AWS re:Invent 2024 - Revolutionizing supply chain: Jabil's journey with Amazon Q Business (AIM253)

thank you for the jable team for coming out here excited to do this presentation with you guys I'm going to give you guys a quick overview of Q business and some of the launches and how we're working uh Q business on supply chain and then I I'll give it over to the jable team may and the good stuff will begin these are some cool slides um slowing showing how massive Supply chains have gotten and of course how jable is involved in supply chain we're going to get through these because I want to get to the fun stuff come on here we go hold on hold on okay here we go so hopefully many of you saw the keynote this morning and you heard a lot of the things that Matt and Andy were talking about Amazon's essentially been using machine learning in in our logistics for the last 25 years and so you look at 4,000 products sold per minute on Amazon um the way we match products to users is is via machine learning um the first primary delivery was on in December 2016 we used neural networks to make these deliveries possible uh we have billions of Alexa interactions each week powered by about 18 models generative uh machine learning models under the hood we have 1.6 million packages delivered every single day if you listen to Andy this morning by using machine learning and generative Ai and just this last year we cut that by 10% sorry we increased the speed of which we can deliver those those packages by 10% so we've been doing this for a very long time uh rofus hopefully some of you who are Shoppers on Amazon have used Rufus to help find products more efficiently um our Pharmacy Amazon Pharmacy we're helping fill prescriptions Faster by leveraging gener generative Ai and ads of course you know that we're matching ads to our customers and we're using generative AI to match the best possible advertisement to the customer possible possible and then finally ma Mastro is our playlist generator on Amazon music and again just we the the point of this these last two slides is just to show how deep the experience we have using generative Ai and machine learning to make our products for our customers better so here's a cool little video um the paths that optimize robotic picking routes and F fulfillment centers are always getting more and more complicated and more complex and the routes that these packages can take through the Fulfillment center become more and more complex and again we're using machine learning every single day to squeeze out every piece of inventory every piece of productivity to deliver packages faster to our customers out of our fulfillment centers so what are we going to talk about today the business impact of generative AI um some of the generative AI use cases in supply chain specifically as it relates to jable um q q business and Q apps Q apps is a capability inside of Q business that we'll talk about briefly and then the really fun stuff is jael's uh generative AI Journey that may will get to momentarily so this is actually one of sles because again we expect generative AI to impact 80% of jobs the reason why this is most exciting to me is because I believe that things like Amazon Q which we're about to talk about is where that's really going to happen when you the things that impact everyday users the business users the non-technical users can use these products seamlessly to help them be more productive and be more effective that's how we're going to get this to 80% so the business impact of generative Ai and supply chain you know 43% of working hours across supply chain activities could be impacted by generative AI um 29% of working hours could be impacted .5 trillion dollar so these ma these numbers are just massive and using generative AI to move the needles and more effective Supply chains is present a massive opportunity I don't am I going to skip over this one so this is the generative AI stack how we think about it in AWS at the bottom here we'll get through this quickly but at the bottom here you have things like Sage maker our chips hopefully you heard about those this morning tranium where you can you know um is I consider this like the operating system for our customers like you to build applications on top of these models and at the very top of the stack my favorite area is the application layer and this is Amazon q and app uh AWS app Studio we're only going to focus on Amazon Q today but this is like the top of the stack you know really that fully managed layer using generative AI to help businesses like you be more productive and more efficient so what's Amazon Q business Amazon Q business is the most capable generative AI assistant helping you get access to information massive amounts ofation information helping you get insights into those documents and actually now we're helping you take action and actually do work and execute work against that data and so um what's very cool about Amazon Q business is as you load this data and you load these documents and we honor the permissions we honor the security so that people when they're using when employees are using Q business they're only able access information that you've actually permissioned them to see we connect over 40 different data ources so that's S3 Google Docs Google Drive Microsoft Office SharePoint um Confluence the list goes out and on but we really enable you to bring in your unstructured data your documents from any system you have within your organization and Q business then allows you to get those insights so this is actually a really cool feature when you ask Q business a question it actually will reference the document in which Q business found that answer