SAP Business Technology Platform in 2026 - Overview ✨

The SAP business technology platform SAP BP in short is the foundation that brings together data analytics integration and application development

to power intelligent enterprise innovation.

In this kickoff session, we explore how SAP B2P is purpose-built for business application, optimizing processes across

SAP and nonSAP landscapes, and how it innovate enables transformation.

Welcome everyone to today's live expert session, an overview of SAP B2P in 2026. We are

thrilled to have you join us.

I have the pleasure of having here with me today AnaBek, product manager for SAP BDP. Anna focuses on platform related

BDP. Anna focuses on platform related cross services topics. During his past 19 years at SAP, Anna was working in

several different roles in the area of SAP's technology portfolio with a strong customer focus. And now without further

customer focus. And now without further ado, over to you, Anna.

Thank you so much Tanya for having me again also this year.

Really happy to provide this overview and the start to this really great uh session that you are planning for many years now. Thank you so much uh for

years now. Thank you so much uh for that. Um yeah so um as uh Tanya already

that. Um yeah so um as uh Tanya already mentioned uh I'm in the BTP product management uh and also this year I would like to give

you an update on what is SAP business technology um how do we see ourselves in 2026 what are some news that we also have but also

for all the ones that are not familiar with BTP until now uh give you really some insights on what you can do with it, how you can use it and which huge

benefits you can achieve by uh using the SAP business technology platform. So um

let's have a look at uh the agenda uh that I prepared for today. So we will first of all have an introduction in general. What is the business technology

general. What is the business technology platform? Uh what are we targeting? What

platform? Uh what are we targeting? What

are also maybe different views on this platform?

uh and how it is being used by different groups. Uh then we will drive go a

groups. Uh then we will drive go a little bit further into the different areas that we're addressing uh with BTP.

So this is then also an introduction for you for the further sessions that are coming up during this series to get a short introduction. So if you are

short introduction. So if you are interested in one of those topics, I really really encourage you to join um the sessions within this series that are

really looking into those different technology areas. We will have a short

technology areas. We will have a short look on what does it mean when we are talking about this multicloud u BTP platform and I will also provide you

some information on how you can start your journey with BTP if you not already uh did so until now. So let's have a

look on the motivation about why it is so important uh to think about technology platforms spec specifically in this business context that we're

providing. So if we look at

providing. So if we look at successful companies that we're seeing out there in the world, it's mainly two things that often differentiate them

from their competitors. And that's on the one hand side, they are really very agile, which means they have the possibility to react very quickly on

changes to their business. And these

changes come from several different areas. It can be that there are new

areas. It can be that there are new norms, new processes in their industries that they have to fulfill. It can be also the reaction to competitors coming

up with new ideas, new business models, industries merging uh together in a lot of areas. So that

um companies really look into new business areas and they have to quickly get on board and and get their experiences there. But often it's also

experiences there. But often it's also the technology itself that requires companies to act quickly on changes. Now if we look at AI for

on changes. Now if we look at AI for example, you have to react on that if you do not want to get left behind. Uh actually and

on the other hand side staying with AI we clearly also see the innovation piece of the coin. So that's basically the other yeah it's it's the other side of

the coin being able to react on changes on the one hand side but on the other hand side also driving innovation to drive change in your business in your

industries which means that you are able to really innovate and bring new ideas into life and this is also something that you need to fulfill if you want to

be successful. ful in your industries

be successful. ful in your industries and if you want to also lead within your industry um to not get lost and in the

end uh be just running behind uh your competition.

So what you actually are seeing when you're trying to be on the one hand side agile but on the other hand side also very innovative then you

see natural borders um or difficulties challenges that we are facing or that companies are

facing. And often looking at the

facing. And often looking at the application and process landscapes, we see a vast of different solutions, different

technologies of completely different ages ages that have to work together in different deployment models with a lot

of media breaks and um spots where actually we only see a very low automation grade. And if you want to

automation grade. And if you want to react fast to changing things, that is of course a very bad situation to drive this change because you have to then

bring it into each individual pieces of your process.

So we see those technologies and legacy systems that we have to bring together to come up to processes before we even

can start to automate them to be much more agile when things are changing. And

on the other hand side often it also is much harder then to apply new innovations and technologies into those processes and technologies that are

available.

