Mohamed Ahmed Anwar of (ssc by stc) Saudi Cloud Computing Company shares how they are embedding Confluent through the OEM program to power secure, scalable AI with real-time data streaming across Saudi Arabia’s digital economy.
Saudi Arabia is rapidly emerging as a global AI powerhouse, a transformation fueled by a fundamental shift in how data is managed, processed, and activated.
Mohamed Ahmed Anwar, General Manager of Presales at (sccc by stc) Saudi Cloud Computing Company, explains why they adopted Confluent’s data streaming platform: cyber resilience and security, strong governance, and scalability paired with simplified operations at enterprise scale.
Anwar unpacks why data streaming is foundational to modern AI, from launching model-as-a-service offerings to enabling agentic architectures. He highlights how sccc by stcs strategic partnership with Confluent delivers value extending far beyond open source Apache Kafka®, including connectors, governance with schemas, Kubernetes-based deployment, self-balancing clusters, and Cluster Linking that make enterprise operations tractable without an “army of engineers”.You’ll Learn:
About the Guest:
Mohamed Ahmed Anwar is a seasoned technology leader with over 18 years of experience driving innovation across the IT industry. He has held leadership roles at global tech giants including Microsoft, Dell Technologies, and Pure Storage, where he led complex digital transformation initiatives with a focus on delivering business impact. Currently, he serves as the General Manager of Presales at sccc by stc, where he drives strategic efforts to empower Saudi organizations through advanced cloud services, accelerating their growth and digital modernization.
Throughout his career, Anwar has led initiatives in data analytics, cloud adoption, and artificial intelligence, enabling organizations to harness the power of emerging technologies. His passion for mentorship and team development is reflected in his dedication to nurturing talent and building resilient, future-ready teams. Anwar is driven by a belief in the transformative potential of technology, consistently working to bridge strategic vision with practical execution to deliver meaningful, lasting impact.
Guest Highlight:
“Batch computing is like getting your water from a water well. You have a bucket and are governed by the size of the bucket and by the speed and the strength in your arms while in the data stream. On a streaming platform, you have a stream of data. You govern it. You know how exactly you will direct this stream of data, how you will store it and so on. This actually affected the time-to-value for our customers.”
Episode Timestamps:
1:00 — Guest introduction & company overview
5:55 — Segment 1: Data Streaming Goodness
14:05 — Segment 2: Beyond the Stream
26:50 — Segment 3: Quick Bytes
30:15 — Joseph’s Top Takeaways
Dive Deeper into Data Streaming:
Links & Resources:
Our Sponsor:
Your data shouldn’t be a problem to manage. It should be your superpower. The Confluent data streaming platform transforms organizations with trustworthy, real-time data that seamlessly spans your entire environment and powers innovation across every use case. Create smarter, deploy faster, and maximize efficiency with a true data streaming platform from the pioneers in data streaming. Learn more at confluent.io.
0:00:00.2 Mohamed Ahmed Anwar: When we are talking about AI agents, the closer the data to the processing is the better performance, the better response time you get. Having this lift and shift model from the legacy systems to the new systems on the cloud, not only it reduces the operational overhead on the customer or on the organization, but it also gives them the opportunity to enhance their business, scale out or scale in as much as needed.
0:00:34.7 Joseph Morais: That's Mohamed Ahmed Anwar at sccc by stc. And this is Life is But a Stream, the web show for tech leaders who need real-time insights. Today, we're diving into how data streaming is powering Saudi Arabia's digital economy. From enterprise financial solutions to customer experiences to its role in the future of artificial intelligence. I'm Joseph Morais, your host and technical champion at Confluent. Let's get started. Thanks for coming on the show, Anwar. Let's jump right into it.
0:01:11.4 Mohamed Ahmed Anwar: Thank you, Joseph. So sccc by stc is a hyperscaler cloud provider in Saudi Arabia built from within Saudi Arabia to serve the region and specifically the growing demands of digital solutions in Saudi Arabia. I'm leading a team of technology generalists who are building the best practices and the most efficient digital solutions to our customers in Saudi Arabia.
0:01:41.6 Joseph Morais: So my follow-up to you is who specifically are your customers?