and so you can see at the bottom here actually did I just uh you can see below right I'm typing in that prompt and you can see the documents that are actually being referenced for that answer and then the end user can go straight to those documents and and dig deeper so one of our customer favorite features we got these buil and connectors across all these different uh apps that I mentioned earlier so again we're enabling you to bring in your data from wherever it resides we also have a custom connector if you have homegrown on premise systems you can integrate with those as well so this is actually um one of the cool features you know perform actions using plugins today actually if you were watching The Kino we just launched 50 more of these today but essentially Q business can interact with a zenes or J created a j ticket updated jur ticket update Salesforce and so this really enables your organization pretty Advanced workflows you know as an example I need to make an update to a customer it could go upload the Salesforce entry update the ticket in zenes maybe potentially update a document and so we're enabling you to establish these pretty sophisticated workflows across multiple systems we also have custom plugins as well that allow you to create actions and take actions against custom systems that a lot of our customers have as well and then this is the most important thing that I want to hit home um we adhere to those data and privacy and security needs and so when you're pulling in these documents pulling in this information from these various systems we are honoring those permissions and that security and privacy of those documents so that when that end user when that employee comes in and asks a question or prompts Q business we only allow them to access the information that they are permissioned to see and so when we built Q business security and privacy were really there from the gecko we built these from the the ground up with security and privacy in mind and we will never ever use your information to train our models or make our models better and finally boost productivity and further I think you know the way I like to explain this is you think about like the beginning of this year you know a lot of us were asking questions about our data and getting some cool answers it was cool and then we were able to actually create content and generate content and that was cooler but I think all of us really want these things to do work for us and make our jobs easier and actually execute tasks and do things and that's where this is going and you know we released an automations engine that allows you to automate workflows think about onboarding a new employee right they got to get a badge they got to get a laptop they got to get um secure access they got to sign their contract all these things that have to happen when onboarding a new employee and through Q business through automations and Q business we're enabling you to um build these workflows end to end that actually work asynchronously and so you could think about all these complicated workflows within your organization that you'll be able to automate via Q business we have q apps uh these are think about this again some people get confused by the name Q apps Q apps is just a feature within Q business and the the best example I like to give is you know imagine there's a new employee coming in and you want to choose their level their Department um how many years of experience they have and automatically qaps will um s qfs will give you um an onboarding plan for that employee and so these things where you have these repetitive prompts that you're doing every morning or every day um you can actually create an app a very lightweight app to automate this process so you don't have to type in that prompt every single morning you get in and just it again it's just a way to make you more efficient and more effective and more productive we have a library so if you create these apps and you want to share them with with other employees and in your organization you can easily do that and very easily discoverable by other folks in your organization and that is it so I want to bring up May the star of the show this is 11 minutes I still told you it would be 10 here you go thanks so good afternoon for those who did not put on the headset you might want to do that right so I'm sure you can hear me but I'm I'm sure you'll be delighted to hear more about our success story so David thanks very much for inviting me to share this session Jaber right and for many of you guys probably Jaber is the best kept secret okay is the best kept secret but I do actually wanted to share this secret with you in a little while right so here we are what I actually put in this title is transforming manufacturing and supply chain Solution on management with Gen Ai and why are we saying what we are saying right now so for the jabber story again I I say it's the best cap secret right so for folks who doesn't know about jabber right we we heard many different pronunciation like Jabra Jabra right but Jabba is actually a manufacturing company a headquarter in USA Florida and it is actually built by this two gentlemen James and Bill so when you put James and Bill together you actually have jabble okay so it is actually a very unique manufacturing company and this is where we are right so we are a Manufacturing Company headquarter in US second largest contract Manufacturing in the world right so if you actually look at our Revenue we are close do about 29 billion and managing about 140,000 employees with over 60 years of experience so when we talk about Jaber what we are really doing is we actually manufacture right so that's