So basically what is needed to overcome this is um or are platforms that help you on the

one hand side aligning your business processes reaching a high level of integration reaching a high level of

automation inside those processes.

Um, and also to a certain degree a common layer of technology that helps being much faster in bringing in new

things without having to really um work with several different technologies that actually have the same purpose. So estab establishing a

purpose. So estab establishing a platform that brings together those technologies centrally for your application systems as well as your innovation systems that is one of those

purposes of the platform that we're searching for and then delivering also the innovation technologies that help you make it easier to do that innovations on the platform and

basically that is the overall idea of BTP.

So if we are searching for a short definition on what is SAP BP then actually it is a platform um that helps

you do custom development, custom integrations and also custom innovations on a solid foundation and ideally

integrated into the application portfolio that SAP is offering you because yes with many customers it's the case that

a big portion of the business processes are handled within SAP's application portfolio. Nevertheless, there are the

portfolio. Nevertheless, there are the points where we need to integrate integrate between the SAP solutions, integrate between SAP and third party

solutions, integrate in between SAP solutions and your custom innovations and custom developments. And if you can do those innovations, those custom

developments on the same technology foundation as a big portion of your uh processes is already running, then definitely you will be more agile. it

will be easier to integrate and to extend your business processes with your very individual um parts of the process that

differentiate you also from your competition.

Now looking at um BTP which are then the basic pillars that we're looking on and

this changed a little bit um with um uh analytics cloud and um data sphere being now said they they did got went through

an evolution and are now offered in another deployment model. So they are now offered as um software as a service

solution in an SAP managed way as part of a business data cloud. Um we are really focusing on those custom

developments when it comes to processes and AI um and agents of course in the AI space. So when we talk about BTP today,

space. So when we talk about BTP today, we're talking about agent and application development, your custom developments to do extensions and

applications.

We have the integration piece looking at classical A2A uh integration topics, but also um working in uh event- driven

architectures, working with wellrescribed and monitored and managed APIs and so on. also not

only talking about A2A but also about B2B and B2G uh integration and then we're providing a strong AI and data foundation

for your developments uh and for your AI scenarios. the platform to create,

scenarios. the platform to create, operate and run your AI scenarios. And

underneath of course there is this strong stack of core platform capabilities like security, life cycle management,

operations and administration um that really help you um making it possible to operate your custom individualizations and extensions to your business

applications with the same technology foundation.

Now if we look at BTP from different perspectives um we also can have a look

on on how SAP for example sees um BTP and what it means for them. So if we are

as SAP looking at BTP first of all it is our harmonized technology foundation for all the business suite applications that

we're offering meaning that we have common um technologies and services that we're using for specific tasks um uh

within our stack. So for example, when it comes to identity handling, we are using the identity management services uh that are running on top of um our uh

BTP for all the solutions that we're offering. Right? If we want to offer UI

offering. Right? If we want to offer UI capabilities, we make sure that the UIs of our different applications can be brought together in a single entry point

on BTP for your um for your employees so that they do not have to work in those sites, right? It's also about

sites, right? It's also about integration, pre-integrated components and applications.

um if you're having different solutions out of the um business suite portfolio predefined or pre-integrated master data

solutions and so on and the technology that actually does this is running on BTP right so we're talking about those qualities also we're also referring to

sweet qualities that we have or that are provided for the business suite by SAP and one point that I wanted to also

mention here explicitly is in the AI area. Um if you look at the application

area. Um if you look at the application portfolio of SAP, you will see that in all lines of businesses, we included a

lot of AI [snorts] based scenarios that makes the work of the different um employees in the different lines of

businesses a lot easier. So if I am uh an HR agent and I want to create a new job posting, generative AI automatically

embedded in success factors helps me today to generate this posting. And the

interesting thing about this so overall we have now at about 400 of such scenarios embedded into our applications.

We are running, maintaining and operating those scenarios all on BTP. So

we created our own platform to operate these scenarios and make it possible to handle those 400 scenarios. And I mean the number is growing a lot for

thousands of customers that are operating our um um or their AI scenarios as part of their business

suite applications.

So it's our technology foundation to run and operate the suite on the one hand side but also when it comes to new scenarios, new developments, it's also

the platform that we are using for all kinds of new developments for new applications that we are creating at SA.

