Ghada Ismail

Imagine you're building a skyscraper. Every floor relies on the strength of the one beneath it. Startup financing works pretty much the same way. A business isn't funded by one cheque or one investor; it is built layer by layer using different types of capital, each with its own level of risk, reward, and priority.

That layered structure is known as the capital stack, and it's one of the most important concepts every founder should understand before raising money.

Think of a capital stack like a layered cake

Let’s say you're building a company worth SAR 10 million. The money that financed that company didn't necessarily come from one source.

Instead, it may have been assembled from different layers:

• Founders' own money 
• Friends and family 
• Bank loans 
• Venture capital 
• Government financing 
• Revenue generated by the business 

Together, these funding sources form the company's capital stack.

In short, a capital stack is the combination of all the money a business uses to finance its operations and growth.

The order of these layers also determines who gets paid first if the company is sold or liquidated.

Why does the order matter?

Because not every investor takes the same level of risk, those who take less risk usually receive lower returns but get paid first. While those who take the biggest risk expect higher returns but are paid last.

A simplified capital stack looks like this:

1. Senior Debt 
2. Junior or Mezzanine Debt 
3. Preferred Equity 
4. Common Equity (Founders and shareholders) 

The higher you are in the stack, the safer your investment.

The lower you are, the greater the risk, but also the potential reward.

Breaking down each layer

Senior Debt

This is usually the safest form of financing. Think of bank loans or financing from traditional lenders. Because these lenders expect repayment regardless of how well the business performs, they often require collateral and receive priority if anything goes wrong. The trade-off? Interest rates are generally lower because the risk is lower.

Mezzanine Debt

This sits between debt and equity. Mezzanine financing is riskier than bank debt but safer than equity. It often comes with higher interest rates and sometimes gives lenders the option to convert part of the loan into company shares later. Growing companies sometimes use mezzanine financing when they need more capital but don't want to dilute ownership too much.

Preferred Equity

Preferred shareholders own part of the company but receive special rights. For example, they may get paid before ordinary shareholders when dividends are distributed or if the company is acquired. Many venture capital firms invest through preferred shares because they offer additional protections while still allowing investors to benefit from future growth.

Common Equity

This is where founders, employees with stock options, and ordinary shareholders sit. They own what's left after everyone above them has been paid. That sounds risky, but if the company becomes highly successful, common shareholders often enjoy the largest financial upside.

That's why startup founders are willing to take this position.

A startup example

Imagine a Saudi startup raises SAR 12 million to expand.

The funding might look like this:

• Founders invest SAR 2 million 
• A bank provides SAR 3 million 
• A venture capital fund invests SAR 7 million 

The capital stack now contains both debt and equity.

If the startup eventually succeeds and is sold for SAR 100 million, everyone gets paid according to their position in the stack. If the company struggles, the bank is usually repaid first, while founders are last in line.

Why founders should care

Many entrepreneurs focus only on how much money they can raise, while experienced founders think about where that money comes from. It’s also important to know that every financing option changes the capital stack. Too much debt may increase repayment pressure. Meanwhile, giving away too much equity reduces ownership and future upside. So, the best capital stack is the one that balances growth with financial flexibility.

As startups mature, their capital stacks often become more sophisticated, combining venture capital, venture debt, revenue-based financing, government programs, and traditional lending.

Choosing the right mix can lower financing costs while preserving founder control.

To Wrap Things Up…

A capital stack isn't just a finance term; it's rather a roadmap showing who has invested in your company, how much risk each party has taken, and who gets paid first when value is created.

For founders, understanding the capital stack means making better fundraising decisions instead of simply accepting the first available source of capital.

After all, raising money isn't just about getting funded. It's about building the right financial foundation for long-term growth.

Noha Gad

Artificial intelligence is making business faster, smarter, and more efficient, paving the way for groundbreaking developments in recent years. Though most innovations have been positive, the rise of AI has also led to the emergence of deepfakes that are used for more harmful purposes, including fraud and deception.