our Core Business and the vision of Jaber is really to become the best the world most advanced and trusted manufacturing solution provider in the world so that's our vision so when you Google and look at Jaber that's really what we say we wanted to do so when I have such a strong vision from our chairman from our CEO so that means a lot to us right a lot to us when I'm saying that hey we are here to transform manufacturing we are here to actually shape the future of manufacturing so if you look at the business that we actually cut across we have 400 customers 400 Brands right so these are brands that you're probably holding in your pockets right or when you look up there are the satellites or when you are driving those are some of the EVS that we are Manufacturing so our business actually spends from Healthcare to to Consumer products to electronics to many many other things right so there there are so many 400 different brands that power the world so the life cycle that we are looking at for JA actually is a end to- endend life cycle right we're involved in some cases with designing of the product with the customers we are then using the product and actually do the manufacturing do the new product introduction do the manufacturing and then ship out and pack out right so it's a endtoend cycle and what is interesting right here is that when you look at Jaber in such a 29 billion Company 400 customers on a day-to-day basis we are dealing with a lot a lot of transactions we are dealing with a lot of supply chain we are dealing with a lot of global span so I bear in mind this number 25 billion of global span that we are trading through in our supply chain Network we have 38,000 suppliers within our Network right so those are the wealth of data that we are actually dealing through on a daily basis okay so this is just the backdrop as to why why we we say we we need AI right we do need AI to actually help us be more efficient be more productive and actually find ways to actually be cost effective and what's more is that when you look at we are not just a Manufacturing Company yes we are but the wealth of knowledge that we have accumulated in the manufacturing processes in supply chain is also shaping the way that we are transforming our business right for example if you read here we are also providing pra practitioner to practitioner Supply Chain Services to other manufacturers right potentially our customer or non-customers we are also teaching them and guiding them and sharing with them our best practices on how to do supply chain so that is actually a very big part of the transformation that we are doing okay so that that's actually everything about Jaber so it is not just a best cap secret it is actually a good secret right all right so when we actually start to think about hey then what are the things that I need to do to actually help to shape this transformation so AI is something that's very close to Heart right not just for me but actually for most people right here we actually started the AI Journey probably like seven eight years ago right so we started with some of the manufacturing sites actually piloting some of the computer vision solution that actually can augment inspection so that's where we actually started right so that's when before cat GPT and all the generative AI really get excited exciting for many people right but when we actually step step back and think through right so what are the key building blocks that important for us where we actually start to build a AI strategy so it is actually kind of defined by this five key pillars right so everything that we do it needs to have a value proposition why are we doing this why are we doing the AI projects that we are doing we are not doing it for PC right I think we are over the stage of PC and it is very important so this afternoon I actually attended a a kind Round Table session with with some of the industry experts right and we were actually chatting so so should we still be doing pilot should we still be doing you know poc's I think at certain point in time especially on gen AI there are a lot of good Solutions out there Q being one right so I think for us it is very clear that first of all we need to actually build our Solutions and build it knowing why we are building it okay so that's why I say it it needs to create value okay and we are shaping the way on how we are working so in fact I I just completed my long-term planning for the IT team presenting to the board and presenting to my leadership team so one of the very key Focus item that we say we're going to do is exactly what we say right the new way of working how do we actually Empower our employees very my 140,000 employees that I have right so part of it are workers but we also have knowledge workers in the whole ecosystem so how do I actually make sure that from my operators workers to technicians to my leaders my finance controller my supply chain officer my buyers how do I actually have a certain persona for them such that for every of this Persona we can actually Empower them to actually work the most effectively okay and that's where gen actually comes to play a big part of it and I'll share a little bit about what we are doing here okay so when we have all this ready I think what is important when we build the AI strategy is what is the digital core what is the digital foundation and where is it right here so again a lot of what we are talking about and I think in this morning keynote speak keynote Matt actually shared that hey it is important that when we talk about any of the things that we doing B AI or gen AI the foundation actually comes in with you need to actually have a good infrastructure you