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Hi. I'm Ollie from Count, and I wanna show you a completely new way that you can Too much too much feels, not enough words. Also, you haven't put the screen on stage, so it wasn't gonna work anyway. So we're We're good. Right. Should we kick off Whenever I'm ready. Just put your finger. Okay. Hey. I'm Ollie from Count, and I wanna show you a completely new way to see and explore your business with AI. So this is the Count Canvas. The canvas is built to give AI the space and scale it needs to help me and my team dig into our data. So I wanna get a handle on a few things going on in my pretend ecommerce business. So I'm gonna add an agent into the canvas and ask it a question. Hey. What's going on in Chicago? So that's a pretty ambiguous question. So it may take a bit of time for our agent to really dig in to what's really going on. But because Counter collaborative space, I can invite Harriet into the Canvas with me to help me start to explore the problem a different way. Hey, Harry. How are you? Hey. So what else should we look at? I've got this agent looking looking at the Chicago problem. It's bringing back some stuff, but it's gonna keep going. So what should we do in in the meantime? Nice. Why don't we look at the product segment split as well? Let's do it. I'll follow you. Great. I'll come up here and ask the question: Make a single dashboard containing three charts over time, looking at profit, sales and orders, with each chart split by segment and grouped by month. Oh, wow. Here it is. So one of the best things about working with AI in count is that every object the AI builds is editable. So it means I can click on a chart, see exactly what the AI has done. And if I want to, I can make tweaks myself. So, Harry, what should we dig into next? I think down here something dodgy looks like it's going on. Yeah. That looks like a big drop. Right. So we could ask the AI to dig into this more, but why don't we just take this chart and move it up here and do a bit of exploration ourselves. So I'm gonna move segment to the filters and make that just for the corporate bit, which where we saw the problem. And then I'm gonna add in a ship mode as color split so we can see if that's the issue. And lo and behold, it is. Looks like standard class is the issue. Now, Harriet and I could work with the AI more by doing more advanced analysis with SQL and Python if we wanted to to really dig in. But why don't we go and see what the other agents been doing in the meantime? Got Got it. Oh, wow. So we can see it started digging really quite a long way down. So we can click on the AI agent here and see what it's been doing. You can see it's been viewing results, editing the canvas. When it's made a mistake, it's gone away and try to fix that mistake to make sure it's getting us the right answers. It's taken us an overview and then broken that out. As it's found more information, it's branching out to show us exactly the full story. So it's gonna continue to do that. But hopefully, this gives you an idea of how Count is a collaborative AI driven way to explore your business with data. Hi. I'm Ollie from Count, and I wanna show you a completely new way that you can see and explore your business using AI. So this is the count canvas. The canvas is built to give AI the space and the scale it needs to really help me and my team dig into our data. So I wanna get a handle on a few questions going on in my pretend ecommerce business. So I'm gonna add an agent into the canvas and ask it and ask it to help me with a question. Hey. What's going on in Chicago? Now that's a pretty ambiguous question. So this agent's gonna go away and may take a bit of time to really dig into that answer. But because count's a collaborative space, I can invite Harriet into the canvas so we can start to tackle a problem a different way. Hey, Harriet. How are you? Hey, Ollie. So we've got this agent cracking into the Chicago problem. What else should we look at in the meantime? Why don't we take a look at the product segment split? Sounds good. I'll follow you. Nice. I'll just come up here. And can you make a single dashboard containing three charts over time, looking at profit, sales, and orders each chart split by segment and grouped by month. Nice. Here we go. So one of the best things about using AI Encounter is that every object the AI makes is editable by users. So you can go in there and look exactly what the AI has done, make sure it's doing everything correctly, and potentially make changes yourself. So, So Harriet, where should we look into next? I think there's something pretty suspicious going on down here in Chicago with the corporate segment. That's a pretty big drop, isn't it? So I could ask the AI to go look into this more, but why don't we just take that chart and do some exploration ourselves? So what I'll do is I'll move segment down to the filters area, and then I'll also look at different charts by ship mode in case that's the