Now changing the view coming from the partner um and with this huge partner environment that we're having it's a natural thing that also this is a very

interesting and important foundation for partners that think about creating their own solutions being it as um resellers

that create things that will they will distribute. So, as independent software

distribute. So, as independent software vendors that will sell their um created solutions to a lot of customers or if we're talking about you getting partners

in that explicitly do their developments for you for your scenarios. So, there

are a lot of solutions available. There

are a lot of trained experts that will help you do your start with BTP and create your individual scenarios on top

of a robust platform here. And then the last point of view and this is basically also why we're talking today. It's a

platform for you as customers, right?

And as said before, it is a very modern development platform that helps you create your individual custom

integrations applications agents AI scenarios and that contains the model on the one hand side maybe but also maybe just the scenario leverage in an

external model and then handling those things with all the aspects on what is the data foundation for that how do I do the life cycle management for those

scenarios on top of a very solid uh foundation here.

So now it's uh time and I hope this made it clear what we're doing. So you see here also a little bit the core pillars

that we are looking at when we talk about those different pillars here. The

development pieces, the integration pieces, AI and data and in the end also those core platform capabilities

like security but also extended with specific compliance services that are really relevant in the business area.

maybe not so much if you're a private dealer.

So, um let's continue with a short insight into what we're actually offering in the different areas. Let's

start with the agent and application development section. So basically when

development section. So basically when we talk about um application and agent development, we really want to address

all kinds of developers with all the different technologies uh that we're seeing in the market that really support

um a fast and reliable um development which means that this contains um low code procode tools. But of course

all enabled by AI and supported by AI to really fulfill the tasks easier and faster with all the capabilities that

we're seeing today and with the clear strategy also to target the the developers in their common environments.

And this is a little bit a change that that we're seeing here that we really want to be open want to bring our capabilities into the environments the

development environments that are used rather than really creating only our own tool sets here.

So what is it that we're looking in?

It's of course focusing a lot on extensions of business applications.

Naturally as SAP we have this business process in mind and if there is something where you need to really have custom extensions

um then it's definitely the platform that makes it easy um to do those things. um make it easy also with the um

things. um make it easy also with the um um programming models that we give you to integrate this into your um

applications that you're having. This is

not restricted to just SAP applications but of course optimized um for those um which means that for example when it

comes to the automation of steps so tasks or processes that we're also working together with um other technology pieces of our portfolio like

for example Zignavio where you can then figure out where do you have challenges, issues in your processes or just room

for improvement.

So you define it there and then you can use BTP directly to overcome some findings here. In a lot of cases there's

findings here. In a lot of cases there's already content available that will help you uh to find a fast solution to your improve your process performance for

example. So it's really also about

example. So it's really also about getting to a higher uh degree of automation um within your processes be it on the task side or

cross-system processes for example right where you have the challenge that you have tasks that span across different um

applications need data from different applications to do the right decisions for example then bringing this together, accessing the right data, having it

completely integrated into the process, but still being on top of different applications that make our make of my

overall process, which then in the end leads to the fact that you have less [snorts] media breaks or having to change user interface or whatever.

Now if if we talk about the user and is his integration into the processes, it's also the possibility that we're offering our customers to create meaningful

digital workspaces, right? Bringing together all the tasks

right? Bringing together all the tasks of all the applications that make up the work of an employee and combine it also

with the necessary information sources or collaborative tools or data that is required to do his job in just one

meaningful place because he is not interested actually in in which system he is working. He just wants to perform his work. Right? And then more and more

his work. Right? And then more and more important um you all know hopefully that with uh SAP Juul or with Juul we have

our agent that supports um the employees within the different lines of business or solutions for the lines of businesses with a lot of

capabilities and agents available.

Nevertheless, you of course have also your own specificities, your own businesses, your own developments, your own insights that you

want to also integrate into that um jewel um assistant and this is exactly what we're also providing here. So the

possibility to create skills and agents and run them then inside Juul to work also with the existing agents that we

are delivering here. And as said before, addressing the different parts of uh the developer community from people with

huge coding skills in whatever language to really people that are maybe more in the business IT area, the ones that in earlier times wrote maybe the

requirement documents and now are enabled with the tools to create things by themselves. of course with the

by themselves. of course with the control that is needed to really keep an eye on what is being done there. So what

we are doing is we're bringing those different development aspects uh together in our SAP build solution to

also have projects um available that include different types of development and still having a meaningful um view

into actually what is happening in those projects and having this general overview.

