In the global race for artificial intelligence dominance, Southeast and East Asia present unique landscapes where the question isn’t simply about having the most advanced algorithms or the largest language models. As investors and entrepreneurs across these regions navigate the AI revolution, a critical question emerges: Is a pure AI software play enough to succeed in these diverse and complex markets?

The Allure of Pure Software

The appeal of pure AI software plays is undeniable. They promise scalability without physical infrastructure, potentially global reach without local logistics networks, and the ability to iterate rapidly without manufacturing constraints. For venture capitalists and founders alike, the economics can seem irresistible—high margins, relatively lower capital requirements compared to hardware-integrated solutions, and the potential for exponential growth.

This model has created tremendous success stories in Western markets, where companies like OpenAI, Anthropic, and Hugging Face have built valuable businesses focused primarily on AI software development. The temptation to replicate these successes in Asian markets is strong, particularly as the region embraces digital transformation at an accelerating pace.

The Case for Pure AI Software in East Asia

While integrated approaches often dominate in Southeast Asia, there are compelling examples of pure AI software plays finding significant success in East Asian markets, particularly in China, Japan, and South Korea. These markets present distinct characteristics that can enable software-focused AI companies to thrive.

China, in particular, has produced several world-leading pure AI software companies. SenseTime, one of the world’s most valuable AI startups with a valuation of $7.5 billion as of 2019, has built its empire primarily on computer vision algorithms and software platforms (Wired, 2019). Similarly, iFlytek has established global leadership in speech recognition and natural language processing without significant hardware integration.

According to the Center for Strategic and International Studies (2023), “Chinese companies such as iFlyTek and SenseTime routinely publish high-quality research and attend prestigious international conferences. Their software solutions have achieved widespread adoption both domestically and internationally.”

Several factors contribute to the viability of pure software plays in these markets:

1. Robust Digital Infrastructure

Unlike the variable infrastructure of Southeast Asia, East Asian economies like Japan, South Korea, and China’s tier-one cities boast world-class digital infrastructure. This creates a more homogeneous environment where pure software solutions can operate effectively without needing to address infrastructure gaps.

2. Massive Domestic Markets

China’s enormous domestic market provides pure software companies with sufficient scale to achieve profitability and continued innovation without immediate international expansion. This allows them to focus on software excellence rather than building physical infrastructure across diverse markets.

3. Strong Government and Enterprise Support

East Asian governments, particularly China’s, have provided substantial support for AI development through policies, funding, and market access. This creates a protected environment where pure software companies can develop their technologies with less immediate competitive pressure from global tech giants.

4. Advanced Technical Talent

Japan, South Korea, and China produce large numbers of highly skilled AI researchers and engineers. According to a 2024 Rouse report, “Two US companies held the largest AI patent portfolios: IBM (8,290) and Microsoft (5,930) followed by a group of Japanese and Korean consumer electronics companies,” demonstrating the technical capabilities supporting pure software innovation in these markets.

The Southeast and East Asian Reality

Despite these success stories, the broader reality across Asia—particularly in Southeast Asia—suggests that pure software approaches face significant challenges. These regions present distinct conditions that often necessitate more integrated approaches combining software with hardware, services, or physical infrastructure.

According to Yinglan Tan, founding managing partner at Insignia Ventures Partners, businesses that combine both online and offline elements have stronger competitive advantages in Southeast Asia: “We believe that companies in Southeast Asia that have real moats (sustainable competitive advantages) are atoms. If you are a pure bits business, I think there is not that much moat against the major software companies like Microsoft and Facebook, but if you have … logistics, local licenses, you have local offline moats, you’re generally more resilient to external competition” (CNBC, 2025).

Several factors contribute to this reality:

1. Infrastructure Gaps and Variability

Unlike more homogeneous developed markets, Southeast Asia presents dramatic infrastructure variability—from Singapore’s world-class digital ecosystem to emerging digital economies in Vietnam, Indonesia, and the Philippines. East Asian markets like Japan, South Korea, and China have advanced infrastructure but often with unique technical standards and requirements.

Pure software plays assume consistent underlying infrastructure that may not exist across these diverse markets. Companies that integrate their AI solutions with appropriate hardware or build complementary infrastructure often find greater success in addressing these gaps.