Deepfake attacks can target executives, finance teams, employees, and even customers, leading to financial losses, reputational damage, and security breaches, representing a business risk that can manipulate decisions. That is why it is becoming increasingly important for businesses to understand how these attacks work and how to protect themselves from them.

What are deepfake attacks?

A deepfake attack is a cyber-enabled deception where AI creates or alters audio, video, or images to convincingly impersonate a real person. Creating a deepfake is a complex process requiring vast amounts of data and computing power to help AI learn how to replicate the person's voice, appearance, and mannerisms. These digitally altered likenesses have the potential to reshape public opinion, damage reputations, and even sway political landscapes.

Generative adversarial networks (GANs) are clear examples of deepfakes. A GAN can be thought of as two AI systems in a digital tug-of-war. One AI, the generator, tries to generate fake content that looks real. The other, the discriminator, judges whether the content is real or fake. As the process iterates countlessly, each round makes the fake content more and more difficult to distinguish.

Deepfakes are at a crossroads between being a remarkable technological breakthrough and acting as a tool for deception. On one side, they offer exciting possibilities for the creative industries, such as filmmaking, gaming, and virtual reality. On the other side, their potential for abuse in spreading misinformation or malicious content cannot be ignored.

Why are startups especially exposed to deepfake attacks?

Startups need to treat deepfake attacks as a real business issue from the beginning, not something to address only after an incident happens. Unlike larger companies, startups usually have fewer layers of review. A fake message, voice note, or video from a founder, investor, or senior leader can be enough to trigger an urgent transfer, share sensitive data, or approve an action without enough checks.

Founders and executives usually share a lot of content across social media, interviews, webinars, and podcasts, which gives attackers material to imitate their voice, face, or style of speaking. At the same time, many startups do not yet have strong security policies or dedicated training, making them easier targets.

How can startups prepare for a deepfake attack?

The best defense against deepfake attacks is a mix of people, process, and technology. Companies should require multi-factor authentication, use callback verification for sensitive requests, and set clear approval rules for payments, data access, and executive instructions. Auditing the AI tool stack is a primary step to get ready and prevent deepfake attacks. Startups must find out the tools that teams actually use, as every voice note or video uploaded to these apps can be at risk of becoming training data for someone’s future scam. 

Startups should also require multi-factor authentication, use callback verification for sensitive requests, and set clear approval rules for payments, data access, and executive instructions. Employee training is also essential, as teams need to know how to spot warning signs, such as urgent messages, unusual tone or phrasing, and requests that bypass normal procedures. 

Building a response plan is another key step to prevent deepfake attacks. The plan should define who handles the issue, how it gets escalated, and how the company communicates internally and externally if a fake message or video spreads. It also helps to prepare templates in advance for internal alerts and public clarification.

Founders and early employees should be extra cautious about messages that claim to come from investors, partners, or executives. A small startup can lower its risk significantly by creating a culture where verification is normal, and no one feels pressured to act quickly without checking first.

Deepfake attacks are no longer a distant threat or a problem reserved for large corporations. As AI becomes more accessible, startups and businesses of all sizes must assume that fake audio, video, and images can be used to impersonate trusted people and manipulate critical decisions. By combining employee awareness, clear verification procedures, strong authentication, and a prepared response plan, startups can build a much stronger defense against deepfake attacks.

Ghada Ismail

A decade ago, artificial intelligence was largely viewed as a futuristic technology discussed in research laboratories and Silicon Valley boardrooms. Today, it writes code, detects diseases, powers government services, personalizes shopping experiences, and helps businesses make decisions in seconds. AI has rapidly evolved from a niche innovation into a transformative force that is reshaping industries and economies across the globe.

Every year on 16 July, Artificial Intelligence Appreciation Day celebrates these technological advances and the people driving them forward. Yet for Saudi Arabia, the occasion represents something even more significant. It is an opportunity to reflect on how artificial intelligence has become a central pillar of the Kingdom's economic transformation, driving innovation, attracting global investment, and creating entirely new industries under Vision 2030.