Um we are uh actually um looking into reducing the complexity of those uh projects of those development projects

to bring this together. Um also when it comes to um who is doing which parts um what does that mean from a licensing

perspective? So we really try to bring

perspective? So we really try to bring the complexity out of that uh development. Of course scaling how can

development. Of course scaling how can we create um applications that are really scalable

on the one hand side that keep your core clean of course as we are a sidebyside platform.

Um we are uh actually uh able to create completely decoupled solutions here.

Yeah. And in the end of course being faster and making it possible to have um uh

um a better and more reliable look on your developments um with very efficient developers.

So looking into some of the tools that we're providing here and as said we're not restricted to just those tools. you

can consume uh most of the build parts already today also out of uh open development environments if you're using um visual studio for example but also in

the toolings if we look at we have for example the um Juul studio which is our tool to give your users the opportunity

to use an intentbased coding approach so it's no coding it's really just telling what is my intent on what I want to do and then coming to the possibility or

giving um your developers the possibility to create meaningful agents or simple uh jewel skills

when it comes to codebased development of course that is a topic that is changing a lot due to the possibilities

of using AI to do code generation so we are using for example le cupbased generative tools here that help creating

the cup artifacts to stay in line with the cloud application um uh programming um model here. that actually makes it

easy to create um extensions and uh also leverage the capabilities of BTP by including very easily logging but

also things like audit logging um creating the data artifacts out of the box. Um so this is available for

the box. Um so this is available for example for Java for Node.js JS and on the other hand side if we talk about

codebased development it's not only the cloudnative world that we're addressing here build also offers an ABAB

environment which um provides the possibility to do ABAB based development also here of course in a new fashion

providing the possibility to use AIS for code generation for the creation of test data and so on that actually really

boost the productivity of your developments.

Um nevertheless also in the um uh in the low code area so really model based approaches we continue to have SAP build apps also

here of course more and more AI capabilities will um be requested or help uh helping to do that. But this in

the end also if I use code generation today if I do not understand what gen what is being generated then still it's hard for me to develop. So with those

tools here we also provide this capability for um other solution.

Now for the specific development of automations, we provide with build process automation

a component that helps creating workflow like um process uh automations

or also task automations in a classical way or also supported of course by AI capabilities

and what I already mentioned the entry for the employees. Uh that is also part of um the build portfolio is the SAP

work zone uh which provides the possibility to really create those meaningful um entries into the

um into the work that your employees have to perform. no matter what applications are behind uh giving him access to all the information the

applications uh and the people also that uh they need to collaborate with uh to perform their their jobs.

So basically um what we're trying to achieve is of course the effort and the productivity

um of our employees. And if you want to read some more on what that really means is there I would ask you to to also

maybe have a look at this um um at at this analysis uh of Gigm um and they were actually looking into now what can I really

achieve by using SAP build versus custom development solutions. very interesting

development solutions. very interesting read and pretty impressive the results that uh they were finding.

So before we go into the next pillar, this gives again an overview about what is included in SAP build for agent and

application development also besides the the solutions of course with the uh frameworks for UI but also

of course cup and for the ABAB based uh development with ABAB cloud. We're

providing also the frameworks uh and a lot of help [snorts] uh that makes it possible to create your applications fast and always in

combination with the core platform capabilities.

Uh providing the uh the possibility then to deploy to the respective runtimes and run and operate also those solutions

over the overall life cycle.

Now coming to integration. Um

integration um basically as said before it is important if we really want to improve

our processes, our agility and also our ability to innovate that we are talking about integrated uh processes.

um which include on the one hand and mainly the application integration with the most modern technologies but of course also the integration of our

partners of um governments where we have to um apply to certain regulations or um

topics like providing our invoices uh to a governmental um system in the end uh to be compliant

here. Um so that is basically the core

here. Um so that is basically the core of what we are looking at in the in the uh integration area. Nevertheless,

in times of AI, it's also the question how do we integrate and uh operate different AI agents? How can they talk

to each other? how do we actually integrate in that whole area of uh AI?