need to actually have your data in place such that you can actually start to do that so this is what I call a solid digital Foundation right how do we actually handle our data how do we look at our data how do we create the data how do we actually set a semantics layer for our data so all these are things that we have to actually do in preparation of that and the notion of continuous Improvement never stops right so I'm also driving transformation for the company so it is important why when we actually think about transformation sometime it's a buzzword that's has been thrown around right and people got scared what are you trying to replace my work with transformation no that's not what I'm talking about right I'm talking about the new way on how we use Le leverage on people process and system to do new things in a new way and in a much efficient way so the continuous Improvement needs to always kick in while we think through our strategy and very importantly how do we actually use all this AI in a responsible way so I was quite happy when you know okay uh let me step back right I was not that happy when we actually started this journey because everybody is looking at it and say hey you guys own the data hey you guys have the data hey you got you got to do this for me and that right so it come to a big discovery that we know that we don't own the data I'm not sure how many of you guys here are from it versus business all right so I'm sure you share the same sentiment as me okay so they look at you hey where's the data give me that data and give me that dashboard and give me that Insight I don't own your data right so that's when we actually started on our journey about one and a half year ago that we say hey we need to actually make the organization realize that data and the initiative needs to be owned by the functional owners okay so we set up a coun where actually appoint senior leaders right really senior leader at the VP SVP level that each of the function needs to send a representative and they sit in my data and AI counsel so collectively we all make the decision collectively they know what's their roles and respons responsibility and collectively we design a Ai and data policy that spells out what are the gut RS what are the dos and don'ts how do we actually use data and AI responsibly right of course we are in this evolving Journey we are still tweaking and actually refining our policy but I think it is a good start it's a good way to start right to make people realize that hey you don't just use your data and pass it to somebody to actually create a model for you right how do you actually Safeguard your data so those are actually a very important asset for us so that was some of the lesson learned when we actually start on this AI Journey so when we actually think through it what's important for me is the nor star what do I want to create with this gen AI initiative right so I talk about the data and AI counsel so collectively collectively we all decided that there are three categories of AI initiative that we will sponsor and run in ja right so we set up very very clear guideline that one it needs to be again remember what I was saying for Value creation right so the AI project needs to be creating value for the collective ask not just you not just her but the collective ask so we actually deep dive to actually understand what are some of the business problem what is actually affecting everybody badly right what are some of the key concerns of of processes that spending a lot of time that we can actually improve on using AI technology or machine learning right so those are what we call a category of advanced machine learning project so that's one the first pillar and remember we are a manufacturing company right I talk about our journey like 7 years ago starting on computer vision to augment our Quality Inspector so that's the second second category of computer vision projects that we are doing and last but not least the third category of AI projects that we are working on are the Gen AI project okay so the Gen AI project actually start with a norstar I call it the Nar all right they kind of change the word that use here right Jaber brain is what I aspire to create for or ja right we wanted to actually use the Gen AI technology to actually create a brain a artificial brain or a smarter brain that can actually fish all the tested knowledge that we have within the company into that brain so that we can query we can ask we can actually drive Insight from all this different knowledge that we have right that is a lot of knowledge think about it right so I have 100 different location operating out of 35 countries right so 140,000 employees every day people are coming out with different ideas so how do I capture that okay so Jaber brain is my noar I wanted to create that brain for the organization right so and that's where we said that we actually see a lot of potential value creation that I can actually get out of this so I see gentlemen nodding their head and appreciating yeah that's the that's the thing that we need right so using the technology using the data point how do I actually improve my product design think about it I have lots of DFX right design for X means anything right I have lots of DFX how do I actually leverage on the DFX that have created for product a to actually be applied to product B or C or D right and how do I actually use the lesson learn that I've learned from the manufacturing process and actually use it and be applied to to other cases so that that is about product design that's about predictive manufacturing I think anybody who is from the manufacturing this is always a use case that's talked about right