Rather than simply adopting AI technologies developed elsewhere, Saudi Arabia has pursued a far more ambitious goal: building an ecosystem where artificial intelligence can be developed, governed and commercialized at scale. In just a few years, the Kingdom has laid the foundations for an AI-powered economy through national strategies, digital infrastructure, talent development and partnerships with some of the world's leading technology companies.

From Vision 2030 to an AI Economy

Saudi Arabia's AI ambitions are rooted in Vision 2030, the national blueprint launched to diversify the economy beyond oil and position innovation at the heart of future growth. While digital transformation has long been a priority, artificial intelligence has evolved into one of the Kingdom's most strategic investments, underpinning everything from government services and healthcare to finance, manufacturing, and education.

A defining milestone came in 2019 with the establishment of the Saudi Data and Artificial Intelligence Authority (SDAIA), which was tasked with leading the Kingdom's AI and data agenda. The following year, the launch of the National Strategy for Data and AI (NSDAI) provided a comprehensive roadmap for developing AI capabilities, attracting investment, fostering innovation and creating a globally competitive digital economy.

Since then, Saudi Arabia has consistently demonstrated that AI is not merely a technology initiative but a national development strategy. The Kingdom has introduced policies to encourage innovation, developed governance frameworks for the responsible use of AI and invested heavily in the digital infrastructure needed to support increasingly sophisticated technologies.

This long-term commitment has translated into measurable international recognition. Saudi Arabia ranked first globally in the Government Strategy pillar of Tortoise Media's Global AI Index, an assessment that measures the strength of national AI policies, governance structures, public investment, and implementation. The ranking reflects more than ambitious targets. It recognizes the Kingdom's establishment of SDAIA, the rollout of the National Strategy for Data and AI, dedicated AI governance frameworks, sustained investment in digital infrastructure, and coordinated efforts to embed AI across government and industry. Together, these initiatives have positioned Saudi Arabia among the world's most proactive governments in developing a national AI ecosystem.

Saudi Arabia's AI by the Numbers

The scale of Saudi Arabia's ambitions is reflected in both its investments and expected economic impact. According to PwC, artificial intelligence is projected to contribute US$135.2 billion to the Kingdom's economy by 2030, equivalent to approximately 12.4% of GDP, making it the highest projected AI-driven economic contribution among Middle Eastern economies and one of the highest globally. Since establishing the Saudi Data and Artificial Intelligence Authority (SDAIA) in 2019, the Kingdom has launched the National Strategy for Data and AI (NSDAI), introduced the Arabic large language model ALLAM, established HUMAIN to accelerate AI infrastructure and innovation, and expanded AI applications across healthcare, finance, education, logistics, manufacturing, and government services. Alongside these initiatives, Saudi Arabia has introduced AI ethics principles and governance frameworks, demonstrating that its AI agenda extends well beyond technology adoption to encompass policy, talent development, infrastructure, and long-term economic transformation.

Saudi Startups Are Driving the Next Wave

Government initiatives may have laid the foundation, but Saudi Arabia's startup ecosystem is increasingly becoming one of the strongest drivers of AI innovation.

A growing number of startups are demonstrating that the Kingdom is moving beyond AI adoption to AI creation. Rather than simply integrating off-the-shelf technologies, these companies are developing solutions tailored to regional markets and real business challenges.

Mozn has emerged as one of Saudi Arabia's leading AI companies, using machine learning to combat financial crime, strengthen compliance and support smarter risk management for financial institutions. Lucidya has built one of the region's most advanced AI-powered customer intelligence platforms, helping businesses analyze Arabic-language conversations across social media and digital channels to better understand consumer behavior.

Meanwhile, Intelmatix is applying artificial intelligence to enterprise decision-making, enabling organizations to optimize operations and improve strategic planning through predictive analytics. Companies such as Salla and Zid are also embedding AI into e-commerce platforms, while startups across healthcare, logistics, cybersecurity and retail continue introducing AI-powered products designed specifically for regional markets.