0:01:46.5 Mohamed Ahmed Anwar: Everything is driven by applications. I don't want to say everyone is our customer, but mainly business entities or government entities that are looking for innovative solutions while maintaining their operational costs and reducing their operational costs and efforts in order to focus on the main business of the entity are, of course, our customers. This includes financial services, energy sector, and of course, government services as well.
0:02:21.8 Joseph Morais: Got you. So it sounds like anyone could be your customer, but the bread and butter comes from those customers that are really generating a lot of data.
0:02:29.8 Mohamed Ahmed Anwar: Exactly.
0:02:30.6 Joseph Morais: So tell me, what is your company's high-level product or company strategy and how is data streaming involved?
0:02:36.8 Mohamed Ahmed Anwar: That's a very good question. The overall strategy is like any hyperscaler. It starts, of course, with providing the latest infrastructure as a service offerings built upon the top technology providers like Intel, NVIDIA, and so on. Of course, after this is the platform services, and here we will start seeing data streaming solutions, enterprise data streaming solutions like Confluent, at the heart of this portfolio, which is the platform as a service, where the customer or the user of the solution is reducing the infrastructure operational overhead and focusing more into the data and the application itself, moving now to a vast portfolio of software as a service that includes business applications like ERP, digital signage, and so on, and focusing now in 2025 and 2026 into the model as a service. So you're offering AI as a model without the need to operate infrastructure, operating systems, different types of databases. So we will just give you the workflow of the AI model as a service. I believe you notice that most of the solutions that I discussed or mentioned now has data in the heart of the solution. And depending on the amount of data producers and data consumers, data streaming is being more and more needed in most of the solutions, especially when we talk about generative AI.
0:04:20.9 Joseph Morais: Yeah, it makes a lot of sense to obviously, I'm going to admit it and I say it all the time, I'm biased. I'm all in on data streaming. But I was talking to somebody yesterday, and the truth is all data is generated in real time. The difference is, or is very close to real time, it's how it's consumed. That's really kind of the shifts. It's like the data can either pile up and then I can react to it, or I can react to it in real time. And that's event-driven architecture. So it makes a lot of sense that that has become kind of the core of your product offering.
0:04:54.3 Mohamed Ahmed Anwar: And if you notice, our behavior as application users has changed in the past couple of decades. Now we expect timely response or timely service. You are not submitting a request and waiting for a couple of days for the service that you requested to happen.
0:05:13.5 Joseph Morais: And I would take that a step further, there's a younger generation that's just behind us. And they're going to be the ones that are going to be running all of our IT systems. And they were born with iPads and tablets and high-speed internet. When I started on the internet, we used to dial in. You couldn't do, there was no high bandwidth. And their expectations of that almost instant gratification, I totally see that. And I see that driving everyone's expectations moving through the future.
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0:05:56.5 Joseph Morais: So, we set the stage. So, let's dive deeper into the heart of your data streaming journey in our first segment. So, we know Saudi Arabia's digital economy is evolving at an unprecedented pace, forcing shifts for business. Why is data streaming so important right now, Anwar?
0:06:12.6 Mohamed Ahmed Anwar: So, Vision 2030 is an ambitious program based on 96 initiatives that Saudi is targeting to diversify the economy, move it into more of a digital economy and enhance the type of services that is provided to the citizen and the residents and the tourists in Saudi Arabia. Out of these 96 initiatives, can you give me like a lucky guess how many of them are revolving around data?
0:06:44.8 Joseph Morais: I'm going to shoot high. I'm going to say 75.
0:06:48.1 Mohamed Ahmed Anwar: Well, very close. It's 66 initiatives.
0:06:51.5 Joseph Morais: Okay, good. That's still very good. It's two thirds.
0:06:54.2 Mohamed Ahmed Anwar: Exactly. Out of the 96 are revolving around data and data is always at the heart of it. So, when Saudi Arabia, for example, started public transportation services in Riyadh, before the actual operations of the trains and so on, the application was ready. It was also integrated with most of the banks in Saudi Arabia. So, you don't need to have your physical card with you all the time, but you can actually use your bank card as your ticket to the train. So, the importance of data revolves from the different behavior of the users, the different expectations from the users. Now, everything is digital and everything is right now, real time.