So this is also part of the uh offering that we're seeing here in the integration portfolio.

So yes, you could argue integration has been there for a long time should be more or less now something that is commodity to a certain extent this might

be true. Nevertheless also here we are

be true. Nevertheless also here we are seeing a lot of new requirements also new technologies uh that are important and we also have

to see that we have to operate in hybrid uh landscapes now. So in former times we had our on premise systems we had our middleware somewhere and then we

integrated. Now if we look at um the

integrated. Now if we look at um the application landscapes of most of our customers, we're seeing private cloud uh installations, we're seeing still on

premise installations, we're seeing public cloud installations and somehow all those different uh applications together have to span and create

integrated processes. So we have to make

integrated processes. So we have to make sure that we are able to operate on the different um stacks in the different landscapes. Um here this is what we are

landscapes. Um here this is what we are targeting with it. Um we also do not want to have separate integration

engines when it comes to B2B A to A or B2G uh integration separate API management systems that are not

integrated. So our approach is really

integrated. So our approach is really looking into a common approach which is mainly delivered by one product on B2P which is called SAP integration

suite which actually uh gives you the capabilities to have A2A B2B B2G

integration on a single platform having um eventbased capabilities to provide the entry into the um event- driven

architecture world having an API management integrated here um offering also the B2B or the required B2B

um let's say add-ons that that we're seeing are needed like um partner management solution

uh or an ex extended onboarding solution um for uh new business uh partners here to be integrated um into into the

solutions and also here of course we're using AI on the one hand side for example to speed up the integration of

new partners but also to create new integrations by also here bringing or generating development artifacts um

helping with AI to also see where we have complex integrations on looking into um scripts that you might have created

as part of your integration and optimizing those um or when you're using the API component here figuring out if

there are any any anomalies in the API usage and then reacting proactively on those. Uh this is part of the

those. Uh this is part of the integration engine. So I mentioned that

integration engine. So I mentioned that we have event uh capabilities as part of the integration suite. Nevertheless, we

see extended at some customers we see extended requirements when it comes to eventing. So this is why we have an

eventing. So this is why we have an additional component which is called integration suite advanced demand mesh that really provides a full-fledged

decentralized uh service mesh approach here um for extended requirements uh in the eventing

area.

So looking at integration suite here and um the advanced event mesh you see the different components here uh so the

integrated components of the solution um the other thing that you can uh read also here is400 business event types for example 5,000

APIs uh 4,200 built-in integrations this is basically another component of PTP which is content pre-delivered content

and I forgot to mention that also in the build area that we already deliver for example a lot of automations as content

reusable for you and this is the same here no matter if this is SAP solutions or third-party solutions in a lot of

cases we already offer to you a pre-built uh integration that you can we use to integrate between SAP and third party applications

but also between third party applications without any involvement of BTP. So we're really seeing and we also

BTP. So we're really seeing and we also see that in the reports of of analysts that the integration suite is an

enterprisegrade platform for all your um integration necessities going beyond just uh acting as an SAP

integration platform um here.

So uh next topic uh artificial intelligence and data foundation. So

what does that mean? We want to provide with BTP your AI um platform uh for the

future and to help you really getting the foot on the ground when it comes to start and then continue to run

also uh with AI. And so the first thing that is really crucial is the data part.

Um so having the access to the right data and also the right types of data no matter if these are

texts, files, graphs, pictures whatever it can be right to leverage it in your AI

developments and then if we look at the the data then also providing the right tools and technologies within the

database to process and work with those different types of data, right? And

maybe even giving or taking the possibility to bring machine learning algorithms, AI capabilities into the database itself.

And then on the other hand side, it's again it's the development effort of AI.

And if we talk about development of AI, there are different aspects, right? It

can be the task to create a new model.

More often, it's the task to bring AI functionalities maybe delivered by an LLM like check GPT or whatever into a

certain process. I mentioned for example

certain process. I mentioned for example the generation of a job posting, right?

So the question is how can we enable you to build those things um effectively? I

showed you already SAP build as the central development um solution suite um on the platform and this is also what we're using here. I was talking about

Juul Studio being the tool to create agents and skills for Juul.