issue. And, yeah, look. Looks like standard classes are the thing that's dropped here. So at this point, we could work with the AI even more, start writing SQL or Python, do some more advanced analytics with Harry and I just working through the problem with the AI to get to the issue together. Hey Ollie, it looks like the agent has done some more with your original question. Let's go have a look. Oh, yeah. It's got lots here, isn't it? So let's go see what it's been doing. So you can see that this is the train of thought it's been going through. You can see it's been editing the canvas, viewing the results it's brought back, and that's led it to go down a train of thought. And you can see it's structuring its thinking as it's going. So it's given us an overview, and then it's also given us market performance by time, looking at negative profits, category performance, customer segments, and profitability analysis. And as it goes, it just branches more and more down the page as it finds things. So we'll leave this to keep going. Hopefully this gives you an idea of how Count is a collaborative, AI driven way to explore your business with data. Hi. I'm Ollie from and I'm gonna show you a completely new way that you can see and explore your business with AI. So this is the CAULT Canvas. The Canvas has been built to give AI the scale and space it needs to help dig help me and my team. Okay. Keep rolling. Keep rolling. Hi. I'm Ollie from Count, and I wanna show you a completely new way you can see and explore your data, Your business. Your business. Hi. I'm Ollie from Count, and I wanna show you a completely new way you can see and explore your business using AI. So this is the Count Canvas. The canvas has been built to give AI the scale and space it needs to help me and my team dig into our data. So I wanna get a handle on a few things going on in my pretend ecommerce business. So I'm gonna add an agent into the canvas and ask it a question. Hey. What's going on in Chicago? So that's a pretty ambiguous question. So we're gonna give the agent a bit of time to really understand what's going on and bring back some answers. Because Count's a collaborative canvas, I can bring in Harriet from my team so we can still keep working through the problem. Hey, Harriet. How are you? Hey, Ollie. So I've got the agent working through the problem. You can see it's starting to bring up results already. While it's doing that, why don't we go ask a few other questions instead? What should we do? Yeah. Why don't we have a look at product segment split? That sounds great. I'm gonna follow you. Okay. Great. I think I would like to know Can you make a single dashboard containing three charts over time looking at profit, sales, and orders, and with each chart split by segment and grouped by month. Wow. Here we go. So one of the best things about using AI Encounter is that every object the AI builds is editable by users. This means you can click on any chart to see exactly what the AI has done and potentially make edits yourself. So Harriet, what do you think we should look at next? I think there's something pretty suspicious going on down here in Chicago at the corporate segment. Pretty big drop, wasn't it? Well, we can get the AI to look into this more, but why don't we just copy this chart up here and do some exploration ourselves? So I'm gonna move segment to the filters section just so we're looking at that corporate segment we were looking at. And then I'm gonna add ship mode here to the chart so we can see how it looks for different ships. And looks like standard class is the big corporate there. So we could keep digging into this more. Harry and I could work with the AI to do some more advanced analytics like Python SQL, just to really see what's going on. Oh, hey, Ollie. It looks like the original agent with your question has done some more. Okay. Let's go back and look. Oh, yeah. So you can see, we can click on the agent and see what it's been doing. You can see it's chain of thought. We can see it's been viewing results of its queries. When it's made a mistake, it's correcting it itself. And as it's going, it's laying out the story really clearly. So we can see that it's realized it's been that Chicago has been losing money, and that it's been breaking the problem down, looking at discount strategies, plot performance. Oh, it's made a change. It's also been looking at how these issues have been trending over time. So we're gonna leave the AI to continue to dig into this. But hopefully, you can see that HatCount is a wonderful collaborative AI driven way to explore your business with data. Hi. I'm Ollie from and I wanna show you a completely new way you can see and explore your business with AI. So this is the count canvas. Canvas is being built to give AI the space and scale it needs to help me and my team understand our data really well. So I'm gonna ask Keep rolling. Hi. I'm Ollie from Count, and I wanna show you a completely new way you can see and explore your business