0:07:49.9 Joseph Morais: You're right. As people's expectations change, your architecture has to change. And I think that's why you see a lot of these digital native companies, whether it's LinkedIn or Apple or Uber, they were early adopters of data streaming. And then they were highly successful with their products. And that created that need. I think the idea is, hey, if I could summon a car by pressing a button, I should be able to check my bank statement in real time. Because if you could do that, someone else should be able to do the other thing. So, that's a really interesting point, and I don't think I've ever put it together. Now, let's talk about the results of that. What have you built or currently building with data streaming as part of Confluent OEM program?
0:08:37.1 Mohamed Ahmed Anwar: In my opinion, beautiful solutions or really interesting solutions. So, one of the use cases that was really attractive was the new system of parking in Riyadh City. Imagine the number of parking slots or parking area in a vast city like Riyadh with all the sensors and the payment machines. So, I want you to imagine the amount of data producers in this scenario. It's huge. In a city like Riyadh, specifically, it's huge. Now, we move into the consumer part, which is around three million cars in Riyadh. So, looking for a parking slot in different spaces, not only giving you or giving the end user the opportunity to book their parking slot on the designated area they are visiting, but also giving them a digital way finding traffic information, the best way to arrive to the slot. All of this is relying on real-time data. It cannot be done in batches.
0:09:51.7 Joseph Morais: That's incredible. So for our audience, if you're unfamiliar, the Confluent OEM program gives partners the easy button for data streaming, allowing them to embed our enterprise-grade platform with a unified Apache Kafka and Flink into their products with a complete, ready-to-use data streaming platform built and supported by industry experts. Our partners get to market faster, maintain focus on their core businesses, and eliminate avoidable costs and risks typically associated with open source technologies. Which leads me into my next question, Anwar. What were the large business or product challenges that you were addressing by implementing data streaming in some of your largest customers?
0:10:29.2 Mohamed Ahmed Anwar: So the first concern, of course, will be cyber resiliency and security. And this is one of the steps or the big differences between open source Kafka and an enterprise solution like Confluent. The security controls, the audit, the governance that you can add to your solution to secure your data, make sure the data is always secure. This is one of the most important thing. The second type, of course, is scalability. When we talk about scalability, it's not only how easy to scale up or out, but it's also how easy the management and the operation of the solution will still be after scaling up or out. Because you can always add more data producers or we can always add more consumers. You can always add more data streams. But managing it is the actual work here. So...
0:11:29.3 Joseph Morais: That's where the real work begins.
0:11:31.6 Mohamed Ahmed Anwar: This drives us also to the second most important thing is the scalability and the operability of the solution after scaling out from gigabytes to terabytes to petabytes of data.
0:11:42.7 Joseph Morais: We talked about the challenges. I'm curious, what did things look like for these customers before they implemented data streaming? What was their experience with day-to-day operations? Were they using batch before or were these brand new initiatives?
0:11:59.1 Mohamed Ahmed Anwar: The easy way was always use batches. Easier to operate, easier to maintain. If you add something or if something goes wrong, we can fix it in the next batch. Everything was like easier to maintain, but time to value totally different between real-time and batch. And this affects the business itself. So time to value affects the company or the organization can roll over their products and services. If I'm late to the market with my service, another provider will come with the service and take the market opportunity from my business. And then the next step was in data governance. How should I govern this data? How should I govern this data stream? Do I need to add data filters between the producer and the consumer? Do I need to do conversion between producer and consumer? So data conversion, data governance, security, all these challenges were fixed actually or really easy to address while moving from open source Kafka or from regular patches to an enterprise system like Confluent with sccc by stc.
0:13:15.6 Joseph Morais: Next, we're going to dive into why sccc by stc has chosen to work with Confluent to solve data challenges. But first, a quick word from our sponsor.
0:13:31.4 Speaker 3: Your data shouldn't be a problem to manage. It should be your superpower. The Confluent Data Streaming Platform transforms organizations with trustworthy real-time data that seamlessly spans your entire environment and powers innovation across every use case. Create smarter, deploy faster, and maximize efficiency with the true Data Streaming Platform from the pioneers in data streaming.
0:14:05.7 Joseph Morais: Now, we'll go beyond the stream on what made sccc by stc choose Confluent as the right partner for their journey ahead. All right, so we knew data streaming was the answer. What led sccc by stc to partner with Confluent over various open source or other vendor products?
