- il y a 2 jours
Meet the Startups from Togg's Ecosystem
Catégorie
🤖
TechnologieTranscription
00:01So these guys are from the same ecosystem, let's keep it short and sweet. I'd like to welcome to the
00:05stage, Bulletin.
00:11Welcome.
00:18Is it working? Okay, perfect. Can you hear me? Perfect.
00:23Hello, hello all. Actually, I was planning to start with a message from our CTO, but it's a bit too
00:32noisy for us, so I want to start with a story, very recent one.
00:36The day before yesterday, we went to a decent French restaurant, Trolle de l'Entocote, if I pronounce well, with
00:44talk executives and startups around, of talk.
00:48We were in a cab, we just jumped into it, and it took 50 minutes to be there, like a
00:55couple of kilometers.
00:57Are we able to know that in advance? Well, it's very easy, you just check it from your map, the
01:03traffic, yeah?
01:05But it ended up with, I mean, catalyzing lots of discussions, lots of good ideas, which I was with Bright
01:13Startups,
01:13I was with Ahmet, senior executive of talk, and it ended up with, like, coming up five to six new
01:19projects on the go.
01:21It was perfect. I'm not going to share those for the time being, for sure, maybe next year, but I'd
01:27like to talk about the ecosystem,
01:29the interaction that we are together and buluttan inside it. But before that, I want to start with a question.
01:39What is the most talkative, what is the most inclusive phenomenon for all human beings, all businesses?
01:47What can be? Maybe four elements of nature, like fire, water, earth, air maybe?
01:57Yeah, I want to talk about air, because everybody likes it. Everybody talks about air.
02:03Air is the mixture of atmosphere, and weather is the status of atmosphere at a particular place, at a particular
02:12time, as you might guess.
02:14And I'm Gökmen, I'm the leader and hard worker of Buluttan, a weather intelligence and climate adaptation company, and I
02:22want to talk about weather and how we use it with talk and other sectors as well.
02:29But I said particular, on purpose, particular. How particular can it be? I mean, as a taxi case, we were
02:39in a cab, we were driving, we had the chance to know what can be coming in advance, but we
02:47didn't check it.
02:47It ended up good, but it can be the same for weather as well. Once you hop in a car,
02:53you can know what is coming.
02:56You can't control it, but you can control the impact to you and to your businesses.
03:03So what Buluttan does is Buluttan offers to B2B customers, starting with mobility, renewables, insurance, e-commerce, q-commerce, weather
03:16-wise solutions, B2B software service, weather-wise solutions to control the impact to our businesses.
03:26It's a funny slide, but it's happening. I mean, you see the rugs on it. I mean, I was talking
03:31about particularity. Yeah, let's say you parked your brand new car outside.
03:37Let's say a white car. Okay. Brand new one. And a hail starts. Let's say hail starts. Okay. What are
03:46you going to do?
03:50You're going to put some rugs after the hail started? Or would you want your car to give an extreme
03:58weather alert to you so that you can go park somewhere else?
04:03It's better, right? Maybe somewhere inside. Even if you stick with the rugs, it's too late to act after the
04:11hail started. It can be the storm as well.
04:13I mean, parking your car is just an example. But are you going to stick with the rugs after the
04:19hail started or the storm started?
04:21Or are you going to ask for your car to give you some alerts up front so that you can
04:28proactively act? That's what we are currently working on.
04:33I was talking about the precision. I mean, how precise you can be. I mean, hyper locality in place. Let's
04:40say precision in time.
04:43Let's say precision in the severity. I mean, as you see on the left hand side, let's go with the
04:49example of hail or storm for the car parked outside.
04:51But you can be driving. You can be planning a drive or it can be parked over there. Let's say
04:58there is a circle on the right hand side and there is a circle on the left hand side.
05:04Let's say you are sticking with the rugs. You are going to put your rugs to the car to cover
05:09from happening a damage.
05:12Would you want to put all the rugs on the right hand side as the precipitation map shows? This is
05:20a precipitation map. It is used for hail forecasting.
05:23It's used for precipitation forecasting. It's used for snow forecasting. If you choose the right hand side, then you must
05:32go with finding some rugs.
05:35And you must put on all the cars inside the purple circle. But what if it turns out that, as
05:41Bulutdan forecasted on the left hand side, it's only a minority in this area.
05:48And what if the car is tailor-based, is car-based, location-based gives alerts in the left hand side
05:56and you just go park somewhere else?
05:58And this is just an example. I mean, hail or storm are like 200 parameters as we forecasted on the
06:07left hand side, hyper-local and car-based.
06:12We are not the ones only aware of the fact that extreme weathers are severe. I mean, it's going crazy.
06:20Now, nowadays, the current damage per day is one billion. Really, I mean it. One billion per day extreme weather
06:29damage.
06:30And World Economic Forum picked as extreme weather number one impact, not once, twice, almost twice, right after the cost
06:40of living crisis just urged this year.
06:43Can you imagine? I mean, this is the number one impact for the upcoming 10 years for all of the
06:49businesses. I mean, cross-sectoral businesses.
06:51And what we do is we are making use of extreme weather alerts to all of the sectors.
06:59Like, if a lightning happens to occur, then would you want to take the right hand side? I mean, like
07:10more than 50% of that tends to be affected?