so we do AI for predictive manufacturing but in reality can we really do that or how many people has already done the predictive manufacturing so I will not claim that we have done it fully but we definitely have a path to actually create predictive manufacturing which I'm pretty proud about it right so we also know that you know how do I actually use this data to actually help us in supply chain resiliency and that's a very interesting one so there are a few use cases that I'm sharing today right in fact three use cases one is actually on manufacturing itself right the other two are on supply chain okay and all this use cases are actually powered by Amazon q and in fact Amazon quick side right so what I was quite happy this morning hearing from the key note is actually the the announcement about q and quick side actually working seamlessly together so that will solve a lot of our problem also right so operations so operation really means in the manufacturing floor in the shop floor ask me how there's a joke behind ask me how right so we are working with this operation VP his name is miow right think about it it's miow so it was funny when we actually started to create this notion of ask meow right so it's like asking me how on what to do but joke aside so this is really what we are doing on ask me how on the right hand side I think that's a very familiar interface that David was actually showing right so that's the interface on Q so the challenges that we have right I would not say it's challenges it's really a lot opportunity that we have so again I think for folks who are in the manufacturing you know that we have a lot of documents a lot aot lot of documents right and you know that some of the time The Operators actually do need help right they do need help but sometimes they will not voice it right and the other big challenges is 100 location 35 countries so you can imagine a lot of our even though our documents are created in English as the standard language but a lot of our operators actually do not really understand okay so there are questions also where you know think about us our processes our smt lines our processes include mechanics lines so we have CNC injection molding and smt machines so you know for smt machine it is very common that you have a few of the equipments eror code that come out occasionally right when you're manufacturing so for example the NOA NOA Arrow 001 okay I'm just making it up okay NOA aror 001 so what does that mean for a new operator how would I remember the 10,000 er codes that's coming out from my smt machines so if I actually lock in and this is really happening today right if I lock into to my ask me how and I put in no code error 001 what does it mean so it will actually come out with that documentation and say this is what it means this is how you can actually solve it and this is actually a and while we are learning we are actually also taking keeping track of how many times have the arrow 001 actually come up and we are actually starting to form our knowledge base as to when you actually have discount of error what are the potential solutions that has been created so think about it right it is not if I use the analogy it is like a library that have books that answer your question but it also have answers for you before you ask your questions right so I I thought that's quite an interesting analogy so the other good things about what we using on asmi how across the site right now is is that it's multilingual right so we have folks from Poland right the documentations are in English so after coming out with error Z nor error 001 in English I just say Translate to Polish and here it goes right it actually prom me with the right answer and it actually index and refer me to where did I get this information so this is how we using it of course this is just baby step think about the possibility that we can really use it extensively across the manufacturing shop floor right this is just the baby step we use it as a library we use it as a knowledge base but what I really wanted to create is beyond that beyond that re really building a Insight a knowledge Insight on how we can solve potential problem before it actually happens it needs to be a closed loop system that actually come prom PR us before the errors happen or before before something break down in the manufacturing shop floor right so the results are obvious the results are obvious it actually reduce downtime because before it happens the operator can actually ask the questions right so it definitely increased efficiency I don't have to wait for my technician I don't have to wait for my supervisor to come in and step in and actually tell me what's going on I don't have to stop the line to actually wait for the answer so that there is a lot of good benefits that come out from this right so I'm very hopeful this is actually going to help us a lot and The Operators like it right it is basically a intelligent shop floor assistant to them so the other one is I I promise you I'm going to share about the to use case study on supply chain right pip it actually stands for procurement intelligence system or programs okay so again remember the numbers that I was talking right 25 billion of global span 350,000 suppliers that we are dealing on a daily basis so if you think about the procurement processes that we are involved in right again I I I think challenge is probably not the right one the opportunity that I do see in this whole procurement process is as a buyer right or as a category manager what is important to me is for my 400 customers I need to know when is the best time to buy my commodity right to buy my capacitor to buy my steel my raisin