0:14:21.5 Mohamed Ahmed Anwar: There is more than technology. Always, always, any solution has the technology, process, and people in inside the solution. So these are the things that create a product or create a technology. And what Confluent did differently than any other provider is coming with a complete plan on the three aspects of the solution, especially the people and the talent part. So what happened differently with Confluent than any other technology provider, we are not just giving you our intellectual property to resell or to distribute in the Saudi market, but we are coming to enable sccc by stc professional services team, solution architects on how to position, how to configure, how to maintain, and what are the best practices for data streaming. And this was the main differentiator alongside with the uniqueness of the solution itself in terms of how easy it is to use for the end user in terms of the integrability or the integration with sccc by stc ecosystem in terms of security tools, in terms of infrastructure monitoring and data infrastructure monitoring tools. So this integration, people and talent enablement, and of course the robustness of the solution itself was the main differentiators for Confluent to be the real choice of sccc by stc.
0:15:57.1 Joseph Morais: Right, so it's great technology plus a great partner equals success. That's a pretty easy equation I think for anybody. Now, as you were talking through it, Anwar, you talked about scaling, you talked about enterprise security. See, these are things I think when people start to work with open source technologies and it's not just limited to Apache Kafka. It could be Postgres, it could be Hadoop. There's a lot of these things that if you're just running in a proof of concept or the stakes aren't high or you're just experimenting, they work just fine. But as you realize and as your company realized that once you get to the enterprise level, the companies that have strong security controls, that have massive scale, that's when working on these open source technologies becomes a chore. So having those additional pieces that Confluent provides, whether it's the connectors, the self-balancing clusters, the ability to deploy using Kubernetes, cluster linking, I could go on and on, the governance features, none of that comes out of box with Apache Kafka. And I think that's when it becomes such a huge thing. When you start and you're just sending data to producers and consumers and then suddenly you're like, well, what about schemas? What about what about replication? What about high availability? And then it suddenly becomes, okay, we could do that, but you're gonna have to give me an army of engineers to do that. And it is really impressive the differentiation you can make when you just you build an enterprise level product, you add those extra pieces that make it easier, suddenly it becomes tenable to run with few engineers. And then like you said, that enablement, best practices, I'm really glad we're able to partner together. We mentioned governance a couple of times. So for anyone that's been following the show, you may know that we have a product called Data Governance. There's things underneath it like our data portal, our schema registry. I'm curious, how important is data governance to sccc by stc’s customers?
0:18:03.0 Mohamed Ahmed Anwar: The importance is growing day by day because lately the Saudi Data and AI Authority has launched a new data privacy governance framework, the classification of data as more categories and who can access this type of data, what type of data can be shared. So at any solution that you are trying to build, if there is data exchange or real-time data processing, you need to make sure that you are complying with the local, of course, governance attributes like PDBL and NCA, complying as well with the well-known international governance like GDPR and so on. So the compliance with these, it gives the solution, of course, better adaptability in terms of that you can replace or they can implicate the solution in other regions or further than Saudi Arabia. And this is one of the targets of most of the businesses here. Of course, it protects the business itself because any data leakage or any data breaches might, as you know, result in bad reputation or even further worse, let's say, consequences. So data governance and data security is one of the most important and let's say it's one of the most important features and most important aspects of Confluent and sccc by stc solution.
0:19:40.0 Joseph Morais: That's great. And I think it's extremely important, like you said, especially for that high quality data, but it's also often overlooked. People start producing data without schemas and then they find that that will become a problem as they start to onboard more and more users. So there's something we talk about quite a bit often here at Confluent, this idea of shifting left, the idea of bringing your processing of data closer to the source of it. And oftentimes that is your data streaming. I'm curious, have you seen any customers, any sccc by stc customers that have adopted this idea of shifting left and bringing that processing closer?