The Next Frontier Is Trust

As artificial intelligence becomes increasingly sophisticated, experts believe the next stage of AI adoption will depend less on algorithms themselves and more on the quality, security, and resilience of the data that powers them.

According to Tim Pfaelzer, Senior Vice President and General Manager for EMEA at Veeam, organizations are entering what he describes as the "agentic era," where AI systems are evolving beyond simple assistants into autonomous digital workers capable of making decisions and performing tasks with minimal human intervention.

"AI is revolutionizing how organizations unlock value from their data, providing instantaneous insights and uncovering opportunities that were previously out of reach," Pfaelzer says.

He believes this shift is fundamentally changing how businesses operate.

"These agents are becoming autonomous, 24/7 digital workforces, scaling productivity and accelerating decision-making."

The scale of investment reflects this growing confidence. According to Pfaelzer, hyperscale technology companies have collectively invested more than US$650 billion to build the infrastructure supporting the next generation of AI innovation. At the enterprise level, adoption is accelerating rapidly, with 88% of organizations already piloting AI agents across their technology environments.

Yet despite this enthusiasm, readiness remains a significant challenge.

According to Veeam's research, only around 7% of organizations currently possess the foundational capabilities required to be genuinely AI-ready.

For Pfaelzer, the problem is not artificial intelligence itself—it is the quality of the data feeding these systems.

"The lack of visibility into data can cause AI models and agents to act on incomplete, outdated or inaccurate information, leading to unreliable outcomes at machine speed."

To address this challenge, Pfaelzer argues that organizations must establish what he describes as a "trust layer" built on complete data visibility, governance and resilience.

"By ensuring AI agents are powered by secure, accurate and readily recoverable data, businesses can unlock AI's full potential without allowing it to become their Achilles' heel."

For Saudi Arabia, this approach aligns closely with its broader AI strategy, which emphasizes responsible innovation alongside rapid technological advancement. As the Kingdom continues expanding AI adoption, building trustworthy and resilient data ecosystems may prove just as important as developing increasingly powerful AI models.

Celebrating Progress While Preparing for the Future

Artificial Intelligence Appreciation Day is often viewed as a celebration of technological breakthroughs. Saudi Arabia's story offers a broader and more compelling perspective.

The Kingdom's AI journey demonstrates that meaningful progress requires far more than sophisticated algorithms or headline-grabbing investments. It depends on long-term national planning, modern digital infrastructure, responsible governance, strategic partnerships and, above all, people capable of transforming innovation into real economic and social value.

Over the past several years, Saudi Arabia has methodically laid these foundations. Through Vision 2030, it has established national AI strategies, built world-class infrastructure, nurtured a vibrant startup ecosystem, attracted global technology leaders and accelerated AI adoption across sectors that directly affect the lives of millions of people.

The next phase of this journey will likely be defined not by the size of AI models or the speed of technological breakthroughs, but by how effectively artificial intelligence improves productivity, enhances public services, empowers businesses, and creates sustainable economic growth.

As the world marks Artificial Intelligence Appreciation Day, Saudi Arabia is celebrating more than the rise of a transformative technology. It is celebrating the emergence of an AI ecosystem built with a long-term vision; one that is positioning the Kingdom not simply to participate in the global AI revolution, but to help shape its future.

Mohamed Ramzy

Since its launch in the Egyptian market a few years ago, Klivvr has focused on building an integrated financial platform that combines payments, consumer financing, and rewards within a single application. Having surpassed EGP 1.2 billion in shareholder investments, the company is now gearing up for a new growth phase centered on investing more in technology and AI and expanding its innovative financing solutions.

In a short period, Klivvr has successfully built a financing portfolio worth EGP 1.5 billion, while expanding its network to include more than 700,000 users and over 1,000 partners and merchants. The company plans to invest an additional $10 million over the next two years to expand its customer base, financing portfolio, and partner network.

In an exclusive interview with Sharikat Mubasher, Nils Bachtler, Co-Founder and CEO of Klivvr, discussed the company’s strategy for the upcoming period, its investment plans, and its vision for the future of AI in the financial sector, as well as its growth and expansion targets within and beyond Egypt.