or whatever so we already have a system called the PIP that's built what we are adding on top of this procurement intelligence system is exactly the Amazon Q system all right think about the possibility and it it's interesting it started out with my chairman challenging me hey you know we have all the demands coming from our customers right we know what other the demands and we have all the third party reference note we we deal with the Traders we deal with you know brokerage that actually sells the part so if you married the two what are the insights that can actually provide to us as a Manufacturing Company it does actually give a very good big prompt right think about it if we are seeing a lot of Demands on capacitor okay and we are seeing that hey from the supply side there is likely to be a shortage of capacitor so what is what is the next action that I'm going to do if if I'm the procurement officer I probably will actually start to buy a lot of capacitor and stock it up right if not my customer will be running short of the capacitor so this is exactly how we using all this intelligence today so we can actually query right which I will show a video shortly on how we are using it today with Q so let me see how I can actually show that video so this is a snapshot on our pip system right and the brain so I'm not sure whether you can read it so I think what it says is what's the latest new in the electronic industry for October 20 2 four right that's what we query the queue you can see that you know when you actually question it it actually went out to actually consolidate all the internal external information the demand signal the suppliers information and consolidate and give us a report hey this is what is happening for supplier ABC this is what is happening for supplier def this is what's happening right for your customers this is actually the trend that we say so this is a lot of good insight for us okay so of of course there's more that we can do right but it this is this actually is very exciting because it actually prompt my chairman to Think Through hey you know if I actually peel the onion down a little bit right besides just buying capacitor so what are the raw material that that's being use to create this capacitor right do I need to actually go source for some you know sand or iron oril or you know I I mean it it makes his imagination run well right I'm not saying we would do that but yeah actually help him to prompt for potential business ideas that's going to come next so that was about procurement right so the other one is what we call the supply chain assistant or V command literally meaning virtual command it's a command and control system for the supply chain and remember what I said about our supply chain management we actually are very good in that and we started to provide it as a service to customer and non-customers and VC command is actually the platform that we have created and we're still evolving it right we have created to actually provide this platform for the services that we are we are providing to our customers so it includes supply chain as a service it includes logistic as a service includes procurement as a service so those are the services that we're providing to customers but if you start to think about it procurement as a service yeah I have my pip there's a lot of intelligence that I I already can actually provide to my customers so again what are the opportunity here right we are constantly looking out on how we can actually use all this Supply Chain Services to increase revenue and actually create new margin for the company okay so it is definitely a sales opportunity for us on how we actually use supply chain information right so in V common like what I say is a combination of Supply Chain Services procurement Services logistic services so everything that we're using right now is using Q to actually prompt us to actually give us what is the best landed cost for any customers who wanted to create Distribution Center so that's one how do I actually identify the risk that's involved in the supply chain right should there be an earthquake or typhoon or hurricane so for the customer Acts do we have alternative for them right so can we actually identify very quickly what are the other alternative suppliers that's around you know 10 kilomet from their area so that we can actually replenish with another new suppliers so we talk about risk management right we talk about providing the best price for our customers when we actually go out to source so that there's tons of opport opportunity right here right so in V command we create this V Commander or SC assistant to actually start to help our supply chain practitioner to actually start using all the data that we have okay again there's tons of data here right so the concept is the same right so how do I actually use all this data to actually help me prom so again that is actually a video right here so this is kind of the look and feeli right so we initiated the V command Q sorry I can't even read the word so summarize okay method is one of the company Electronics forecast so you actually go out to actually source for let's say method is our customer method Electronics of course this is pseudo name right so for method Electronics I wanted to actually know everything about methods Electronics right their data because they are our customer we can actually know and summarize their data point and we can actually go source for external information and complement it so everything that we do know about methods Electronics will help us to decide on what we want to do on the supply chain side so again remember I was talking about V command is really for a sales