0:20:18.1 Mohamed Ahmed Anwar: The best approach, especially when we are talking about AI agents, the closer the data to the processing is the better performance, the better response time you get. Not only this, with real time streaming or data streaming. Now, if we are utilizing a retrieval augmented generation solution, then the update of this knowledge base or vector database of the model is much easier. Hence, the fine tuning of the solution or the retraining, if required, of the model to protect it from any model drift is much easier and happens much faster. This means because most of these solutions are directly connected to your end users. So any issue in these type of solutions will result in negative feedback directly. So protecting this type of solution and giving it a fast cycle of updates and fine tuning is a huge plus for the solution. And it assures that the service delivered by the solution or the technology is always up to date and it reduces any issues that happens in the future. Another thing, of course, is this is an easy way to move from on-prem legacy systems to cloud distributed or open systems that can scale easily, can have high availability built in inside it without the need of the operational overhead or extra software licenses. Having this lift and shift model from the legacy systems to the new systems on the cloud, whether it's containerized or platform services, not only it reduces the operational overhead on the customer or on the organization, but it also gives them the opportunity to enhance their business scale out or scale in as much as needed.
0:22:36.0 Joseph Morais: You stole my thunder a little bit with my next question because you already talked about it a little bit, but what's the future of data streaming and AI at sccc by stc?
0:22:46.5 Mohamed Ahmed Anwar: Wow, it's promising. It's very promising. Now, because with the robust solution that Confluent, you can face the technology changes and advancement with trust. Now we are moving more into the context engineering, and this has a huge impact. Context engineering cannot happen without data streaming. Now I will read the data directly from the source. The system can access the data directly to the source. Not only this, but now the models are not only generating text or videos. It can generate business reports. It can integrate with business intelligence and data visualization tools to give you really attractive dashboards or holistic dashboards that gives you, for example, for some project that, as we talked, imagine the number of parking slots, parking meters, and so on across Riyadh. So having this and augmenting the solution with a large language model or an AI model to support the operations and to streamline the operation of the solution, this area needs more attention, create an alert to the maintenance team to go to this meter and so on. So now it's a different story. Data streaming is at the heart of it, and it will actually gain more attraction as we advance on the AI use cases and workflows.
0:24:36.3 Joseph Morais: So you touched on two things, and I want to unpack them individually. So the first one is this idea of facing technical advances as they come, or basically future-proofing your architecture. So as I mentioned earlier, more or less all data is generated in real time. It's just whether we consume it in real time or not. But by setting yourself up with the data streaming and having this real-time data available, you really do future-proof your architecture. Because whatever's going to come down the line, no one's going to say, I need the data faster than real time. Because then you'd be seeing the future. And if you figure that out, Anwar, please call me up. We can figure something. We'll start a business together. So if your baseline is right now, then you're future-proof for whatever's going to come out, whether it's a brand new implementation of large language models or even being able to route data to different generative AI services. Because there may be a great reason to have this data go to this provider and that provider, because you're baking them off or because they have different value propositions.
0:25:47.5 Joseph Morais: So having those data streams basically just means I can send this data to one place, to 100 places, and I can do that at the speed of real time, which I really can't get faster. And the other thing I wanted to call out is this idea of, so at Confluent, we call it our Data Streaming Platform. So our Data Streaming Platform is more than just data streaming. It's stream processing. It's governance. It's this integration suite that we call Connect. You need all of those pieces if you're talking about generative AI. The data has to be high quality. It has to be right now. It has to integrate with other things. And there's very few systems that I can think of that kind of compact in with all the tools. So you can go to one provider and have all of those outcomes. And I'm really happy that sccc by stc sees the value in the investments we've made in our technologies.
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0:26:52.8 Joseph Morais: So Anwar, before we let you go, we're going to do a lightning round. Byte-sized questions, byte-sized answers. That's right. That's B-Y-T-E, like hot takes, but schema-backed and serialized, because I know how important governance is to you. Are you ready? Let's go. What is your hot take on the future of artificial intelligence?
0:27:11.7 Mohamed Ahmed Anwar: It's the tool of the future, the collaboration tool of the future. I remember my generation growing up seeing personal computers working with collaboration tools like Excels and PowerPoints and so on. For the next generation, the new tool is generative AI, not only on the front of text generation or media generation, but I can see how it can help in education, healthcare, and of course, financial services.
0:27:42.8 Joseph Morais: Absolutely. I'm sure within a generation or two, people are going to forget about search engines and just ask their AI assistant for everything. So what's a non-tech activity or hobby that's impacted how you think about data?