Klivvr was launched with a capital of EGP 100 million, with plans to reach EGP 500 million. Where does the company currently stand on these targets? And do you plan to increase capital over the next period to support growth and expansion plans?

We already achieved this target, as total shareholder investments in Klivvr have surpassed EGP 1.2 billion ($25 million), a milestone that reflects investors’ confidence in our business model and growth plans.

We plan to invest an additional $10 million over the next two years to continue developing the platform, enhancing the technological infrastructure, and launching new services.

How will Klivvr secure these new investments and how will it deploy them?

We will secure these investments from existing shareholders, not through new funding rounds or from additional investors.

From day one, Klivvr has bet on technology as the primary engine of its growth, and we still believe that investing in technology is the fastest way to build a more intelligent financial platform. Therefore, we will dedicate the largest share of the investment to developing digital infrastructure and AI, alongside launching more advanced products that enhance user experience.

Klivvr obtained final approvals to launch consumer financing activity in the Egyptian market. How do you assess the performance of this activity since its launch, and what level of demand have you witnessed so far?

We obtained the consumer financing license in April 2025 and officially launched the service in June 2025. Within a short period, the financing portfolio reached nearly EGP 1.5 billion, reflecting growing demand for our services.

Our focus is not limited to increasing financing volume alone; we are also working on diversifying financing products to meet the needs of different customer segments. Among the products we are currently developing are automotive financing solutions, as well as high-value financing programs that meet customers’ significant needs through flexible, convenient plans.

Today, Klivvr’s network includes more than 1,000 partners and merchants, spanning payment networks, financing partners, and merchants. This offers customers broader options to benefit from Klivvr’s services across the Egyptian market.

Klivvr launched ‘K·ai’ as the first AI-powered assistant in fintech applications in Egypt. How do you expect this product to transform customer experience?

From the outset, we noticed that a large segment of customers faces difficulty in understanding financial products or comparing different offers, which can lead to making decisions that do not align with their needs or capabilities. Hence, we designed ‘K.ai’ to be a personal AI-powered financial assistant that responds to users’ inquiries, explains financial products in a simple way, compares different financing options, and clarifies fees and requirements, thereby helping them make more informed financial decisions.

Within a short period of launching the service, we noticed a clear reduction in the pressure on customer service centers, as customers are now able to access all information they need directly through the application.

We also believe that AI will completely transform the future of financial services; thus, we will continue to invest in developing this technology and adding more features that make the user experience more intelligent and personalized.

With over 700,000 users and a remarkable growth in financing portfolio and activity since launch, what are Klivvr’s targets for the next two years? 

We do not measure growth solely by the number of customers, but rather by our ability to build an integrated financial ecosystem that delivers real value to the user. Accordingly, over the next two years, we aim to double our customer base, expand the financing portfolio and partner network, and launch new services.

Achieving these targets will depend on continuing to invest in technology and AI, strengthening the digital infrastructure, developing new financing solutions, and expanding the partner network. This will enable us to reach larger customer segments and enhance the daily usage of Klivvr’s platform.

What are Klivvr’s regional expansion plans for the upcoming years, notably in key markets, such as Saudi Arabia and the UAE?

With regard to geographic expansion, the Egyptian market remains our top priority, given the significant growth opportunities it offers; however, we expect regional expansion to begin after 2028.

We have not yet decided on a model for entering foreign markets. This can be through strategic partnerships, acquisitions, or launching new operations. The most suitable model will be decided based on the nature of each market and the opportunities available at the time of implementation.

Translated by: Noha Gad

Ghada Ismail

In the first part of this series, we explored why media buying matters for startups and how a well-planned advertising strategy can help young businesses reach the right audience. We also discussed the role of a media buyer in managing campaigns, optimizing budgets, and improving return on investment.

In Part Two, we will build on that foundation by examining the different types of media buying available to startups. Understanding these options can help founders choose the channels and buying methods that best align with their goals, target audience, and stage of growth.