Nevertheless, of course, you have all the other tools to to do development in the I AI um space and also deploy and

operate those. And this brings us to the

operate those. And this brings us to the next point which is run AI at scale. If

you want to run those things, you need to have the right infrastructures, the runtimes to do so to actually create um

the workloads for your specific scenarios to operate the life cycle of on the one hand side the models on the other hand side the scenarios and the

applications that you build on top and of course all that with um a robust security uh delivered by the platform.

And if we look at a lot of AI scenarios today, then it's not so much often about the models because a lot of models are already there. Right? If we look at the

already there. Right? If we look at the market, there are a ton of large language models uh that can be used.

Nevertheless, in a lot of cases, it's required to have specific knowledge and SAP has a lot of knowledge about the applications that you're using, about the processes that you're running,

right? And you have your own data that

right? And you have your own data that has to be included there. Nevertheless,

it's also about bringing you the connectivity to reuse all the great things that are out there and to give you a secure access to the models that

are available.

Now if we look at the challenges um of a lot of those scenarios, it's the pace of innovation that is quite difficult to come across at the moment

or to continue to be on top of the line.

It's moving so fast in the AI area that it is is a huge challenge to stay there. you developed a scenario, you did a lot of effort and time and

we're coming to that point to say which is the right model that I need to use and how can I fine-tune it and do the

ideal prompt uh and then you finally have found it but five weeks later it's not the latest model version uh of that vendor. There are other models coming up

vendor. There are other models coming up and how do you want to actually make sure that over the life cycle your solution that you have developed will

still bring the best results that are possible with the solutions that are in the market. And on the other hand side

the market. And on the other hand side how does it do that with a meaningful usage of resources. So also the cost

aspects and the possibilities to meter and monitor those has to be taken into consideration. And

what do we see and where this leads often to is that a lot of AI scenarios do not fail with creating a great proof

of concept or or a great prototype but really with the possibility to bring it to production, right? to also automate the processes

right? to also automate the processes that are necessary behind like automating trainings um retrainings

regenerations of models if you're using your own models but again also as said staying ahead of time when it comes to just following the pace with the models

that are available right so it's really in that productivity to oper operationalization um where we see a lot of projects fail

and this is exactly what we want to address with our platform.

So coming back a little to what now is this platform let's first focus on the data piece a little bit with HANA we are providing the perfect database for any

custom development. So on the one hand

custom development. So on the one hand side you can say it's the perfect solution for my applications and extensions that I have um for my for my processes because I

have the different data access options to our applications maybe also to BDC data products um or to external data stores. I can

still use that. I have a tiered storage system which makes it possible also to say what is the most important data that I need to access regularly. I will keep

that in memory. I have native storage extension. I have then data lake um um

extension. I have then data lake um um capabilities within HANA cloud to make use of that data. And if we talk about data then also very important we can

store every kind of data within um HANA cloud which means no matter if I'm looking at spatial data structured data unstructured data vectors knowledge

graphs graphs whatever it is we can store that and we can work with that in the same platform and in a lot of cases I said already

bringing down a lot of machine learning and AI high capabilities predictions inside the platform and directly operated inside the database.

On the other hand side, if we think a little bit further um how HANA is the correct or the the the best platform

when it comes to AI scenarios, it's also looking into wait a second there are those engines uh that offer me a lot of capabilities when it comes to work with

those. So I have all those different

those. So I have all those different models also in there and I have the engines to work with the uh with the models which means I can do similarity

search on the vector engine. I can do text embeddings um in there and I can use that for my rec scenarios in in AI.

I have the possibility with the knowledge graph engine to really create my own custom database object knowledge graph that I can use for my AI

scenarios. I can use the search and text

scenarios. I can use the search and text processing inside Hana cloud to make use of it in my AI scenarios and with the

agents that Hana cloud provides and the capabilities also of the MCP server leveraging those capabilities

it's even easier making use of the capabilities inside my um my scenario generation for my custom um AI scenario.

arios here.

So now then when we talk about AI and data foundation and if HNA provides the possibility for from a data perspective and I did

not even talk about the agentic memory.