07:13Or you just need the hyper-locality. Up to you.
07:19How do we do that?
07:21Bulutan Weather Intelligence and Climate Adaptation offers hyper-local, precise, super-short-term, short-term, mid-term, long-term, and
07:32very long-term solutions,
07:34software-as-a-service solutions, modeling solutions through APIs, through products, to the customers,
07:40so that you can first make use of the data that we provide to alert for any prompt action.
07:50Or you can make use of data to plan your operation. Or you can make use of data to have
07:56a vision for the future steps.
07:59How do we do that? What's the difference? What's the different thing?
08:01There are billion-dollar companies all around, weather intelligence, and it's very, very high.
08:07What do we do differently? I mean, what we do is we collect data. I mean, data like terabytes, I
08:14mean, terabytes per month.
08:15We collect data from all of the sources, public, private, proprietary, the data that we own only.
08:22And we put that into our engine, AI-driven engine, to forecast hyper-locality.
08:27When I say hyper-local, it's like 100 meter to 100 meter, like a football pitch.
08:32Okay, can you imagine, you can forecast all the rain in a football match size for agriculture, for mobility, for
08:42logistics, whatever you call it.
08:44I mean, come up with a sector, then I will create like three solid use cases immediately.
08:49It is happening, yeah. And the engine forecasts, this engine is a physical modeling of the atmosphere as well as
08:58statistical model of the atmosphere on top of it.
09:00And the engine, the AI-driven engine, feeds into products so that you can plan your operation.
09:07I mean, imagine all of the surroundings, all of the everywhere, you are just filled with air, you are just
09:15exposed to weather.
09:16I mean, who didn't check weather as a human being? Even, I mean, at once, who didn't check it?
09:24But businesses are coming way behind to utilize it and to keep your safety weather-wise, let's say.
09:37And Bulutdan has the privilege, actually, I'm highlighting it, has the privilege to work with Turkey's pioneering smart devices, EV
09:49smart devices talk.
09:51And what we offer, what we work on is not today's best available options.
09:56What we offer is today and tomorrow's best possible, best possible solutions so that we can equip devices and it
10:04can be weather-wise.
10:05We are just conducting a weather-wise transformation for mobility.
10:09It is right before you drive. I mean, let's say you are going to go a one day long trip.
10:16Okay, and what would you do? I mean, wouldn't you check the traffic, just the map layer from the map
10:23layer?
10:23But what if you check the weather from your map, let's say, what will be coming right after you drive,
10:31you start driving?
10:32This is before the drive starts. And during the drive, what if, let's say, would you choose a road icing
10:40alert, which is stating that if the temperature is going below 3 Celsius, then it's saying, hey, there is road
10:50icing.
10:50Is it something technological? Is it sounding very good to you? Or is it something like a smart device hits
10:59through air each and every second and the location-based hyper-local alerts are driven from the car itself rather
11:08than a statistical model?
11:11What if the car says, hey, slow down, slow down. There is road icing over there. Like, it's three out
11:18of five risks. Slow down. What if it happens? It will.
11:23And the third one, it keeps being your vision after the car is even parked. I mean, you parked somewhere
11:32else and let's say it's a very low probability.
11:35But what if a lighting happens to occur? Where is severity? Would you want to save your car or would
11:44you want to get an alert from your insurance so that your car can be safe?
11:51It's on and on and on. I'm not going to share all of the details for sure. Maybe each and
11:59every year we can work on the details that we have created with talk.
12:04But I want to highlight as the taxi driver case story just as I started. We are in a car.
12:12The car is called Smart Device Talk.
12:15It's full of startups interacting with each other, interacting with talk. And it's a journey of true more platform. I'm
12:22not advertising. I'm just feeling what I'm saying.
12:24Okay. And last but not least, I'm the spokesperson of 20 people working very hard. I'm a top-notch meteorologist,
12:36top-notch data science.
12:37Located in Istanbul now. Currently operating in Europe, Africa and Turkey. I hope you be weather-wise. And if you
12:46wonder how, if you wonder why, let's talk.
12:49Right after, I'll be delighted to meet. My name is Gökman. And thanks for listening. It's an honor to speak
12:55here. Thanks a lot.
12:58Thank you, Gökman. Thank you very much. Very energetic pitch there. Thank you. So, I have a question. Just to
13:05be clear, what you're talking about is an app that goes into a car, right?
13:08Yeah. Even in the car. Even in your mobile. Even in your mobile. Okay. So, the manufacturer can install it.
13:16But also, you can just, okay, those of us who have mobiles, like Waze, for example, we install it and
13:21we can use it like that.
13:22Let's say you are sitting in a couch, okay, in your home, at your home. And you are planning a
13:26drive. What if you can check from mobile app of the car, smart device, and plan your journey tomorrow.
13:34And how will the weather will be? Hyper-local. And once you start driving, it gives alerts so that you
13:39can increase your safety. Once you park, then it keeps being your security vision.
13:44Okay. So, basically, if there's hail that is being warned, you can stop the car and put rugs on it.
13:51Or park it under the bridge, right? Yeah, hail just an example for sure.
13:55Listen, that's what we have time for. So, Gökman from Bulletin. Thank you. Thank you. Thank you very much.
14:02All right. So, let's move on from talking about cars and weather and online shopping.
14:08And...
Commentaires