Traditional Media Buying

Traditional media buying refers to purchasing advertising space through offline channels. Although digital advertising has become dominant, traditional media can still be valuable for startups seeking broad brand awareness.

• Television advertising: Suitable for startups targeting a large audience, though it often requires a significant budget.
• Radio advertising: Effective for local businesses and startups aiming to reach commuters or regional audiences.
• Print advertising: Useful for reaching niche audiences through newspapers, magazines, and industry publications.
• Outdoor advertising: Includes billboards, transit ads, and posters, which can help increase local visibility.

Traditional media buying can enhance credibility and brand recognition, but it may offer less precise targeting compared to digital channels.

Digital Media Buying

Digital media buying involves purchasing advertising space on online platforms. This is often the most practical option for startups because it offers detailed targeting, measurable results, and flexible budgeting.

• Search engine advertising: Ads appear on search engine results pages when users search for relevant keywords.
• Social media advertising: Platforms such as Facebook, Instagram, LinkedIn, TikTok, and X allow startups to target users based on demographics, interests, and behavior.
• Display advertising: Banner and visual ads appear on websites, apps, and online publications.
• Video advertising: Ads are shown before, during, or after online video content on platforms such as YouTube.

Digital media buying is particularly attractive for startups because campaigns can be adjusted quickly based on performance data.

Programmatic Media Buying

Programmatic media buying uses automated technology to purchase digital advertising space in real time. Instead of negotiating directly with publishers, advertisers use software platforms to bid for ad placements based on audience data.

• Real-time bidding (RTB): Advertisers bid for ad impressions as they become available.
• Private marketplace (PMP): Premium publishers offer ad inventory to selected advertisers through invitation-only auctions.
• Programmatic direct: Advertisers purchase ad inventory directly from publishers at a fixed price.

Programmatic buying allows startups to target specific audiences efficiently and optimize campaigns automatically.

Performance-Based Media Buying

Performance-based media buying focuses on paying for measurable results rather than simply paying for ad placement. This model is especially valuable for startups because it aligns advertising costs with business outcomes.

• Cost per click (CPC): Payment occurs when a user clicks on the ad.
• Cost per acquisition (CPA): Payment occurs when a user completes a desired action, such as making a purchase or signing up.
• Cost per lead (CPL): The startup pays for each qualified lead generated through the campaign.
• Cost per thousand impressions (Cost Per Mille or CPM): Payment is based on the number of times the ad is displayed.

Performance-based buying helps startups track ROI more accurately and allocate budgets to the channels that generate the best results.

Influencer and Native Media Buying

Influencer marketing and native advertising are increasingly popular media buying strategies for startups seeking authentic audience engagement.

• Influencer marketing: Startups partner with influencers to promote products or services to their followers.
• Native advertising: Ads are designed to match the format and style of the platform where they appear, making them less disruptive to users. For example: A fintech startup might sponsor an article on a business website titled “How Small Businesses Can Improve Cash Flow Management.” The article provides useful information while also mentioning the startup’s payment solution. Because it resembles regular editorial content and provides value to readers, it is considered native advertising.

These approaches can help startups build trust and reach targeted audiences in a more organic way.

Choosing the Right Media Buying Type

The best media buying strategy depends on a startup’s goals, target audience, budget, and growth stage.

• For brand awareness: Digital display ads, social media ads, and outdoor advertising can be effective.
• For lead generation: Search engine advertising and performance-based campaigns are often the best options.
• For niche targeting: Direct media buying, influencer marketing, and native advertising can deliver strong results.
• For scalable growth: Programmatic media buying allows startups to optimize campaigns efficiently as they expand.

To Wrap Things Up…

As we continue this media buying series, it becomes clear that there is no one-size-fits-all approach for startups. Each type of media buying offers unique advantages, and the right choice depends on the startup’s objectives, audience, and available resources.

For many early-stage startups, digital and performance-based media buying provide the most accessible and measurable starting points. As the business grows, programmatic, direct, and traditional media buying can become valuable additions to a broader marketing strategy.