Verihubs, an Indonesia-based AI company in Insignia Ventures Partners’ portfolio, exemplifies this approach. Rather than simply developing AI authentication software, the company has built partnerships with local banks like BCA and financial services platforms like Payfazz to create an integrated solution that works for both banked and unbanked populations. As the first AI startup from Indonesia backed by Y Combinator, Verihubs demonstrates how combining AI software with local infrastructure partnerships creates a more effective solution for Southeast Asian markets.

2. Data Localization and Regulatory Fragmentation

Both Southeast and East Asia feature increasingly complex regulatory environments regarding data sovereignty, AI ethics, and technology deployment. China’s comprehensive AI regulations, Japan’s Society 5.0 framework, and emerging digital economy regulations across ASEAN create a patchwork of compliance requirements.

Pure software plays often struggle to navigate these varied regulatory landscapes, particularly when they involve sensitive data or critical sectors. Companies that combine AI software with local infrastructure, partnerships, or service components can more effectively address these regulatory challenges.

Shefali Dodani, VP of Investment and Indonesia Country Head at Insignia Ventures Partners, emphasizes the importance of considering local financial regulations in business models: “Founders should pay attention to being able to ensure not on a P&L basis, but — let’s say they take financing — the interest that they pay to these financing companies are also factored into unit economics, which five years ago, maybe this was not a core focus” (Insignia Business Review, 2023).

3. Localization Beyond Translation

The cultural and linguistic diversity across Southeast and East Asia demands localization that goes far beyond simple translation. Effective AI solutions must understand cultural nuances, business practices, and communication patterns that vary dramatically across the region.

Pure software approaches often underestimate the depth of localization required. Companies that combine their AI software with local service components, human expertise, or hardware adaptations can deliver more contextually appropriate solutions.

WIZ.AI, a Singapore-based AI company in Insignia’s portfolio, demonstrates this principle in conversational voice AI. Founded by Lu JianFeng, WIZ.AI deploys AI solutions that combine text-to-speech, automatic speech recognition, and natural language processing with hardware and consulting services to help enterprises scale their customer service operations across Southeast Asia. Their success stems not just from advanced language models but from deep integration with local telecommunications infrastructure and extensive customization for specific cultural and linguistic contexts across the region.

4. The Trust Factor

Across many Asian markets, particularly in sectors like finance, healthcare, and government services, trust remains heavily tied to physical presence and human relationships. Pure digital interactions, especially those powered by AI, often face adoption barriers related to trust and credibility.

Companies that combine AI software with physical touchpoints, human oversight, or hardware components can more effectively bridge this trust gap. This hybrid approach acknowledges the importance of human relationships while leveraging AI to enhance efficiency and capabilities.

Reconciling the Approaches: When Pure Software Can Win vs. When Integration Is Essential

The contrasting examples from East Asia and Southeast Asia suggest a nuanced reality: pure AI software plays can succeed under specific conditions, but integrated approaches offer more resilience across the broader Asian context.

Even the pure software success stories from East Asia reveal an evolution toward more integrated models. SenseTime, while starting as a pure computer vision software company, has gradually expanded into hardware partnerships, IoT solutions, and industry-specific applications that combine software with physical components. This evolution reflects the recognition that long-term defensibility in Asian markets often requires more than algorithms alone.

The key distinction appears to be market maturity and infrastructure consistency. In markets with advanced digital infrastructure, large-scale domestic demand, and strong technical talent—like parts of China, Japan, and South Korea—pure software plays can establish initial footholds. However, even in these markets, the most enduring companies tend to evolve toward more integrated approaches over time.

Successful Models: Beyond Pure Software

Across Southeast and East Asia, the most successful AI implementations typically fall into several categories that extend beyond pure software plays:

AI-Enabled Hardware

Companies that embed AI capabilities into specialized hardware have found particular success in sectors ranging from agriculture to manufacturing. These solutions address the reality that many potential AI applications in the region involve physical processes or environments where standard computing devices are insufficient.

In agricultural technology, for instance, companies combining AI software with specialized sensors, drones, or processing equipment have gained traction by addressing the specific needs of local farming practices. Similarly, in manufacturing, AI solutions integrated with robotics or specialized machinery have proven more effective than pure software approaches.

AI + Services Hybrids

Another successful model combines AI software with service components delivered by human teams. This approach recognizes that in many Asian markets, particularly for enterprise solutions, customers expect implementation support, customization, and ongoing service relationships.