So now how do I do that? Right? Hana

with its tiered model is the perfect solution to also keep the memory of your agents and to not forget the conversations your employees that do

with that right but on top on on BTP we are delivering a lot more with the AI capabilities that we're having. So we

already were talking about creating custom applications and extensions maybe even with AI or creating um agents. We saw the Jew

studio. Nevertheless, for the from the

studio. Nevertheless, for the from the perspective of the developer, it's even more like if we for example or if we have a scenario looking into documents,

we are providing services to classify extract information out of these documents to make information out of these documents much more reliable. If

we extract them in an automated fashion leveraging AI technology, we can use translation services in a contextaware form to have much better translation

results.

Now we also have of course a huge knowledge that we want to leverage. So

if you can think of code generation and if you try that with a large language model for ABBA simply that is going to be really difficult because the information that is spread in the

outside world around ABAB are let's say very fluent and and and separated but we have a pre-trained model that actually

does that code generation to help the developers and then with rapid one so I don't know if you're aware about that So

you all potentially know GPT models. So

general pre-trained transformer models, the large language models that are perfectly in understanding, writing and creating text, but not very well um

serving structured data that comes from relational databases or tables, right?

And what SAP announced at tech was the rpt1 or rapid one as we say which is a model that is optimized to work with

structured data and you have the access to use that for your structured data.

Then of course it's the capability of model access. So all those great models

model access. So all those great models that are out there public models we provide you the possibility to use them all with a single license. So you can

test them, you can also benchmark them um to see what is the best model for a particular scenario that you have to do and then over time also say does that

change? Can we change that in the

change? Can we change that in the future? Do we do or do we need optimized

future? Do we do or do we need optimized prompt? Then we have tools that help you

prompt? Then we have tools that help you even generate optimized prompts for the different models.

Now we have with the knowledge graph for SAP you have access to a lot of information that we're getting from the usage of our applications

of the processes that are spanning. So

it's a huge benefit if you create business related AI scenarios.

Now with the AI orchestration we are providing tools that actually bring a lot of those

tasks of a developer down to the layer of this foundation. So for example searching for the right model testing it independently doing benchmarks. But on

the other hand side also if you say okay I need to have grounding I need to have uh a prompt templating you should not do

that hardcoded in the scenario implementation you should bring that down because that is what is changing fast and where you see a lot of movement

in the AI development today and if you're bringing it down to this layer you can handle this centrally and Yes, you have to integrate this into your

applications, but we are providing exactly those SDKs to use this AI foundation within your developments. No

matter if you're developing in ABAB, in NodeJS or in Python, right? And then

as said before, the life cycle management of your AI projects. So

really, how can you keep up the pace with what's going on to really maintain those things?

I'm not going into many details on this slide here. Um I just want to provide

slide here. Um I just want to provide this as an overview about all not all a lot of the different components that we

are actually offering inside this AI foundation layer here on BTP, right? the

access to more than 40 models be it public models be it models that we are operating on our platform or models that

are SAP uh SAP's owned uh models benchmarking of those um optimizing the prompts the possibility to orchestrate

the different tasks that you need to have like prompt templating oh data masking right translations we want to do

maybe even within the communication of the different models. So all this can be brought to that layer and then

orchestrated and handled over the life cycle of your scenarios. Also here short look um on how this is delivered. We

were talking about build being the solution to provide the development tools specifically here the jewel studio

for agents and um skills for for Juul and um the um the specific AI capabilities with SAP HANA then

underneath.

Now coming to the last uh topic here very briefly that is the core platform capabilities.

It's about handling and operating this part of the platform in your company to make sure that the life cycle management on the one hand side of your

applications is working but on the other hand side also on the infrastructure itself right making it possible to

automate the creation of um instances of BTP for your different projects.

Automate this, make it easy to create and automate the processes around running such a platform and your

extensions and integrations on uh on this topic. Having a secure environment

this topic. Having a secure environment to do that, having the services that handle uh identity management, identity handling, but on the other hand side

also with extended capabilities handling privacy data, right? looking at data protection um going maybe one step further and

saying also what do we do with uh auditing or um how do we handle compliance issues? Do we have a

compliance issues? Do we have a possibility uh to figure out what are the requirements and maybe also defining

gaps in our uh compliance situation uh that we're having.