with AI. So this is the count canvas. The canvas has been built to give AI the space and scale it needs to help me and my team really dig into our data. So I wanna get a handle on a few things going on in my pretend ecommerce business. So I'm gonna add an agent to the canvas and ask it a question. Hey. What's going on in Chicago? That's a pretty ambiguous question, so it may take the agent a bit of time to really dig into numbers and see what's going on. But because count's a collaborative space, I can ask Harriet for my team to come in and help me tackle a problem a different way. I'm glad it was you this time rather than me. It's always been me so far, so that's good. Okay. I'm gone. My friend, like Harriet. Okay. That's good. Rolling? Yeah. Cool. Hi. I'm Ollie from Count, and I wanna show you a complete Hi. I'm Ollie from Count, and I wanna show you a completely new way to see and explore your business with AI. So this is the Count Canvas. The canvas is built to give AI the space and scale it needs to help me and my team dig into our data. So I wanna get a handle on a few things going on in my pretend ecommerce business. So I'm gonna add an agent to the canvas, and I'm gonna ask it a question. Hey. What's going on in Chicago? So that's a pretty ambiguous question. So I'm gonna leave the agent to get on with that and really see what's going on. But because counter collaborative space, I can bring in my colleague, Harriet, and we can start to wrestle the problem a different way. Hey, Harriet. How are you? Hey Ollie. So I've got this agent in here starting to tackle the Chicago issue. What could we be looking at in the meantime? Nice. Why don't we look at the product segment split? Sounds good. Right. I'll follow you. Great. I'll come up here. And ask Make a single dashboard containing three charts over time, looking at profit, sales, and orders with each chart split by segment and grouped by month, and then make the same dashboard next door but just for Chicago. Here we go. So one of the best things about using, AI in count is that every object the AI builds is editable by users. So you can come in and click on a chart, see exactly what the AI has done, and make some small tweaks yourself. So, Harry, what should we dig into next? I think there's something pretty suspicious going on down here with the corporate segment Tushka. Yeah. That looks pretty bad. So we could get the AI to look into this asset itself, but why don't we just take that chart ourselves and do a bit of exploration. So gonna move that segment down to the filters so we can isolate that corporate issue. And then I'm gonna actually guess that maybe ship mode's an issue, and so add that to the chart. There we go. Looks like standard class is is the issue. So, Harriet and I could keep digging into this more with our AI. We could be writing SQL and Python code to do some more detailed analytics. But Harriet, why don't we go back and see what the original agent is doing and how it's getting on? Yeah. Go ahead. Oh, wow. So it's been going quite at it. There's a lot. It's so annoying how, like, they have a lapse. Yeah. Okay. There's time for another. There's time for another. We've got a four o'clock stop. Yep. I'm gonna remove myself. I'm gonna close it all. One sec. Okay. Okay. Who's ready? Oh, Oh, you dropped. Okay. I was gonna use a different canvas, sorry, to change it as we Ciao. Oh, sorry. I realized one way of Hi. I'm Ollie from Count, and I wanna show you a completely new way that you can see and explore your business with AI. So this is the Count Canvas. The has been built to give AI the space and scale it needs to help me and my team dig into our data. So I wanna get a handle on a few things going on in my pretend ecommerce business. So I'm gonna add an agent into the canvas and ask it a question. Hey. What's going on in Chicago? So that's a pretty ambiguous question. So it may take the AI agent a bit of time to really dig into what's going on. But because counts are collaborative space, I can bring my team Harriet into the into the canvas so we can start tackling the problem a different way. Hey, Harriet. How are you? Hey, Ollie. So I've got our agent here looking into the Chicago issue. It's already bringing back some stuff. But why don't we go in here and tackle the problem a different way in the meantime? Nice. Why don't we have a look at the product segments, but instead? Let's go. Great. Let me ask a question here. Can you make a single dashboard containing three charts over time, looking at profit, sales, and orders with each chart split by segment, Group by month, and then make the same dashboard next door, but just for Chicago. Here we go. So one of the the great things about working with AI in count is that every object the AI builds is is editable by users. So I can click on any of these charts, see what the AI has done, and make small tweaks myself. So, Harriet, what should we do next? I think there's something pretty dodgy going on over here for Chicago with the