engine for Supply Chain Services so to me to the supply chain officer this is actually helping us to reduce the sales cycle because it's a very convincing platform it's this is a super convincing platform once we actually reduce down the cycle time on how we convince people that hey all the insights you know all the information that I collected are providing good insights to our customers it actually helped to increase our revenue and increase our margin right so those are the three use cases so on a daily basis we have many many use cases that come up and actually wanted to actually experiment on Q but again I'm not interested in experimenting right I'm interested in actually productizing it and making sure that the solution that we made it needs to replicate throughout all my 100 locations okay so again that's why the governance is actually very important for us so with that we have also set up a gen AI councel right the baby tiger cups from the big AI Council where again each of the function will come back they have to think through what is The Right Use case for them and justify what are the ROI that we are going to see okay collectively as a councel we will discuss about all this initiative and decide which is the right one where we actually need to put put resources to do it right so until we are actually ready we will actually the next thing that we'll do is probably to empower them to do it right with the guideline with the policy we will Empower them to do it and they follow a certain guideline on how to do it and that's how we can actually expedite the the the deployment so the Gen AI Journey forward right again I I said that we are still in baby steps right there are a lot of things that we can do and we we are still evolving okay so this is what we think are super important and again we call it the building blocks on how we can be successful in gen AI it includes you know teaching our people on AI literacy I think it's super important that everybody needs to have a common knowledge about what we are talking about when I talk about data when I talk about AI when I talk about gen do they know what we are talking about it needs to create a common understanding so using the workday platform we actually roll it out to every single individual and say that hey guys you guys got to complete this initial program okay so I I think it helps and we were also doing I I was doing a lot of Education session to the jab management team and also to our board right I think the whole jet GPT helps a lot because even the board members wanted to know what we are doing wanted to learn about chat GPT and this is perfect Avenue for me to actually start promoting and educating people I think with more exposure with more knowledge that's when they can actually know and support you more okay so I find that really helpful right the AI literacy the cross functional collaboration I talk about that right again it's not my job is not my only job but it's everybody's job so where everybody is involved they actually feel that they own it together value driven use cases we don't just do it for fun right we do it for a purpose what's the ROI what's the value how do you actually account for Value so for me I even created a new role for for my team right because I'm driving transformation I even created a new role that's called a value tracker a financial controller that I pull out that will actually help us to track all this value okay I I think when you are able to track Roi is it becomes more convincing collaboration on AI right so I I think partnership is super important and this is where we feel that partnering with AWS and partnering with and using the que actually give us a lot of velocity right it give me a lot of confidence because I know you know B AWS or other partners right the partners actually invested a lot on R&D they invested a lot on security and protecting our data and this is where we actually made a very hard ation that we stop all our own chatboard development right and actually focus on vendor solution so another this is another decision point right so the brain continues to grow I I do want to extract as much txed knowledge as possible right everybody has a lot of tested knowledge how do I actually use it and use it in in a good way right and API is super important here so we do actually put in place API strategy last but not least right this is actually my last slide that talks about Jaber commitment we are shaping the future of manufacturing we wanted to revolutionalize manufacturing and become responsible in harnessing the data and AI right so for me it is not just shaping the future of manufacturing we are also building with the community to build the future of the future of manufacturing so David I'm not sure where you are right now so back to you take this B I think y thank you so much may I think that's so couple things you can get going on Q business immediately you can do it from the console and spin up an app a q app you can add your data immediately and get going and start playing and you we got FAQ as a user guide and if you have an account executive or someone that you're working closely with you know we're here to offer you know solution architect support and help you get going we also help you with adoption support and train you in your end users on how to use Q business and adopt Q business so um you know feel free to leverage those resources and we're here to help and thank you guys all so much for coming you loyal followers and thank you again jable and may for uh taking the time today and uh I hope everyone has a great great rest of the week [Applause]

2024-12-24 04:17

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