These things are actually making up the platform services. A lot of services

platform services. A lot of services that are simply the the gore work that has to be done actually to create and

operate custom solutions very well being integrated into that world of business applications that you are running um and maintaining

um uh with the with the business suite applications of SAP and sometimes Also of course when we

talk about cross system applications also for third party applications at least when it comes to integration that

is definitely um the possibility here.

So also here short overview uh about the different services that actually fulfill those um requirements

uh and then we are coming to the last real chapter looking into multicloud. So what does that mean and

multicloud. So what does that mean and what is this multicloud idea behind? So

basically if we look at how SAP B2P is delivered to you then in most cases uh you will look at a public cloud solution.

Um what does that mean? So at the moment we have uh at about 40 different locations uh worldwide so globally

spanning or spanning across the globe.

And we're working together with the big um hyperscala infrastructure providers AWS, Azure, Google Cloud Platform and

Ali Cloud. And and that's new since last

Ali Cloud. And and that's new since last year, we're also providing BP on SAP's own cloud infrastructure. So we also have now seven data centers

um where SAP actually provides also the infrastructure. So that means you can if

infrastructure. So that means you can if you're getting BTP you can you can choose between the different locations of BTP you do not have to be

at one location you can also spread several locations you have access to use those to create your applications and you're independent of the underlying

infrastructure provider of course in every case with a robust security and compliance framework underneath and the same is when it comes

to data protection and privacy.

Nevertheless, in certain areas there are certain requirements for certain industries. So in some of those

industries. So in some of those locations of the public cloud, we have some extended um offerings uh like for example EU

access where we have four data center locations currently where we guarantee that personal data is not leaving

um the EU or basically it also includes Switzerland for example and and Norway.

uh but this European room and also the access when it comes to maintenance and support all only is being done uh out of

that uh region. we have some other um other extensions to those public cloud environments when it comes to India,

Israel Korea KSA Switzerland uh and the United Arab Emirates to help specific customer segments being

compliant with the um uh with the requirements in those countries.

Nevertheless, of course, we see industries um regulated industries uh that even need to go beyond this. So,

what we're also offering currently in four different locations is a sovereign cloud offering where we can provide complete data, operational, technical

and legal sovereignity.

At the moment, these are the US, Canada, uh the combination of Australia and New Zealand and the UK. And we're planning

to have also this during 2026 for India and to European locations.

Another thing that we starting to offer now is sovereign cloud onsite. that is

for very specific large customers with sovereignity requirements where we even have the possibility to use or to bring

the complete infrastructure stack of the SAP with BTP on top into the data centers of the customers and then also

operate them uh exclusively for those customers.

So, here is an overview about the different locations uh and a little bit about the plans. Here's also um a QR code that you can use to have a look at

what we're planning when it comes uh to new locations uh in the future. And with

that, just in time, uh, hopefully I wanted to give you or to end with one slide that puts together all the different

important or very interesting sources of information. If you want to start your

information. If you want to start your journey now with BTP, uh getting guidance in the guidance framework, getting information on services, AI capabilities,

architecture or reference architectures for certain scenarios in discovery center.

uh learning for BTP. Uh if you starting, you also have access to the onboarding resource uh center where you get a lot

of great information for your start. You

have the possibility to create trial or use uh most of the services also in a free TF uh fashion if you have a

contract. So you can try out services

contract. So you can try out services without them uh generating cost. And for

all road map related stuff, please have a look at our road map explorer. And

with this, I am uh done with what I wanted to uh tell you and show you today. And I hope that uh a lot of you got some new

information, some better understanding on BTP. And I really would like to uh

on BTP. And I really would like to uh yeah encourage you to go into the deep dive sessions of all the different uh

chapters uh that I was talking to where you get a lot of more detail on how this uh looks like uh than in reality.

Back to Tanya.

>> Thank you so much Anna for this incredible presentation.

Uh we have some questions. I think we are already over the time. I will send you the questions and then we will answer

them in the comments area as I wrote in the chat. Um yeah, especially with

the chat. Um yeah, especially with questions about June, but we'll come to that in the comments area.

Then a big thank you for everyone who joined us today. I hope you got a lot of value from this session and I look forward to seeing you again next week and all the other upcoming session.

Again, a big thank you Anna for your incredible presentation.

And with this, have a great day, have a great evening depending on where you are.