corporate segment. That doesn't look good, does it? Now we could get the AI to dig into this more, but why don't we just take this chart and do a bit of exploration ourselves? So I'll drag this chart up here. I'll move the segment to the filter so we can just isolate that corporate segment. And then I might add in ship mode into this chart just to see if that could be the issue. Yeah, there you go. Looks like standard class is the problem. So Harry, you and I, we could keep going with the AI here. We could go in further. We could use some SQL or Python code to like go a bit further advanced analysis. But why don't we go back and check how the AI is doing in that original Question. Yeah. Good at it. Oh, I can see it's still going going out here. So we can click on the AI and see its audit trail. We can see what it's been doing. We can see when it's been failing to answer the question and repeating and editing itself. You can see what it's been doing with orders, sales trends, and it's been laying out its thinking in the canvas as it's gone. Popped it. Just errors everywhere. Oh, a real shame. Okay, One more. It's worth it. Doing well. Goodbye. K. You're off stage. I'm deleting. Higher energy. Higher energy. Okay. I zoom in because he needs to be a hundred percent. Right. Okay. Three two One. Hi. I'm Ollie from and I wanna show you a completely new way that you can see and explore your business using AI. So this is the count canvas. The canvas has been built to give AI the space and scale it I've got a phone with Right? This is not there. This really is the last time I think we're gonna do this. Let me go call it. Hi. I'm Ollie from and I wanna show you a completely new way that you can see and explore your business with AI. This is the Count canvas. The canvas has been built to give AI the space and scale it meet needs. Damn it. Damn it. Oh. Oh. Hi. I'm Ollie from Count, and I wanna show you a completely new way that you can see and explore your business using AI. This is the count canvas. The canvas is being built to give AI the space and scale it needs to really help me and my team dig into our data. So I wanna get a handle on a few things going on in my pretend ecommerce business. So I'm gonna add an agent into the canvas and ask it a question. Hey. What's going on in Chicago? So that's a pretty ambiguous question, and it may take the agent a bit of time to really dig into exactly what's going on. But because CAUNT's a collaborative space, I can invite my team, Harriet, to come join me and get into the problem a different way. Hey, Harriet. How's it going? Hey, Ollie. So I can see our agent is digging into the Chicago issue, it's bringing back some results already. But why don't we go off and do a bit more exploration somewhere else and see what else we can find? Nice. Yeah. Why don't we look at the product segment split? Sounds good. I'll follow you. Great. I'll start up here, and let's make a single dashboard containing three charts over time, looking at profit, sales, and orders with each chart split by segment, grouped by month, and then make the same dashboard next door but just for Chicago. Here Here we go. So one of the best things about working in count is that everything the AI builds is editable and viewable by humans. So I can click on this chart, I can see what it's built, I may make a few changes myself. So, Harriet, where should we look next? I think there's something pretty suspicious going on down here in Chicago, the corporate segment. Yeah, I'd agree. That's a pretty big drop, isn't it? So we could get the AI to go and explore the spores, but why don't we, in this case, just take that that chart, we Move it above and then have a bit of explore ourselves. So I'll move the segment to the the filters here, so we're isolating just that corporate segment. And then maybe I'll add in ship mode into the chart just in case that's the issue. Yep. Looks like standard class is not doing us any favors here. So we could keep digging into the data here. Harriet and I could be asking the AI to go a bit further with maybe some Python analysis or SQL to go even deeper and do some more advanced calculations. But Harriet, why don't we go back and look at all the original AI has been doing so far? Yeah, good idea. Okay. It's been doing been busy. So you can see I'll click on the agent here, and you can see it's chain of thought. It's been editing the canvas. It's been viewing the results, and then digging further and further. And as it's going, it's laying out the story as it's as it's as it's going. So you can see here, it's being a severe financial distress, it looks like. And it's been digging further into that with profitability analysis and returns analysis. But it's also been looking at the different angles, looking at different segments, phone lead sales dropping, and looking at things over time. So we'll leave this to keep going, but hopefully this gives you a sense of how Count is a collaborative AI driven way to explore your business with data.