0:27:55.1 Mohamed Ahmed Anwar: Gaming.
0:27:55.9 Joseph Morais: Gaming.
0:27:56.5 Mohamed Ahmed Anwar: Gaming. Of course, gaming. I'm a fan of first-person shooter games, especially where you play in a squad and there is a specific target that you need to achieve with your squad. So data streaming is a must in this type of games, whether it's for matchmaking, it's for gamer profiling, and of course, for the gamer experience. If I'm collecting something from the game or giving it to a colleague, I need to reach my partner in the squad at real time, I cannot wait for it to reach in a batch or something like that.
0:28:38.1 Joseph Morais: Some of those games you play, I guarantee are powered by Confluent. I don't know which ones I can talk about, which ones I can't, so I'm just going to leave it with that. So where are you getting outside inspiration from, Anwar, whether it's from a book or a thought leader?
0:28:49.5 Mohamed Ahmed Anwar: There was a very good book by Ben Stopford. It's called Designing Data... Sorry. Designing Driven Systems. And in this book, there is the practical concept of what is a distributed system, what is the real-time processing. And it's one of the eye-openers on how important and how this type of solutions like real-time data streaming is actually everywhere around us.
0:29:21.6 Joseph Morais: So Anwar, any final thoughts or anything to plug?
0:29:24.8 Mohamed Ahmed Anwar: I would like to thank the Confluent team on first, on introducing this type of innovative technology to sccc by stc, on enabling the whole commercial and architectural teams on the solution and what are the value proposition behind the solution and what is coming next with the solution, and supporting us build innovative AI solutions with our growing customer base in Saudi Arabia.
0:30:00.1 Joseph Morais: Amazing. Well, thank you so much for joining me today, Anwar. And for the audience, stick around because after this, I'm giving you my top three takeaways in two minutes.
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0:30:18.9 Joseph Morais: That was a great conversation with Anwar. Here are my top three takeaways. So Anwar mentioned that data streaming and Confluent's DSP is ideal for AI agents to prevent model drift, it's better for retrieval augmented generation. And honestly, I couldn't agree with him more. You need high quality, interconnected data at the speed of light. And all of those things are provided with the Data Streaming Platform, whether it's high quality data through governance, the inherent real-time nature of data streaming, stream processing to maybe do some preprocessing before you actually present the data to your AI agents, and that interconnectivity. All of our connectors, whether they're source connectors or sync connectors that pull data into your data stream, move data out of your data stream. We have vector partners, we have connectors to every flavor of database you can imagine. It really is an incredible tool for any organization that has the intent of building high-powered AI agents and utilizing agentic AI.
0:31:25.7 Joseph Morais: Another takeaway was that the Data Streaming Platform is an easy way for sccc by stc customers to move data from on-prem to cloud services. Now, that's not just limited to somebody migrating to the cloud, which plenty of our customers do. Having data in both places is very attractive for that migration. But it's not just that. Some people just want to build persistent pipelines to the cloud. Perhaps you have a bunch of on-prem resources, you have a data center, you're never going to get rid of it because it's affordable, you have 10 years to commit, but you still want to utilize some of these cloud services that are native to the cloud only, something like our partner, like Snowflake. There is no on-prem Snowflake. So you need to have a conduit, a robust, scalable pipeline, and Confluent can help you do that and so can sccc by stc.
0:32:12.3 Joseph Morais: And I really want to close on something that Anwar said that really made me feel good as a five-year Confluent employee, and that the partnership with Confluent and sccc by stc is more than just technology. It's the partnership itself. It's the relationships. It's Confluent coming through, enabling sccc by stc, setting best practices, and even helping collaborate on changes for our technology. For any OEM partner or anyone seeking OEM relationship with Confluent, hopefully Anwar's message resonates with you.
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0:32:47.5 Joseph Morais: That's it for this episode of Life is But a Stream. Thanks again to Anwar for joining us, and thanks to you for tuning in. As always, we're brought to you by Confluent. The Confluent Data Streaming Platform is the data advantage every organization needs to innovate today and win tomorrow. Your unified platform to stream, connect, process, and govern your data starts at Confluent.io. If you'd like to connect, find me on LinkedIn, tell a friend or coworker about us, and subscribe to the show so you never miss an episode. We'll see you next time.