on LinkedIn, Dr. Sayed, there on LinkedIn, we'll put those all the links in our show notes, so you'll be able to see those. Thank you so much, ladies and gentlemen, for watching. We hope that you have found this stimulating, and and if so, tell us in some of the comments to to whatever platform you're watching. Tell us what it is about this that you're super interested in, or what are you hesitant about, or what are you worried about with that? We will take either one of those. Anyways, have yourself a great day, ladies and gentlemen. Thanks again, and thank you, Dr. Saeed.