GANI.AI, a legal technology company in Insignia’s portfolio, exemplifies this hybrid approach. Founded by Indonesian lawyer Bintang Hidayanto and AI expert Timur Nugroho, GANI.AI combines generative AI, natural language processing, and legal expertise to automate legal document workflows. Rather than offering just software, they provide a comprehensive solution that includes intelligent contract drafting, review automation, and legal risk assessment services, making it effective for law firms and corporations across Southeast Asia.

Vertical Integration

Perhaps the most distinctive pattern in successful Asian AI companies is vertical integration—controlling multiple layers of the value chain rather than focusing solely on the software layer. This approach addresses the fragmentation and inefficiencies common in many Asian markets.

Investment Implications

For investors considering AI opportunities in Southeast and East Asia, these realities suggest several strategic implications:

1. Value Chain Analysis: Evaluating not just the AI technology itself but its position in the broader value chain and whether additional components (hardware, services, infrastructure) are necessary for effective deployment.
2. Regulatory Navigation Capabilities: Assessing a company’s ability to adapt to varied regulatory environments and compliance requirements across different markets.
3. Localization Depth: Looking beyond surface-level localization to understand how deeply a solution addresses local market needs, cultural contexts, and business practices.
4. Infrastructure Independence: Considering whether a solution can succeed despite infrastructure limitations or variability across target markets.

As Yinglan Tan suggests, one way to build successful AI businesses in the region is to find “what may be seen as a traditional business, but [inject] AI into it, to make it more efficient, increase margins, optimize revenue, open up new products, and have an online, offline experience” (CNBC, 2025).

The Path Forward

While pure AI software plays have demonstrated success in specific East Asian contexts with robust infrastructure and large domestic markets, the most transformative opportunities across the broader Asian landscape likely lie in more integrated approaches. Companies that recognize the unique characteristics of these diverse regions and build solutions that address them holistically—combining software with hardware, services, or infrastructure as needed—will be better positioned for long-term success.

For entrepreneurs building AI companies targeting these markets, this suggests several strategic considerations:

1. Start with the Problem, Not the Technology: Understanding the specific challenges in target markets and designing solutions that address them comprehensively, even if that means extending beyond software.
2. Build for Variability: Creating flexible architectures that can adapt to different infrastructure environments, regulatory requirements, and cultural contexts.
3. Consider Physical Components: Evaluating whether hardware elements, service networks, or physical infrastructure would enhance adoption, trust, or effectiveness.
4. Invest in Deep Localization: Going beyond translation to understand the cultural, business, and regulatory nuances of each target market.

As AI continues to transform industries across Southeast and East Asia, the most successful implementations will likely be those that recognize that in these diverse and complex regions, pure software is rarely enough for sustained competitive advantage. The future belongs to integrated approaches that combine the power of AI with the necessary components to make it truly effective in these unique contexts.

References

1. CNBC. (2025, April 25). Venture capitalists in Southeast Asia turn to offline businesses. Retrieved from https://www.cnbc.com/2025/04/25/enture-funds-becoming-pe-funds-venture-capitalists-in-southeast-asia-make-pe-like-deals-into-offline-businesses-.html
2. Insignia Business Review. (2023, November 30). 6 Things to Know About a VC’s Mindset in Indonesia on Startup Fundraising. Retrieved from https://review.insignia.vc/2023/11/30/venture-capital-indonesia-startup-fundraising/
3. Insignia Business Review. (2025, April 15). In the Age of AI, Moats Matter More Than Ever: Why Defensibility is Your Startup’s Most Valuable Asset. Retrieved from https://review.insignia.vc/2025/04/15/moats-ai/
4. Insignia Ventures Partners. (2025). GANI.AI Portfolio Company. Retrieved from https://www.insignia.vc/portfolio/gani-ai
5. Insignia Ventures Partners. (2025). Verihubs Portfolio Company. Retrieved from https://www.insignia.vc/portfolio/verihubs
6. Insignia Ventures Partners. (2025). WIZ.AI Portfolio Company. Retrieved from https://www.insignia.vc/portfolio/wiz-ai
7. Wired. (2019). The Rise of Chinese AI: SenseTime and the New World Order. Retrieved from https://www.wired.com/story/china-ai-sensetime/
8. Center for Strategic and International Studies. (2023). China’s AI Ecosystem: Current Capabilities and Future Directions. Retrieved from https://www.csis.org/analysis/chinas-ai-ecosystem